mirror of
https://github.com/ggml-org/llama.cpp.git
synced 2026-07-10 07:57:54 +02:00
Compare commits
14 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
| 8cb1ad5a2c | |||
| 400d4bf0e2 | |||
| 5dca9f3470 | |||
| c264f65ff9 | |||
| 07e012afdc | |||
| ed8c26150e | |||
| 90e0f5cfcb | |||
| bbebeec4a8 | |||
| 230ea9d214 | |||
| f296fdfbed | |||
| f1161b15f2 | |||
| da46e59cbf | |||
| 0512ef1e5a | |||
| 4a7ee3126d |
@@ -9,6 +9,8 @@ on:
|
||||
'.github/workflows/hip-quality-check.yml',
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'**/*.cu',
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'**/*.cuh',
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'ggml/src/ggml-hip/CMakeLists.txt',
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'ggml/src/ggml-cuda/vendors/hip.h',
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'scripts/hip/gcn-cdna-vgpr-check.py'
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]
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@@ -18,6 +20,8 @@ on:
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'.github/workflows/hip-quality-check.yml',
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'**/*.cu',
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'**/*.cuh',
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'ggml/src/ggml-hip/CMakeLists.txt',
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'ggml/src/ggml-cuda/vendors/hip.h',
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'scripts/hip/gcn-cdna-vgpr-check.py'
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]
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||||
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||||
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+16
-4
@@ -27,6 +27,7 @@
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#include <cinttypes>
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#include <climits>
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#include <cstdarg>
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#include <filesystem>
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#include <fstream>
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#include <list>
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#include <regex>
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@@ -718,9 +719,8 @@ static bool common_params_parse_ex(int argc, char ** argv, common_params_context
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// model is required (except for server)
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// TODO @ngxson : maybe show a list of available models in CLI in this case
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if (params.model.path.empty()
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&& !params.usage
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&& !params.completion) {
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bool can_skip_model = params.usage || params.completion || !params.server_base.empty();
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if (!can_skip_model && params.model.path.empty()) {
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throw std::invalid_argument("error: --model is required\n");
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}
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}
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@@ -1240,6 +1240,13 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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params.completion = true;
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}
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));
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add_opt(common_arg(
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{"--server-base"}, "URL",
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string_format("connect to this server instead of starting a new one, example: 'http://localhost:8080' (default: none)"),
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[](common_params & params, const std::string & value) {
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params.server_base = value;
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}
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).set_examples({LLAMA_EXAMPLE_CLI}));
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add_opt(common_arg(
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{"--verbose-prompt"},
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string_format("print a verbose prompt before generation (default: %s)", params.verbose_prompt ? "true" : "false"),
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@@ -3451,9 +3458,14 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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||||
).set_env("LLAMA_ARG_LOG_FILE"));
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add_opt(common_arg(
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{"--log-prompts-dir"}, "PATH",
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"Log prompts to directory (only used for debugging, default: disabled)",
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"Log prompts to directory (auto-created if not present; only used for debugging, default: disabled)",
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[](common_params & params, const std::string & value) {
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params.path_prompts_log_dir = value;
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std::error_code ec;
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std::filesystem::create_directories(value, ec);
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if (ec) {
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fprintf(stderr, "warning: failed to create prompts-log-dir '%s': %s\n", value.c_str(), ec.message().c_str());
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}
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}
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).set_examples({LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}));
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add_opt(common_arg(
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@@ -644,6 +644,9 @@ struct common_params {
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std::map<std::string, std::string> default_template_kwargs;
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// CLI params
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std::string server_base; // if set, connect to this server instead of starting a new one
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// UI configs
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bool ui = true;
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bool ui_mcp_proxy = false;
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@@ -2,6 +2,16 @@
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#include <cpp-httplib/httplib.h>
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#ifdef _WIN32
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#include <winsock2.h>
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#include <windows.h>
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||||
#else
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#include <sys/socket.h>
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||||
#include <netinet/in.h>
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#include <arpa/inet.h>
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#include <unistd.h>
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#endif
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||||
|
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struct common_http_url {
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std::string scheme;
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std::string user;
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@@ -119,3 +129,63 @@ static std::pair<httplib::Client, common_http_url> common_http_client(const std:
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static std::string common_http_show_masked_url(const common_http_url & parts) {
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return parts.scheme + "://" + (parts.user.empty() ? "" : "****:****@") + common_http_format_host(parts.host) + parts.path;
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||||
}
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||||
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||||
static int common_http_get_free_port() {
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||||
#ifdef _WIN32
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||||
WSADATA wsaData;
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||||
if (WSAStartup(MAKEWORD(2, 2), &wsaData) != 0) {
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return -1;
|
||||
}
|
||||
typedef SOCKET native_socket_t;
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#define INVALID_SOCKET_VAL INVALID_SOCKET
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#define CLOSE_SOCKET(s) closesocket(s)
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||||
#else
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||||
typedef int native_socket_t;
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||||
#define INVALID_SOCKET_VAL -1
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#define CLOSE_SOCKET(s) close(s)
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#endif
|
||||
|
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native_socket_t sock = socket(AF_INET, SOCK_STREAM, 0);
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||||
if (sock == INVALID_SOCKET_VAL) {
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#ifdef _WIN32
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WSACleanup();
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#endif
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return -1;
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||||
}
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||||
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||||
struct sockaddr_in serv_addr;
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std::memset(&serv_addr, 0, sizeof(serv_addr));
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serv_addr.sin_family = AF_INET;
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serv_addr.sin_addr.s_addr = htonl(INADDR_ANY);
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serv_addr.sin_port = htons(0);
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||||
|
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if (bind(sock, (struct sockaddr*)&serv_addr, sizeof(serv_addr)) != 0) {
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CLOSE_SOCKET(sock);
|
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#ifdef _WIN32
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WSACleanup();
|
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#endif
|
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return -1;
|
||||
}
|
||||
|
||||
#ifdef _WIN32
|
||||
int namelen = sizeof(serv_addr);
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||||
#else
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||||
socklen_t namelen = sizeof(serv_addr);
|
||||
#endif
|
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if (getsockname(sock, (struct sockaddr*)&serv_addr, &namelen) != 0) {
|
||||
CLOSE_SOCKET(sock);
|
||||
#ifdef _WIN32
|
||||
WSACleanup();
|
||||
#endif
|
||||
return -1;
|
||||
}
|
||||
|
||||
int port = ntohs(serv_addr.sin_port);
|
||||
|
||||
CLOSE_SOCKET(sock);
|
||||
#ifdef _WIN32
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||||
WSACleanup();
|
||||
#endif
|
||||
|
||||
return port;
|
||||
}
|
||||
|
||||
@@ -362,7 +362,7 @@ class EvalState:
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||||
case = cases.get(task_id, {})
|
||||
status = case.get("status", "pending")
|
||||
expected = case.get("expected", "")
|
||||
answer = case.get("answer", "") if status == "ok" else ""
|
||||
answer = case.get("answer") or "" if status == "ok" else ""
|
||||
is_correct = case.get("correct", False) if status == "ok" else False
|
||||
response = case.get("response", "") or ""
|
||||
prompt = case.get("prompt", "") or ""
|
||||
@@ -647,7 +647,7 @@ class EvalState:
|
||||
question, prompt, expected = self.get_case(i)
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||||
case = cases.get(task_id, {})
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||||
status = case.get("status", "pending")
|
||||
answer = case.get("answer", "N/A") if status == "ok" else "N/A"
|
||||
answer = case.get("answer") or "N/A" if status == "ok" else "N/A"
|
||||
tokens = case.get("tokens")
|
||||
tokens_str = str(tokens) if tokens is not None else "N/A"
|
||||
tps_gen = case.get("tps_gen")
|
||||
|
||||
@@ -340,9 +340,6 @@ set(GGML_PUBLIC_HEADERS
|
||||
include/gguf.h)
|
||||
|
||||
set_target_properties(ggml PROPERTIES PUBLIC_HEADER "${GGML_PUBLIC_HEADERS}")
|
||||
#if (GGML_METAL)
|
||||
# set_target_properties(ggml PROPERTIES RESOURCE "${CMAKE_CURRENT_SOURCE_DIR}/src/ggml-metal.metal")
|
||||
#endif()
|
||||
install(TARGETS ggml LIBRARY PUBLIC_HEADER)
|
||||
install(TARGETS ggml-base LIBRARY)
|
||||
|
||||
|
||||
@@ -4709,10 +4709,16 @@ static bool ggml_backend_cuda_device_supports_op(ggml_backend_dev_t dev, const g
|
||||
} break;
|
||||
case GGML_OP_SET_ROWS:
|
||||
{
|
||||
return (op->type == GGML_TYPE_F32 || op->type == GGML_TYPE_F16 || op->type == GGML_TYPE_BF16 ||
|
||||
op->type == GGML_TYPE_Q4_0 || op->type == GGML_TYPE_Q4_1 || op->type == GGML_TYPE_Q5_0 ||
|
||||
op->type == GGML_TYPE_Q5_1 || op->type == GGML_TYPE_Q8_0 || op->type == GGML_TYPE_IQ4_NL) &&
|
||||
op->src[0]->type == GGML_TYPE_F32 &&
|
||||
return (
|
||||
(
|
||||
(op->type == GGML_TYPE_F32 || op->type == GGML_TYPE_F16 || op->type == GGML_TYPE_BF16 ||
|
||||
op->type == GGML_TYPE_Q4_0 || op->type == GGML_TYPE_Q4_1 || op->type == GGML_TYPE_Q5_0 ||
|
||||
op->type == GGML_TYPE_Q5_1 || op->type == GGML_TYPE_Q8_0 || op->type == GGML_TYPE_IQ4_NL) &&
|
||||
op->src[0]->type == GGML_TYPE_F32
|
||||
) || (
|
||||
op->type == GGML_TYPE_F16 && op->src[0]->type == GGML_TYPE_F16
|
||||
)
|
||||
) &&
|
||||
(op->src[1]->type == GGML_TYPE_I64 || op->src[1]->type == GGML_TYPE_I32);
|
||||
} break;
|
||||
case GGML_OP_SET:
|
||||
|
||||
@@ -322,17 +322,77 @@ static void set_rows_cuda(ggml_backend_cuda_context & ctx, const ggml_tensor * s
|
||||
}
|
||||
}
|
||||
|
||||
template<>
|
||||
void set_rows_cuda<half, int32_t>(ggml_backend_cuda_context & ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
|
||||
const half * src0_d = (const half *)src0->data;
|
||||
const int32_t * src1_d = (const int32_t *)src1->data;
|
||||
|
||||
GGML_TENSOR_BINARY_OP_LOCALS
|
||||
|
||||
cudaStream_t stream = ctx.stream();
|
||||
|
||||
|
||||
if (dst->type == GGML_TYPE_F16) {
|
||||
set_rows_cuda(
|
||||
src0_d, src1_d, (half*)dst->data,
|
||||
ne00, ne01, ne02, ne03,
|
||||
ne10, ne11, ne12, ne13,
|
||||
nb01, nb02, nb03,
|
||||
nb10, nb11, nb12,
|
||||
nb1, nb2, nb3,
|
||||
stream
|
||||
);
|
||||
} else {
|
||||
GGML_ABORT("unsupported type %s", ggml_type_name(dst->type));
|
||||
}
|
||||
}
|
||||
|
||||
template<>
|
||||
void set_rows_cuda<half, int64_t>(ggml_backend_cuda_context & ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
|
||||
const half * src0_d = (const half *)src0->data;
|
||||
const int64_t * src1_d = (const int64_t *)src1->data;
|
||||
|
||||
GGML_TENSOR_BINARY_OP_LOCALS
|
||||
|
||||
cudaStream_t stream = ctx.stream();
|
||||
|
||||
|
||||
if (dst->type == GGML_TYPE_F16) {
|
||||
set_rows_cuda(
|
||||
src0_d, src1_d, (half*)dst->data,
|
||||
ne00, ne01, ne02, ne03,
|
||||
ne10, ne11, ne12, ne13,
|
||||
nb01, nb02, nb03,
|
||||
nb10, nb11, nb12,
|
||||
nb1, nb2, nb3,
|
||||
stream
|
||||
);
|
||||
} else {
|
||||
GGML_ABORT("unsupported type %s", ggml_type_name(dst->type));
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
void ggml_cuda_op_set_rows(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
|
||||
const ggml_tensor * src0 = dst->src[0];
|
||||
const ggml_tensor * src1 = dst->src[1];
|
||||
|
||||
GGML_ASSERT(src0->type == GGML_TYPE_F32);
|
||||
GGML_ASSERT(src0->type == GGML_TYPE_F32 || (src0->type == GGML_TYPE_F16 && dst->type == GGML_TYPE_F16));
|
||||
GGML_ASSERT(src1->type == GGML_TYPE_I64 || src1->type == GGML_TYPE_I32);
|
||||
|
||||
if (src1->type == GGML_TYPE_I64) {
|
||||
set_rows_cuda<float, int64_t>(ctx, src0, src1, dst);
|
||||
if (src0->type == GGML_TYPE_F32) {
|
||||
if (src1->type == GGML_TYPE_I64) {
|
||||
set_rows_cuda<float, int64_t>(ctx, src0, src1, dst);
|
||||
} else {
|
||||
set_rows_cuda<float, int32_t>(ctx, src0, src1, dst);
|
||||
}
|
||||
} else if (src0->type == GGML_TYPE_F16) {
|
||||
if (src1->type == GGML_TYPE_I64) {
|
||||
set_rows_cuda<half, int64_t>(ctx, src0, src1, dst);
|
||||
} else {
|
||||
set_rows_cuda<half, int32_t>(ctx, src0, src1, dst);
|
||||
}
|
||||
} else {
|
||||
set_rows_cuda<float, int32_t>(ctx, src0, src1, dst);
|
||||
GGML_ABORT("unsupported type %s", ggml_type_name(src0->type));
|
||||
}
|
||||
}
|
||||
|
||||
@@ -24,62 +24,119 @@ if (GGML_METAL_NDEBUG)
|
||||
endif()
|
||||
|
||||
set(METALLIB_COMMON "${CMAKE_CURRENT_SOURCE_DIR}/../ggml-common.h")
|
||||
set(METALLIB_KERNELS_COMMON "${CMAKE_CURRENT_SOURCE_DIR}/kernels/common.h")
|
||||
set(METALLIB_KERNELS_DEQUANTIZE "${CMAKE_CURRENT_SOURCE_DIR}/kernels/dequantize.h")
|
||||
set(METALLIB_KERNELS_QUANTIZE "${CMAKE_CURRENT_SOURCE_DIR}/kernels/quantize.h")
|
||||
|
||||
set(METALLIB_KERNEL_SOURCES
|
||||
kernels/fa.metal
|
||||
kernels/mul_mv.metal
|
||||
kernels/mul_mm.metal
|
||||
kernels/quantize.metal
|
||||
kernels/softmax.metal
|
||||
kernels/norm.metal
|
||||
kernels/unary.metal
|
||||
kernels/binbcast.metal
|
||||
kernels/reduce.metal
|
||||
kernels/tri.metal
|
||||
kernels/ssm.metal
|
||||
kernels/wkv.metal
|
||||
kernels/gated_delta_net.metal
|
||||
kernels/solve_tri.metal
|
||||
kernels/rope.metal
|
||||
kernels/conv.metal
|
||||
kernels/upscale.metal
|
||||
kernels/argsort.metal
|
||||
kernels/pool.metal
|
||||
kernels/misc.metal
|
||||
)
|
||||
|
||||
if (GGML_METAL_EMBED_LIBRARY)
|
||||
enable_language(ASM)
|
||||
|
||||
add_compile_definitions(GGML_METAL_EMBED_LIBRARY)
|
||||
|
||||
set(METALLIB_SOURCE "${CMAKE_CURRENT_SOURCE_DIR}/ggml-metal.metal")
|
||||
set(METALLIB_IMPL "${CMAKE_CURRENT_SOURCE_DIR}/ggml-metal-impl.h")
|
||||
set(METALLIB_IMPL "${CMAKE_CURRENT_SOURCE_DIR}/ggml-metal-impl.h")
|
||||
|
||||
file(MAKE_DIRECTORY "${CMAKE_CURRENT_BINARY_DIR}/autogenerated")
|
||||
|
||||
# merge ggml-common.h and ggml-metal.metal into a single file
|
||||
set(METALLIB_EMBED_ASM "${CMAKE_CURRENT_BINARY_DIR}/autogenerated/ggml-metal-embed.s")
|
||||
set(METALLIB_SOURCE_EMBED "${CMAKE_CURRENT_BINARY_DIR}/autogenerated/ggml-metal-embed.metal")
|
||||
set(METALLIB_SOURCE_EMBED_TMP "${CMAKE_CURRENT_BINARY_DIR}/autogenerated/ggml-metal-embed.metal.tmp")
|
||||
set(METALLIB_EMBED_ASM_FILES "")
|
||||
foreach(src ${METALLIB_KERNEL_SOURCES})
|
||||
get_filename_component(kind ${src} NAME_WE)
|
||||
# symbol names must be valid C identifiers ('-' is not allowed)
|
||||
string(REPLACE "-" "_" kind_sym ${kind})
|
||||
|
||||
add_custom_command(
|
||||
OUTPUT "${METALLIB_EMBED_ASM}"
|
||||
COMMAND echo "Embedding Metal library"
|
||||
COMMAND sed -e "/__embed_ggml-common.h__/r ${METALLIB_COMMON}" -e "/__embed_ggml-common.h__/d" < "${METALLIB_SOURCE}" > "${METALLIB_SOURCE_EMBED_TMP}"
|
||||
COMMAND sed -e "/\#include \"ggml-metal-impl.h\"/r ${METALLIB_IMPL}" -e "/\#include \"ggml-metal-impl.h\"/d" < "${METALLIB_SOURCE_EMBED_TMP}" > "${METALLIB_SOURCE_EMBED}"
|
||||
COMMAND echo ".section __DATA,__ggml_metallib" > "${METALLIB_EMBED_ASM}"
|
||||
COMMAND echo ".globl _ggml_metallib_start" >> "${METALLIB_EMBED_ASM}"
|
||||
COMMAND echo "_ggml_metallib_start:" >> "${METALLIB_EMBED_ASM}"
|
||||
COMMAND echo .incbin "\"${METALLIB_SOURCE_EMBED}\"" >> "${METALLIB_EMBED_ASM}"
|
||||
COMMAND echo ".globl _ggml_metallib_end" >> "${METALLIB_EMBED_ASM}"
|
||||
COMMAND echo "_ggml_metallib_end:" >> "${METALLIB_EMBED_ASM}"
|
||||
DEPENDS ../ggml-common.h ggml-metal.metal ggml-metal-impl.h
|
||||
COMMENT "Generate assembly for embedded Metal library"
|
||||
VERBATIM
|
||||
)
|
||||
set(SRC "${CMAKE_CURRENT_SOURCE_DIR}/kernels/${kind}.metal")
|
||||
set(EMBED "${CMAKE_CURRENT_BINARY_DIR}/autogenerated/ggml-metal-embed-${kind}.metal")
|
||||
set(ASM "${CMAKE_CURRENT_BINARY_DIR}/autogenerated/ggml-metal-embed-${kind}.s")
|
||||
|
||||
target_sources(ggml-metal PRIVATE "${METALLIB_EMBED_ASM}")
|
||||
# only prepend headers that this source actually includes
|
||||
set(HEADERS_FOR_SRC ${METALLIB_KERNELS_COMMON})
|
||||
file(STRINGS ${SRC} _has_dequantize REGEX "#include \"dequantize\\.h\"")
|
||||
file(STRINGS ${SRC} _has_quantize REGEX "#include \"quantize\\.h\"")
|
||||
if(_has_dequantize)
|
||||
list(APPEND HEADERS_FOR_SRC ${METALLIB_KERNELS_DEQUANTIZE})
|
||||
endif()
|
||||
if(_has_quantize)
|
||||
list(APPEND HEADERS_FOR_SRC ${METALLIB_KERNELS_QUANTIZE})
|
||||
endif()
|
||||
|
||||
add_custom_command(
|
||||
OUTPUT "${ASM}"
|
||||
# Step 1: concatenate shared headers + this kernel source
|
||||
COMMAND cat ${HEADERS_FOR_SRC} ${SRC} > "${EMBED}.tmp1"
|
||||
# Step 2: remove internal #include and #pragma once
|
||||
COMMAND sed -e "/\#include \"common.h\"/d" -e "/\#include \"dequantize.h\"/d" -e "/\#include \"quantize.h\"/d" -e "/\#pragma once/d" < "${EMBED}.tmp1" > "${EMBED}.tmp2"
|
||||
# Step 3: inline ggml-common.h (replacing __embed_ggml-common.h__ sentinel)
|
||||
COMMAND sed -e "/__embed_ggml-common.h__/r ${METALLIB_COMMON}" -e "/__embed_ggml-common.h__/d" < "${EMBED}.tmp2" > "${EMBED}.tmp3"
|
||||
# Step 4: inline ggml-metal-impl.h
|
||||
COMMAND sed -e "/\#include \"ggml-metal-impl.h\"/r ${METALLIB_IMPL}" -e "/\#include \"ggml-metal-impl.h\"/d" < "${EMBED}.tmp3" > "${EMBED}"
|
||||
# Step 5: emit an asm chunk with kind-specific start/end symbols
|
||||
# note: '-' is illegal in C symbols, so we use kind_sym; the macOS
|
||||
# section name is limited to 16 chars so we keep it shared
|
||||
# across kinds (__ggml_metallib) and only vary the global symbols.
|
||||
COMMAND echo ".section __DATA,__ggml_metallib" > "${ASM}"
|
||||
COMMAND echo ".globl _ggml_metallib_${kind_sym}_start" >> "${ASM}"
|
||||
COMMAND echo "_ggml_metallib_${kind_sym}_start:" >> "${ASM}"
|
||||
COMMAND echo .incbin "\"${EMBED}\"" >> "${ASM}"
|
||||
COMMAND echo ".globl _ggml_metallib_${kind_sym}_end" >> "${ASM}"
|
||||
COMMAND echo "_ggml_metallib_${kind_sym}_end:" >> "${ASM}"
|
||||
DEPENDS ../ggml-common.h ggml-metal-impl.h
|
||||
kernels/common.h kernels/dequantize.h kernels/quantize.h
|
||||
kernels/${kind}.metal
|
||||
COMMENT "Generate embedded Metal library for ${kind}"
|
||||
VERBATIM
|
||||
)
|
||||
|
||||
list(APPEND METALLIB_EMBED_ASM_FILES "${ASM}")
|
||||
endforeach()
|
||||
|
||||
target_sources(ggml-metal PRIVATE ${METALLIB_EMBED_ASM_FILES})
|
||||
else()
|
||||
# copy metal files to bin directory
|
||||
# copy header files to bin directory
|
||||
configure_file(../ggml-common.h ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/ggml-common.h COPYONLY)
|
||||
configure_file(ggml-metal.metal ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/ggml-metal.metal COPYONLY)
|
||||
configure_file(ggml-metal-impl.h ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/ggml-metal-impl.h COPYONLY)
|
||||
|
||||
file(MAKE_DIRECTORY "${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/kernels")
|
||||
configure_file(kernels/common.h ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/kernels/common.h COPYONLY)
|
||||
configure_file(kernels/dequantize.h ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/kernels/dequantize.h COPYONLY)
|
||||
configure_file(kernels/quantize.h ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/kernels/quantize.h COPYONLY)
|
||||
|
||||
foreach(src ${METALLIB_KERNEL_SOURCES})
|
||||
configure_file(${src} ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/${src} COPYONLY)
|
||||
endforeach()
|
||||
|
||||
if (GGML_METAL_SHADER_DEBUG)
|
||||
# custom command to do the following:
|
||||
# xcrun -sdk macosx metal -fno-fast-math -c ggml-metal.metal -o ggml-metal.air
|
||||
# xcrun -sdk macosx metallib ggml-metal.air -o default.metallib
|
||||
#
|
||||
# note: this is the only way I found to disable fast-math in Metal. it's ugly, but at least it works
|
||||
# disabling fast math is needed in order to pass tests/test-backend-ops
|
||||
# note: disabling fast math is needed in order to pass tests/test-backend-ops
|
||||
# note: adding -fno-inline fixes the tests when using MTL_SHADER_VALIDATION=1
|
||||
# note: unfortunately, we have to call it default.metallib instead of ggml.metallib
|
||||
# ref: https://github.com/ggml-org/whisper.cpp/issues/1720
|
||||
# note: adding -g causes segmentation fault during compile
|
||||
#set(XC_FLAGS -fno-fast-math -fno-inline -g)
|
||||
set(XC_FLAGS -fno-fast-math -fno-inline)
|
||||
else()
|
||||
set(XC_FLAGS -O3)
|
||||
endif()
|
||||
|
||||
# Append macOS metal versioning flags
|
||||
if (GGML_METAL_MACOSX_VERSION_MIN)
|
||||
message(STATUS "Adding -mmacosx-version-min=${GGML_METAL_MACOSX_VERSION_MIN} flag to metal compilation")
|
||||
list (APPEND XC_FLAGS -mmacosx-version-min=${GGML_METAL_MACOSX_VERSION_MIN})
|
||||
@@ -90,35 +147,46 @@ else()
|
||||
list (APPEND XC_FLAGS -std=${GGML_METAL_STD})
|
||||
endif()
|
||||
|
||||
# Compile each kernel source to .air, then link into default.metallib
|
||||
set(AIR_FILES "")
|
||||
foreach(src ${METALLIB_KERNEL_SOURCES})
|
||||
get_filename_component(name ${src} NAME_WE)
|
||||
set(AIR "${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/${name}.air")
|
||||
list(APPEND AIR_FILES ${AIR})
|
||||
add_custom_command(
|
||||
OUTPUT ${AIR}
|
||||
COMMAND xcrun -sdk macosx metal ${XC_FLAGS} -I ${CMAKE_RUNTIME_OUTPUT_DIRECTORY} -c ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/${src} -o ${AIR}
|
||||
DEPENDS ${src} kernels/common.h kernels/dequantize.h kernels/quantize.h ${METALLIB_COMMON} ggml-metal-impl.h
|
||||
COMMENT "Compiling ${src}"
|
||||
VERBATIM
|
||||
)
|
||||
endforeach()
|
||||
|
||||
add_custom_command(
|
||||
OUTPUT ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/default.metallib
|
||||
COMMAND xcrun -sdk macosx metal ${XC_FLAGS} -c ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/ggml-metal.metal -o - |
|
||||
xcrun -sdk macosx metallib - -o ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/default.metallib
|
||||
COMMAND xcrun -sdk macosx metallib ${AIR_FILES} -o ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/default.metallib
|
||||
COMMAND rm -f ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/ggml-common.h
|
||||
COMMAND rm -f ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/ggml-metal.metal
|
||||
DEPENDS ggml-metal.metal ${METALLIB_COMMON}
|
||||
COMMENT "Compiling Metal kernels"
|
||||
)
|
||||
COMMAND rm -f ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/ggml-metal-impl.h
|
||||
COMMAND rm -rf ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/kernels
|
||||
DEPENDS ${AIR_FILES}
|
||||
COMMENT "Linking Metal kernels into default.metallib"
|
||||
)
|
||||
|
||||
# FIXME: only add to the ggml-metal target?
|
||||
add_custom_target(
|
||||
ggml-metal-lib ALL
|
||||
DEPENDS ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/default.metallib
|
||||
)
|
||||
)
|
||||
endif() # GGML_METAL_EMBED_LIBRARY
|
||||
|
||||
if (NOT GGML_METAL_EMBED_LIBRARY)
|
||||
install(
|
||||
FILES src/ggml-metal/ggml-metal.metal
|
||||
PERMISSIONS
|
||||
OWNER_READ
|
||||
OWNER_WRITE
|
||||
GROUP_READ
|
||||
WORLD_READ
|
||||
DESTINATION ${CMAKE_INSTALL_BINDIR})
|
||||
DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}/kernels/
|
||||
DESTINATION ${CMAKE_INSTALL_BINDIR}/kernels
|
||||
FILES_MATCHING PATTERN "*.metal" PATTERN "*.h"
|
||||
)
|
||||
|
||||
install(
|
||||
FILES ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/default.metallib
|
||||
DESTINATION ${CMAKE_INSTALL_BINDIR}
|
||||
)
|
||||
install(
|
||||
FILES ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/default.metallib
|
||||
DESTINATION ${CMAKE_INSTALL_BINDIR}
|
||||
)
|
||||
endif()
|
||||
|
||||
@@ -160,11 +160,15 @@ ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_get_rows(ggml_me
|
||||
return res;
|
||||
}
|
||||
|
||||
ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_set_rows(ggml_metal_library_t lib, ggml_type tidx, ggml_type tdst) {
|
||||
ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_set_rows(ggml_metal_library_t lib, const ggml_tensor * op) {
|
||||
char base[256];
|
||||
char name[256];
|
||||
|
||||
snprintf(base, 256, "kernel_set_rows_%s_%s", ggml_type_name(tdst), ggml_type_name(tidx));
|
||||
const auto tsrc = op->src[0]->type;
|
||||
const auto tidx = op->src[1]->type;
|
||||
const auto tdst = op->type;
|
||||
|
||||
snprintf(base, 256, "kernel_set_rows_%s_%s_%s", ggml_type_name(tsrc), ggml_type_name(tidx), ggml_type_name(tdst));
|
||||
snprintf(name, 256, "%s", base);
|
||||
|
||||
ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name);
|
||||
|
||||
@@ -112,7 +112,7 @@ struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_cpy
|
||||
struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_pool_1d (ggml_metal_library_t lib, const struct ggml_tensor * op, enum ggml_op_pool op_pool);
|
||||
struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_pool_2d (ggml_metal_library_t lib, const struct ggml_tensor * op, enum ggml_op_pool op_pool);
|
||||
struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_get_rows (ggml_metal_library_t lib, enum ggml_type tsrc);
|
||||
struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_set_rows (ggml_metal_library_t lib, enum ggml_type tidx, enum ggml_type tdst);
|
||||
struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_set_rows (ggml_metal_library_t lib, const struct ggml_tensor * op);
|
||||
struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_diag (ggml_metal_library_t lib, const struct ggml_tensor * op);
|
||||
struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_repeat (ggml_metal_library_t lib, enum ggml_type tsrc);
|
||||
struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_concat (ggml_metal_library_t lib, enum ggml_type tsrc);
|
||||
|
||||
@@ -94,8 +94,63 @@ int ggml_metal_pipeline_max_theads_per_threadgroup(struct ggml_metal_pipeline_wi
|
||||
return pipeline.pipeline->obj.maxTotalThreadsPerThreadgroup;
|
||||
}
|
||||
|
||||
//
|
||||
// MTLLibrary collection (one library per op-source, compiled separately)
|
||||
//
|
||||
|
||||
// Single source of truth for the per-kind metal libraries. The order here
|
||||
// defines the enum values and every per-kind table below, so adding a library
|
||||
// is a one-line change here (plus adding its source to CMakeLists.txt).
|
||||
// X(suffix, name): name is both the kernels/<name>.metal basename and the
|
||||
// ggml_metallib_<name>_{start,end} embed-symbol stem.
|
||||
#define GGML_METAL_LIBS \
|
||||
X(FA, fa) \
|
||||
X(MUL_MV, mul_mv) \
|
||||
X(MUL_MM, mul_mm) \
|
||||
X(QUANTIZE, quantize) \
|
||||
X(SOFTMAX, softmax) \
|
||||
X(NORM, norm) \
|
||||
X(UNARY, unary) \
|
||||
X(BINBCAST, binbcast) \
|
||||
X(REDUCE, reduce) \
|
||||
X(TRI, tri) \
|
||||
X(SSM, ssm) \
|
||||
X(WKV, wkv) \
|
||||
X(GATED_DELTA_NET, gated_delta_net)\
|
||||
X(SOLVE_TRI, solve_tri) \
|
||||
X(ROPE, rope) \
|
||||
X(CONV, conv) \
|
||||
X(UPSCALE, upscale) \
|
||||
X(ARGSORT, argsort) \
|
||||
X(POOL, pool) \
|
||||
X(MISC, misc)
|
||||
|
||||
enum ggml_metal_lib_kind {
|
||||
#define X(e, s) GGML_METAL_LIB_##e,
|
||||
GGML_METAL_LIBS
|
||||
#undef X
|
||||
GGML_METAL_LIB_COUNT,
|
||||
};
|
||||
|
||||
static const char * const k_lib_names[GGML_METAL_LIB_COUNT] = {
|
||||
#define X(e, s) [GGML_METAL_LIB_##e] = #s,
|
||||
GGML_METAL_LIBS
|
||||
#undef X
|
||||
};
|
||||
|
||||
struct ggml_metal_library {
|
||||
id<MTLLibrary> obj;
|
||||
// Per-kind compiled libraries. When single_library is true, the whole library
|
||||
// (e.g. a pre-compiled default.metallib or a from-source build) lives at
|
||||
// objs[0] and the remaining slots are nil.
|
||||
id<MTLLibrary> objs[GGML_METAL_LIB_COUNT];
|
||||
bool single_library; // true: combined library at objs[0]; false: per-kind libs in objs[*]
|
||||
|
||||
// Routing table: kernel function name -> objs[] index, populated from each
|
||||
// compiled library's -[MTLLibrary functionNames]. The actual compiled
|
||||
// libraries are the single source of truth for which library owns a kernel,
|
||||
// so adding kernels later requires no manual routing maintenance.
|
||||
// nil in single_library mode (everything resolves to objs[0]).
|
||||
NSMutableDictionary<NSString *, NSNumber *> * fn_to_lib;
|
||||
|
||||
ggml_metal_device_t dev;
|
||||
ggml_metal_pipelines_t pipelines; // cache of compiled pipelines
|
||||
@@ -103,160 +158,376 @@ struct ggml_metal_library {
|
||||
NSLock * lock;
|
||||
};
|
||||
|
||||
ggml_metal_library_t ggml_metal_library_init(ggml_metal_device_t dev) {
|
||||
id<MTLLibrary> library = nil;
|
||||
id<MTLDevice> device = ggml_metal_device_get_obj(dev);
|
||||
// Build the fn_to_lib routing table by querying each compiled library's public
|
||||
// function names. Call once after all per-kind libraries have been compiled.
|
||||
static void ggml_metal_library_build_index(ggml_metal_library_t lib) {
|
||||
@autoreleasepool {
|
||||
NSMutableDictionary<NSString *, NSNumber *> * index = [[NSMutableDictionary alloc] init];
|
||||
for (int kind = 0; kind < GGML_METAL_LIB_COUNT; ++kind) {
|
||||
for (NSString * fname in [lib->objs[kind] functionNames]) {
|
||||
index[fname] = @(kind);
|
||||
}
|
||||
}
|
||||
lib->fn_to_lib = index;
|
||||
}
|
||||
}
|
||||
|
||||
// load library
|
||||
//
|
||||
// - first check if the library is embedded
|
||||
// - then check if the library is in the bundle
|
||||
// - if not found, load the source and compile it
|
||||
// - if that fails, return NULL
|
||||
//
|
||||
// TODO: move to a function
|
||||
{
|
||||
const int64_t t_start = ggml_time_us();
|
||||
// Parse a `#include "name"` line. Returns the quoted name in *include_name on
|
||||
// success. Whitespace-tolerant; ignores `#include <...>` (system headers).
|
||||
static bool ggml_metal_library_parse_quoted_include(NSString * line, NSString ** include_name) {
|
||||
NSScanner * scanner = [NSScanner scannerWithString:line];
|
||||
scanner.charactersToBeSkipped = [NSCharacterSet whitespaceCharacterSet];
|
||||
|
||||
NSError * error = nil;
|
||||
NSString * src = nil;
|
||||
if (![scanner scanString:@"#" intoString:NULL] ||
|
||||
![scanner scanString:@"include" intoString:NULL] ||
|
||||
![scanner scanString:@"\"" intoString:NULL]) {
|
||||
return false;
|
||||
}
|
||||
|
||||
#if GGML_METAL_EMBED_LIBRARY
|
||||
GGML_LOG_INFO("%s: using embedded metal library\n", __func__);
|
||||
NSString * name = nil;
|
||||
if (![scanner scanUpToString:@"\"" intoString:&name]) {
|
||||
return false;
|
||||
}
|
||||
|
||||
extern const char ggml_metallib_start[];
|
||||
extern const char ggml_metallib_end[];
|
||||
if (include_name) {
|
||||
*include_name = name;
|
||||
}
|
||||
return true;
|
||||
}
|
||||
|
||||
src = [[NSString alloc] initWithBytes:ggml_metallib_start length:(ggml_metallib_end-ggml_metallib_start) encoding:NSUTF8StringEncoding];
|
||||
#else
|
||||
// Recursively inline `#include "name"` directives. System includes (<...>),
|
||||
// `#if/#else/#endif`, and other preprocessor lines are passed through to the
|
||||
// Metal compiler unchanged. `#pragma once` is dropped since `seen` already
|
||||
// guards against double-inclusion.
|
||||
static bool ggml_metal_library_flatten_file(NSMutableString * dst, NSString * path,
|
||||
NSArray<NSString *> * search_paths,
|
||||
NSMutableSet<NSString *> * seen, NSError ** error) {
|
||||
NSString * key = [path stringByStandardizingPath];
|
||||
if ([seen containsObject:key]) {
|
||||
return true;
|
||||
}
|
||||
[seen addObject:key];
|
||||
|
||||
#ifdef SWIFT_PACKAGE
|
||||
NSBundle * bundle = SWIFTPM_MODULE_BUNDLE;
|
||||
#else
|
||||
NSBundle * bundle = [NSBundle bundleForClass:[GGMLMetalClass class]];
|
||||
#endif
|
||||
NSString * src = [NSString stringWithContentsOfFile:path encoding:NSUTF8StringEncoding error:error];
|
||||
if (!src) {
|
||||
return false;
|
||||
}
|
||||
|
||||
NSString * path_lib = [bundle pathForResource:@"default" ofType:@"metallib"];
|
||||
if (path_lib == nil) {
|
||||
// Try to find the resource in the directory where the current binary located.
|
||||
NSString * bin_cur = [[NSProcessInfo processInfo] arguments][0];
|
||||
NSString * bin_dir = [bin_cur stringByDeletingLastPathComponent];
|
||||
NSFileManager * fm = [NSFileManager defaultManager];
|
||||
for (NSString * line in [src componentsSeparatedByString:@"\n"]) {
|
||||
NSString * trimmed = [line stringByTrimmingCharactersInSet:[NSCharacterSet whitespaceCharacterSet]];
|
||||
if ([trimmed isEqualToString:@"#pragma once"]) {
|
||||
continue;
|
||||
}
|
||||
|
||||
NSString * path_lib_default = [NSString pathWithComponents:@[bin_dir, @"default.metallib"]];
|
||||
if ([[NSFileManager defaultManager] isReadableFileAtPath:path_lib_default]) {
|
||||
GGML_LOG_INFO("%s: found '%s'\n", __func__, [path_lib_default UTF8String]);
|
||||
|
||||
NSDictionary * atts = [[NSFileManager defaultManager] attributesOfItemAtPath:path_lib_default error:&error];
|
||||
if (atts && atts[NSFileType] == NSFileTypeSymbolicLink) {
|
||||
// Optionally, if this is a symlink, try to resolve it.
|
||||
path_lib_default = [[NSFileManager defaultManager] destinationOfSymbolicLinkAtPath:path_lib_default error:&error];
|
||||
if (path_lib_default && [path_lib_default length] > 0 && ![[path_lib_default substringToIndex:1] isEqualToString:@"/"]) {
|
||||
// It is a relative path, adding the binary directory as directory prefix.
|
||||
path_lib_default = [NSString pathWithComponents:@[bin_dir, path_lib_default]];
|
||||
}
|
||||
if (!path_lib_default || ![[NSFileManager defaultManager] isReadableFileAtPath:path_lib_default]) {
|
||||
// Link to the resource could not be resolved.
|
||||
path_lib_default = nil;
|
||||
} else {
|
||||
GGML_LOG_INFO("%s: symlink resolved '%s'\n", __func__, [path_lib_default UTF8String]);
|
||||
}
|
||||
NSString * include_name = nil;
|
||||
if (ggml_metal_library_parse_quoted_include(line, &include_name)) {
|
||||
NSString * resolved = nil;
|
||||
for (NSString * dir in search_paths) {
|
||||
NSString * candidate = [dir stringByAppendingPathComponent:include_name];
|
||||
if ([fm isReadableFileAtPath:candidate]) {
|
||||
resolved = candidate;
|
||||
break;
|
||||
}
|
||||
} else {
|
||||
// The resource couldn't be found in the binary's directory.
|
||||
path_lib_default = nil;
|
||||
}
|
||||
|
||||
path_lib = path_lib_default;
|
||||
if (!resolved) {
|
||||
if (error) {
|
||||
NSString * msg = [NSString stringWithFormat:@"could not resolve include \"%@\" from '%@'", include_name, path];
|
||||
*error = [NSError errorWithDomain:@"ggml-metal-source-flatten" code:1
|
||||
userInfo:@{NSLocalizedDescriptionKey: msg}];
|
||||
}
|
||||
return false;
|
||||
}
|
||||
if (!ggml_metal_library_flatten_file(dst, resolved, search_paths, seen, error)) {
|
||||
return false;
|
||||
}
|
||||
continue;
|
||||
}
|
||||
|
||||
if (path_lib != nil) {
|
||||
// pre-compiled library found
|
||||
NSURL * libURL = [NSURL fileURLWithPath:path_lib];
|
||||
GGML_LOG_INFO("%s: loading '%s'\n", __func__, [path_lib UTF8String]);
|
||||
[dst appendString:line];
|
||||
[dst appendString:@"\n"];
|
||||
}
|
||||
|
||||
library = [device newLibraryWithURL:libURL error:&error];
|
||||
if (error) {
|
||||
GGML_LOG_ERROR("%s: error: %s\n", __func__, [[error description] UTF8String]);
|
||||
return nil;
|
||||
}
|
||||
} else {
|
||||
GGML_LOG_INFO("%s: default.metallib not found, loading from source\n", __func__);
|
||||
return true;
|
||||
}
|
||||
|
||||
NSString * path_source;
|
||||
NSString * path_resource = [[NSProcessInfo processInfo].environment objectForKey:@"GGML_METAL_PATH_RESOURCES"];
|
||||
static NSString * ggml_metal_library_flatten_source(NSString * path_source, NSError ** error) {
|
||||
// Search paths cover both runtime layout (build/bin/kernels + build/bin)
|
||||
// and source-tree layout (ggml/src/ggml-metal/kernels + ggml/src/ggml-metal + ggml/src).
|
||||
NSString * path_kernels = [path_source stringByDeletingLastPathComponent];
|
||||
NSString * path_base = [path_kernels stringByDeletingLastPathComponent];
|
||||
NSArray<NSString *> * search_paths = @[
|
||||
path_kernels,
|
||||
path_base,
|
||||
[path_base stringByDeletingLastPathComponent],
|
||||
];
|
||||
|
||||
GGML_LOG_INFO("%s: GGML_METAL_PATH_RESOURCES = %s\n", __func__, path_resource ? [path_resource UTF8String] : "nil");
|
||||
NSMutableString * src = [[NSMutableString alloc] init];
|
||||
NSMutableSet<NSString *> * seen = [NSMutableSet set];
|
||||
|
||||
if (path_resource) {
|
||||
path_source = [path_resource stringByAppendingPathComponent:@"ggml-metal.metal"];
|
||||
} else {
|
||||
path_source = [bundle pathForResource:@"ggml-metal" ofType:@"metal"];
|
||||
if (!ggml_metal_library_flatten_file(src, path_source, search_paths, seen, error)) {
|
||||
[src release];
|
||||
return nil;
|
||||
}
|
||||
return src;
|
||||
}
|
||||
|
||||
// Compile all per-kind libraries in parallel. `source_for_kind` returns the MSL
|
||||
// source for a kind (the helper takes ownership and releases it), or nil with
|
||||
// *err set on failure. On success the objs[] slots are populated and the routing
|
||||
// index is built; on any failure every error is logged and false is returned
|
||||
// (the caller is responsible for freeing `res`).
|
||||
static bool ggml_metal_library_compile_all(
|
||||
ggml_metal_library_t res,
|
||||
id<MTLDevice> device,
|
||||
NSDictionary * prep,
|
||||
NSString * (^source_for_kind)(int kind, NSError ** err),
|
||||
const char * origin) {
|
||||
const int64_t t_start = ggml_time_us();
|
||||
|
||||
int64_t * t_per_lib = calloc(GGML_METAL_LIB_COUNT, sizeof(int64_t));
|
||||
NSError ** err_per_lib = calloc(GGML_METAL_LIB_COUNT, sizeof(NSError *));
|
||||
__block atomic_bool any_failure = false;
|
||||
|
||||
dispatch_group_t group = dispatch_group_create();
|
||||
dispatch_queue_t queue = dispatch_get_global_queue(QOS_CLASS_USER_INITIATED, 0);
|
||||
|
||||
for (int kind = 0; kind < GGML_METAL_LIB_COUNT; ++kind) {
|
||||
dispatch_group_async(group, queue, ^{
|
||||
|
||||
const int64_t t0 = ggml_time_us();
|
||||
|
||||
NSError * error = nil;
|
||||
|
||||
NSString * src = source_for_kind(kind, &error);
|
||||
if (!src) {
|
||||
err_per_lib[kind] = [error retain];
|
||||
atomic_store(&any_failure, true);
|
||||
return;
|
||||
}
|
||||
|
||||
if (path_source == nil) {
|
||||
GGML_LOG_WARN("%s: error: could not use bundle path to find ggml-metal.metal, falling back to trying cwd\n", __func__);
|
||||
path_source = @"ggml-metal.metal";
|
||||
}
|
||||
id<MTLLibrary> lib = nil;
|
||||
|
||||
GGML_LOG_INFO("%s: loading '%s'\n", __func__, [path_source UTF8String]);
|
||||
|
||||
src = [NSString stringWithContentsOfFile:path_source encoding:NSUTF8StringEncoding error:&error];
|
||||
if (error) {
|
||||
GGML_LOG_ERROR("%s: error: %s\n", __func__, [[error description] UTF8String]);
|
||||
return nil;
|
||||
}
|
||||
}
|
||||
#endif
|
||||
|
||||
if (!library) {
|
||||
@autoreleasepool {
|
||||
// dictionary of preprocessor macros
|
||||
NSMutableDictionary * prep = [NSMutableDictionary dictionary];
|
||||
|
||||
if (ggml_metal_device_get_props(dev)->has_bfloat) {
|
||||
[prep setObject:@"1" forKey:@"GGML_METAL_HAS_BF16"];
|
||||
}
|
||||
|
||||
if (ggml_metal_device_get_props(dev)->has_tensor) {
|
||||
[prep setObject:@"1" forKey:@"GGML_METAL_HAS_TENSOR"];
|
||||
}
|
||||
|
||||
#if GGML_METAL_EMBED_LIBRARY
|
||||
[prep setObject:@"1" forKey:@"GGML_METAL_EMBED_LIBRARY"];
|
||||
#endif
|
||||
|
||||
MTLCompileOptions * options = [MTLCompileOptions new];
|
||||
options.preprocessorMacros = prep;
|
||||
|
||||
//[options setFastMathEnabled:false];
|
||||
lib = [device newLibraryWithSource:src options:options error:&error];
|
||||
|
||||
library = [device newLibraryWithSource:src options:options error:&error];
|
||||
if (error) {
|
||||
GGML_LOG_ERROR("%s: error: %s\n", __func__, [[error description] UTF8String]);
|
||||
return nil;
|
||||
}
|
||||
|
||||
#if !__has_feature(objc_arc)
|
||||
[options release];
|
||||
#endif
|
||||
|
||||
// retain the error before the autorelease pool drains it
|
||||
if (!lib) {
|
||||
err_per_lib[kind] = [error retain];
|
||||
}
|
||||
}
|
||||
|
||||
[src release];
|
||||
|
||||
t_per_lib[kind] = ggml_time_us() - t0;
|
||||
|
||||
if (!lib) {
|
||||
atomic_store(&any_failure, true);
|
||||
return;
|
||||
}
|
||||
|
||||
res->objs[kind] = lib;
|
||||
});
|
||||
}
|
||||
dispatch_group_wait(group, DISPATCH_TIME_FOREVER);
|
||||
dispatch_release(group);
|
||||
|
||||
const bool ok = !atomic_load(&any_failure);
|
||||
|
||||
if (ok) {
|
||||
const int64_t t_total = ggml_time_us() - t_start;
|
||||
int64_t t_max = 0;
|
||||
for (int kind = 0; kind < GGML_METAL_LIB_COUNT; ++kind) {
|
||||
GGML_LOG_DEBUG("%s: compiled '%s' library in %.3f sec\n",
|
||||
__func__, k_lib_names[kind], t_per_lib[kind] / 1e6);
|
||||
if (t_per_lib[kind] > t_max) t_max = t_per_lib[kind];
|
||||
}
|
||||
GGML_LOG_INFO("%s: loaded %d libraries from %s in %.3f sec (max single = %.3f sec)\n",
|
||||
__func__, GGML_METAL_LIB_COUNT, origin, t_total / 1e6, t_max / 1e6);
|
||||
|
||||
ggml_metal_library_build_index(res);
|
||||
} else {
|
||||
for (int kind = 0; kind < GGML_METAL_LIB_COUNT; ++kind) {
|
||||
if (err_per_lib[kind]) {
|
||||
GGML_LOG_ERROR("%s: failed to build '%s' library: %s\n", __func__,
|
||||
k_lib_names[kind], [[err_per_lib[kind] description] UTF8String]);
|
||||
[err_per_lib[kind] release];
|
||||
}
|
||||
}
|
||||
|
||||
#if GGML_METAL_EMBED_LIBRARY
|
||||
[src release];
|
||||
#endif // GGML_METAL_EMBED_LIBRARY
|
||||
|
||||
GGML_LOG_INFO("%s: loaded in %.3f sec\n", __func__, (ggml_time_us() - t_start) / 1e6);
|
||||
}
|
||||
|
||||
ggml_metal_library_t res = calloc(1, sizeof(struct ggml_metal_library));
|
||||
free(err_per_lib);
|
||||
free(t_per_lib);
|
||||
|
||||
res->obj = library;
|
||||
return ok;
|
||||
}
|
||||
|
||||
ggml_metal_library_t ggml_metal_library_init(ggml_metal_device_t dev) {
|
||||
id<MTLDevice> device = ggml_metal_device_get_obj(dev);
|
||||
|
||||
ggml_metal_library_t res = calloc(1, sizeof(struct ggml_metal_library));
|
||||
res->dev = dev;
|
||||
res->pipelines = ggml_metal_pipelines_init();
|
||||
res->lock = [NSLock new];
|
||||
|
||||
// shared MTLCompileOptions preprocessor macros (matches the build-time defines)
|
||||
NSMutableDictionary * prep = [NSMutableDictionary dictionary];
|
||||
if (ggml_metal_device_get_props(dev)->has_bfloat) {
|
||||
[prep setObject:@"1" forKey:@"GGML_METAL_HAS_BF16"];
|
||||
}
|
||||
if (ggml_metal_device_get_props(dev)->has_tensor) {
|
||||
[prep setObject:@"1" forKey:@"GGML_METAL_HAS_TENSOR"];
|
||||
}
|
||||
#if GGML_METAL_EMBED_LIBRARY
|
||||
[prep setObject:@"1" forKey:@"GGML_METAL_EMBED_LIBRARY"];
|
||||
#endif
|
||||
|
||||
#if GGML_METAL_EMBED_LIBRARY
|
||||
GGML_LOG_INFO("%s: using embedded metal library\n", __func__);
|
||||
|
||||
// start/end symbols emitted by CMake (see CMakeLists.txt), one pair per kind
|
||||
#define X(e, s) extern const char ggml_metallib_##s##_start[]; extern const char ggml_metallib_##s##_end[];
|
||||
GGML_METAL_LIBS
|
||||
#undef X
|
||||
|
||||
static const char * const lib_start[GGML_METAL_LIB_COUNT] = {
|
||||
#define X(e, s) [GGML_METAL_LIB_##e] = ggml_metallib_##s##_start,
|
||||
GGML_METAL_LIBS
|
||||
#undef X
|
||||
};
|
||||
static const char * const lib_end[GGML_METAL_LIB_COUNT] = {
|
||||
#define X(e, s) [GGML_METAL_LIB_##e] = ggml_metallib_##s##_end,
|
||||
GGML_METAL_LIBS
|
||||
#undef X
|
||||
};
|
||||
|
||||
const bool ok = ggml_metal_library_compile_all(res, device, prep,
|
||||
^NSString * (int kind, NSError ** err) {
|
||||
(void) err;
|
||||
return [[NSString alloc] initWithBytes:lib_start[kind]
|
||||
length:(lib_end[kind] - lib_start[kind])
|
||||
encoding:NSUTF8StringEncoding];
|
||||
}, "embedded data");
|
||||
|
||||
if (!ok) {
|
||||
ggml_metal_library_free(res);
|
||||
return NULL;
|
||||
}
|
||||
|
||||
return res;
|
||||
#else
|
||||
#ifdef SWIFT_PACKAGE
|
||||
NSBundle * bundle = SWIFTPM_MODULE_BUNDLE;
|
||||
#else
|
||||
NSBundle * bundle = [NSBundle bundleForClass:[GGMLMetalClass class]];
|
||||
#endif
|
||||
|
||||
const int64_t t_start = ggml_time_us();
|
||||
|
||||
NSError * error = nil;
|
||||
NSString * path_lib = [bundle pathForResource:@"default" ofType:@"metallib"];
|
||||
if (path_lib == nil) {
|
||||
// Try to find the resource in the directory where the current binary located.
|
||||
NSString * bin_cur = [[NSProcessInfo processInfo] arguments][0];
|
||||
NSString * bin_dir = [bin_cur stringByDeletingLastPathComponent];
|
||||
|
||||
NSString * path_lib_default = [NSString pathWithComponents:@[bin_dir, @"default.metallib"]];
|
||||
if ([[NSFileManager defaultManager] isReadableFileAtPath:path_lib_default]) {
|
||||
GGML_LOG_INFO("%s: found '%s'\n", __func__, [path_lib_default UTF8String]);
|
||||
|
||||
NSDictionary * atts = [[NSFileManager defaultManager] attributesOfItemAtPath:path_lib_default error:&error];
|
||||
if (atts && atts[NSFileType] == NSFileTypeSymbolicLink) {
|
||||
// Optionally, if this is a symlink, try to resolve it.
|
||||
path_lib_default = [[NSFileManager defaultManager] destinationOfSymbolicLinkAtPath:path_lib_default error:&error];
|
||||
if (path_lib_default && [path_lib_default length] > 0 && ![[path_lib_default substringToIndex:1] isEqualToString:@"/"]) {
|
||||
// It is a relative path, adding the binary directory as directory prefix.
|
||||
path_lib_default = [NSString pathWithComponents:@[bin_dir, path_lib_default]];
|
||||
}
|
||||
if (!path_lib_default || ![[NSFileManager defaultManager] isReadableFileAtPath:path_lib_default]) {
|
||||
// Link to the resource could not be resolved.
|
||||
path_lib_default = nil;
|
||||
} else {
|
||||
GGML_LOG_INFO("%s: symlink resolved '%s'\n", __func__, [path_lib_default UTF8String]);
|
||||
}
|
||||
}
|
||||
} else {
|
||||
// The resource couldn't be found in the binary's directory.
|
||||
path_lib_default = nil;
|
||||
}
|
||||
|
||||
path_lib = path_lib_default;
|
||||
}
|
||||
|
||||
if (path_lib != nil) {
|
||||
// pre-compiled library found: a single combined default.metallib
|
||||
NSURL * libURL = [NSURL fileURLWithPath:path_lib];
|
||||
GGML_LOG_INFO("%s: loading '%s'\n", __func__, [path_lib UTF8String]);
|
||||
|
||||
res->objs[0] = [device newLibraryWithURL:libURL error:&error];
|
||||
res->single_library = true;
|
||||
if (!res->objs[0]) {
|
||||
GGML_LOG_ERROR("%s: error: %s\n", __func__, [[error description] UTF8String]);
|
||||
ggml_metal_library_free(res);
|
||||
return NULL;
|
||||
}
|
||||
|
||||
GGML_LOG_INFO("%s: loaded in %.3f sec\n", __func__, (ggml_time_us() - t_start) / 1e6);
|
||||
return res;
|
||||
}
|
||||
|
||||
// no pre-compiled metallib: fall back to compiling each kernel source separately
|
||||
GGML_LOG_INFO("%s: default.metallib not found, loading kernel sources\n", __func__);
|
||||
|
||||
NSString * path_resource = [[NSProcessInfo processInfo].environment objectForKey:@"GGML_METAL_PATH_RESOURCES"];
|
||||
if (path_resource) {
|
||||
GGML_LOG_INFO("%s: GGML_METAL_PATH_RESOURCES = %s\n", __func__, [path_resource UTF8String]);
|
||||
}
|
||||
|
||||
// resolve each kind's source path up front (file lookup/logging stays on the calling thread)
|
||||
NSString ** path_per_kind = calloc(GGML_METAL_LIB_COUNT, sizeof(NSString *));
|
||||
for (int kind = 0; kind < GGML_METAL_LIB_COUNT; ++kind) {
|
||||
NSString * rel = [NSString stringWithFormat:@"kernels/%s.metal", k_lib_names[kind]];
|
||||
|
||||
NSString * path_source = nil;
|
||||
if (path_resource) {
|
||||
path_source = [path_resource stringByAppendingPathComponent:rel];
|
||||
} else {
|
||||
NSString * stem = [NSString stringWithFormat:@"kernels/%s", k_lib_names[kind]];
|
||||
path_source = [bundle pathForResource:stem ofType:@"metal"];
|
||||
}
|
||||
|
||||
if (path_source == nil || ![[NSFileManager defaultManager] isReadableFileAtPath:path_source]) {
|
||||
GGML_LOG_WARN("%s: could not locate %s in bundle, falling back to cwd\n", __func__, [rel UTF8String]);
|
||||
path_source = rel;
|
||||
}
|
||||
|
||||
GGML_LOG_DEBUG("%s: loading '%s'\n", __func__, [path_source UTF8String]);
|
||||
|
||||
path_per_kind[kind] = [path_source retain];
|
||||
}
|
||||
|
||||
const bool ok = ggml_metal_library_compile_all(res, device, prep,
|
||||
^NSString * (int kind, NSError ** err) {
|
||||
return ggml_metal_library_flatten_source(path_per_kind[kind], err);
|
||||
}, "source");
|
||||
|
||||
for (int kind = 0; kind < GGML_METAL_LIB_COUNT; ++kind) {
|
||||
[path_per_kind[kind] release];
|
||||
}
|
||||
free(path_per_kind);
|
||||
|
||||
if (!ok) {
|
||||
ggml_metal_library_free(res);
|
||||
return NULL;
|
||||
}
|
||||
|
||||
return res;
|
||||
#endif
|
||||
}
|
||||
|
||||
ggml_metal_library_t ggml_metal_library_init_from_source(ggml_metal_device_t dev, const char * source, bool verbose) {
|
||||
@@ -318,10 +589,11 @@ ggml_metal_library_t ggml_metal_library_init_from_source(ggml_metal_device_t dev
|
||||
return NULL;
|
||||
}
|
||||
|
||||
res->obj = library;
|
||||
res->dev = dev;
|
||||
res->pipelines = ggml_metal_pipelines_init();
|
||||
res->lock = [NSLock new];
|
||||
res->objs[0] = library;
|
||||
res->single_library = true;
|
||||
res->dev = dev;
|
||||
res->pipelines = ggml_metal_pipelines_init();
|
||||
res->lock = [NSLock new];
|
||||
|
||||
return res;
|
||||
}
|
||||
@@ -331,8 +603,14 @@ void ggml_metal_library_free(ggml_metal_library_t lib) {
|
||||
return;
|
||||
}
|
||||
|
||||
if (lib->obj) {
|
||||
[lib->obj release];
|
||||
for (int kind = 0; kind < GGML_METAL_LIB_COUNT; ++kind) {
|
||||
if (lib->objs[kind]) {
|
||||
[lib->objs[kind] release];
|
||||
}
|
||||
}
|
||||
|
||||
if (lib->fn_to_lib) {
|
||||
[lib->fn_to_lib release];
|
||||
}
|
||||
|
||||
ggml_metal_pipelines_free(lib->pipelines);
|
||||
@@ -393,11 +671,28 @@ struct ggml_metal_pipeline_with_params ggml_metal_library_compile_pipeline(ggml_
|
||||
|
||||
GGML_LOG_DEBUG("%s: compiling pipeline: base = '%s', name = '%s'\n", __func__, base, name);
|
||||
|
||||
// route to the library that actually defines this kernel; fn_to_lib is
|
||||
// built from -[MTLLibrary functionNames] so it's always in sync
|
||||
int lib_idx = 0;
|
||||
if (!lib->single_library) {
|
||||
NSNumber * idx = lib->fn_to_lib[base_func];
|
||||
if (!idx) {
|
||||
[lib->lock unlock];
|
||||
|
||||
GGML_LOG_ERROR("%s: kernel not found in any metal library: base = '%s', name = '%s'\n", __func__, base, name);
|
||||
|
||||
return res;
|
||||
}
|
||||
lib_idx = [idx intValue];
|
||||
}
|
||||
|
||||
id<MTLLibrary> mtl_lib = lib->objs[lib_idx];
|
||||
|
||||
id<MTLFunction> mtl_function;
|
||||
if (!cv) {
|
||||
mtl_function = [lib->obj newFunctionWithName:base_func];
|
||||
mtl_function = [mtl_lib newFunctionWithName:base_func];
|
||||
} else {
|
||||
mtl_function = [lib->obj newFunctionWithName:base_func constantValues:cv->obj error:&error];
|
||||
mtl_function = [mtl_lib newFunctionWithName:base_func constantValues:cv->obj error:&error];
|
||||
}
|
||||
if (!mtl_function) {
|
||||
[lib->lock unlock];
|
||||
@@ -1334,7 +1629,7 @@ bool ggml_metal_device_supports_op(ggml_metal_device_t dev, const struct ggml_te
|
||||
return op->src[0]->type != GGML_TYPE_NVFP4;
|
||||
case GGML_OP_SET_ROWS:
|
||||
{
|
||||
if (op->src[0]->type != GGML_TYPE_F32) {
|
||||
if (op->src[0]->type != GGML_TYPE_F32 && op->src[0]->type != GGML_TYPE_F16) {
|
||||
return false;
|
||||
}
|
||||
|
||||
|
||||
@@ -1202,7 +1202,7 @@ int ggml_metal_op_set_rows(ggml_metal_op_t ctx, int idx) {
|
||||
GGML_TENSOR_LOCALS( int32_t, ne, op, ne);
|
||||
GGML_TENSOR_LOCALS(uint64_t, nb, op, nb);
|
||||
|
||||
auto pipeline = ggml_metal_library_get_pipeline_set_rows(lib, op->src[1]->type, op->type);
|
||||
auto pipeline = ggml_metal_library_get_pipeline_set_rows(lib, op);
|
||||
|
||||
const int32_t nk0 = ne0/ggml_blck_size(op->type);
|
||||
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
@@ -0,0 +1,232 @@
|
||||
#include "common.h"
|
||||
|
||||
// bitonic sort implementation following the CUDA kernels as reference
|
||||
typedef void (argsort_t)(
|
||||
constant ggml_metal_kargs_argsort & args,
|
||||
device const char * src0,
|
||||
device int32_t * dst,
|
||||
threadgroup int32_t * shmem_i32 [[threadgroup(0)]],
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
ushort3 tpitg[[thread_position_in_threadgroup]],
|
||||
ushort3 ntg[[threads_per_threadgroup]]);
|
||||
|
||||
template<ggml_sort_order order>
|
||||
kernel void kernel_argsort_f32_i32(
|
||||
constant ggml_metal_kargs_argsort & args,
|
||||
device const char * src0,
|
||||
device int32_t * dst,
|
||||
threadgroup int32_t * shmem_i32 [[threadgroup(0)]],
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
ushort3 tpitg[[thread_position_in_threadgroup]],
|
||||
ushort3 ntg[[threads_per_threadgroup]]) {
|
||||
// bitonic sort
|
||||
const int col = tpitg[0];
|
||||
const int ib = tgpig[0] / args.ne01;
|
||||
|
||||
const int i00 = ib*ntg.x;
|
||||
const int i01 = tgpig[0] % args.ne01;
|
||||
const int i02 = tgpig[1];
|
||||
const int i03 = tgpig[2];
|
||||
|
||||
device const float * src0_row = (device const float *) (src0 + args.nb01*i01 + args.nb02*i02 + args.nb03*i03);
|
||||
|
||||
// initialize indices
|
||||
shmem_i32[col] = i00 + col;
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
for (int k = 2; k <= ntg.x; k *= 2) {
|
||||
for (int j = k / 2; j > 0; j /= 2) {
|
||||
int ixj = col ^ j;
|
||||
if (ixj > col) {
|
||||
if ((col & k) == 0) {
|
||||
if (shmem_i32[col] >= args.ne00 ||
|
||||
(shmem_i32[ixj] < args.ne00 && (order == GGML_SORT_ORDER_ASC ?
|
||||
src0_row[shmem_i32[col]] > src0_row[shmem_i32[ixj]] :
|
||||
src0_row[shmem_i32[col]] < src0_row[shmem_i32[ixj]]))
|
||||
) {
|
||||
SWAP(shmem_i32[col], shmem_i32[ixj]);
|
||||
}
|
||||
} else {
|
||||
if (shmem_i32[ixj] >= args.ne00 ||
|
||||
(shmem_i32[col] < args.ne00 && (order == GGML_SORT_ORDER_ASC ?
|
||||
src0_row[shmem_i32[col]] < src0_row[shmem_i32[ixj]] :
|
||||
src0_row[shmem_i32[col]] > src0_row[shmem_i32[ixj]]))
|
||||
) {
|
||||
SWAP(shmem_i32[col], shmem_i32[ixj]);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
}
|
||||
}
|
||||
|
||||
const int64_t i0 = ib*args.top_k;
|
||||
|
||||
// copy the result to dst without the padding
|
||||
if (i0 + col < args.ne0 && col < args.top_k) {
|
||||
dst += i0 + args.ne0*i01 + args.ne0*args.ne1*i02 + args.ne0*args.ne1*args.ne2*i03;
|
||||
|
||||
dst[col] = shmem_i32[col];
|
||||
}
|
||||
}
|
||||
|
||||
template [[host_name("kernel_argsort_f32_i32_asc")]] kernel argsort_t kernel_argsort_f32_i32<GGML_SORT_ORDER_ASC>;
|
||||
template [[host_name("kernel_argsort_f32_i32_desc")]] kernel argsort_t kernel_argsort_f32_i32<GGML_SORT_ORDER_DESC>;
|
||||
|
||||
typedef void (argsort_merge_t)(
|
||||
constant ggml_metal_kargs_argsort_merge & args,
|
||||
device const char * src0,
|
||||
device const int32_t * tmp,
|
||||
device int32_t * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
ushort3 tpitg[[thread_position_in_threadgroup]],
|
||||
ushort3 ntg[[threads_per_threadgroup]]);
|
||||
|
||||
template<ggml_sort_order order>
|
||||
kernel void kernel_argsort_merge_f32_i32(
|
||||
constant ggml_metal_kargs_argsort_merge & args,
|
||||
device const char * src0,
|
||||
device const int32_t * tmp,
|
||||
device int32_t * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
ushort3 tpitg[[thread_position_in_threadgroup]],
|
||||
ushort3 ntg[[threads_per_threadgroup]]) {
|
||||
|
||||
const int im = tgpig[0] / args.ne01;
|
||||
const int i01 = tgpig[0] % args.ne01;
|
||||
const int i02 = tgpig[1];
|
||||
const int i03 = tgpig[2];
|
||||
|
||||
const int start = im * (2 * args.len);
|
||||
|
||||
const int len0 = MIN(args.len, MAX(0, args.ne0 - (int)(start)));
|
||||
const int len1 = MIN(args.len, MAX(0, args.ne0 - (int)(start + args.len)));
|
||||
|
||||
const int total = len0 + len1;
|
||||
|
||||
device const int32_t * tmp0 = tmp + start
|
||||
+ i01*args.ne0
|
||||
+ i02*args.ne0*args.ne01
|
||||
+ i03*args.ne0*args.ne01*args.ne02;
|
||||
|
||||
device const int32_t * tmp1 = tmp0 + args.len;
|
||||
|
||||
dst += start
|
||||
+ i01*args.top_k
|
||||
+ i02*args.top_k*args.ne01
|
||||
+ i03*args.top_k*args.ne01*args.ne02;
|
||||
|
||||
device const float * src0_row = (device const float *)(src0
|
||||
+ args.nb01*i01
|
||||
+ args.nb02*i02
|
||||
+ args.nb03*i03);
|
||||
|
||||
if (total == 0) {
|
||||
return;
|
||||
}
|
||||
|
||||
const int chunk = (total + ntg.x - 1) / ntg.x;
|
||||
|
||||
const int k0 = tpitg.x * chunk;
|
||||
const int k1 = MIN(MIN(k0 + chunk, total), args.top_k);
|
||||
|
||||
if (k0 >= args.top_k) {
|
||||
return;
|
||||
}
|
||||
|
||||
if (k0 >= total) {
|
||||
return;
|
||||
}
|
||||
|
||||
int low = k0 > len1 ? k0 - len1 : 0;
|
||||
int high = MIN(k0, len0);
|
||||
|
||||
// binary-search partition (i, j) such that i + j = k
|
||||
while (low < high) {
|
||||
const int mid = (low + high) >> 1;
|
||||
|
||||
const int32_t idx0 = tmp0[mid];
|
||||
const int32_t idx1 = tmp1[k0 - mid - 1];
|
||||
|
||||
const float val0 = src0_row[idx0];
|
||||
const float val1 = src0_row[idx1];
|
||||
|
||||
bool take_left;
|
||||
if (order == GGML_SORT_ORDER_ASC) {
|
||||
take_left = (val0 <= val1);
|
||||
} else {
|
||||
take_left = (val0 >= val1);
|
||||
}
|
||||
|
||||
if (take_left) {
|
||||
low = mid + 1;
|
||||
} else {
|
||||
high = mid;
|
||||
}
|
||||
}
|
||||
|
||||
int i = low;
|
||||
int j = k0 - i;
|
||||
|
||||
// keep the merge fronts into registers
|
||||
int32_t idx0 = 0;
|
||||
float val0 = 0.0f;
|
||||
if (i < len0) {
|
||||
idx0 = tmp0[i];
|
||||
val0 = src0_row[idx0];
|
||||
}
|
||||
|
||||
int32_t idx1 = 0;
|
||||
float val1 = 0.0f;
|
||||
if (j < len1) {
|
||||
idx1 = tmp1[j];
|
||||
val1 = src0_row[idx1];
|
||||
}
|
||||
|
||||
for (int k = k0; k < k1; ++k) {
|
||||
int32_t out_idx;
|
||||
|
||||
if (i >= len0) {
|
||||
while (k < k1) {
|
||||
dst[k++] = tmp1[j++];
|
||||
}
|
||||
break;
|
||||
} else if (j >= len1) {
|
||||
while (k < k1) {
|
||||
dst[k++] = tmp0[i++];
|
||||
}
|
||||
break;
|
||||
} else {
|
||||
bool take_left;
|
||||
|
||||
if (order == GGML_SORT_ORDER_ASC) {
|
||||
take_left = (val0 <= val1);
|
||||
} else {
|
||||
take_left = (val0 >= val1);
|
||||
}
|
||||
|
||||
if (take_left) {
|
||||
out_idx = idx0;
|
||||
++i;
|
||||
if (i < len0) {
|
||||
idx0 = tmp0[i];
|
||||
val0 = src0_row[idx0];
|
||||
}
|
||||
} else {
|
||||
out_idx = idx1;
|
||||
++j;
|
||||
if (j < len1) {
|
||||
idx1 = tmp1[j];
|
||||
val1 = src0_row[idx1];
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
dst[k] = out_idx;
|
||||
}
|
||||
}
|
||||
|
||||
template [[host_name("kernel_argsort_merge_f32_i32_asc")]] kernel argsort_merge_t kernel_argsort_merge_f32_i32<GGML_SORT_ORDER_ASC>;
|
||||
template [[host_name("kernel_argsort_merge_f32_i32_desc")]] kernel argsort_merge_t kernel_argsort_merge_f32_i32<GGML_SORT_ORDER_DESC>;
|
||||
@@ -0,0 +1,226 @@
|
||||
#include "common.h"
|
||||
|
||||
// OP: 0 - add, 1 - sub, 2 - mul, 3 - div
|
||||
constant short FC_bin_op [[function_constant(FC_BIN + 0)]];
|
||||
constant short FC_bin_f [[function_constant(FC_BIN + 1)]];
|
||||
constant bool FC_bin_rb [[function_constant(FC_BIN + 2)]];
|
||||
constant bool FC_bin_cb [[function_constant(FC_BIN + 3)]];
|
||||
|
||||
template <typename T0, typename T1, typename T>
|
||||
kernel void kernel_bin_fuse_impl(
|
||||
constant ggml_metal_kargs_bin & args,
|
||||
device const char * src0,
|
||||
device const char * src1,
|
||||
device char * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
ushort3 tpitg[[thread_position_in_threadgroup]],
|
||||
ushort3 ntg[[threads_per_threadgroup]]) {
|
||||
#define FC_OP FC_bin_op
|
||||
#define FC_F FC_bin_f
|
||||
#define FC_RB FC_bin_rb
|
||||
#define FC_CB FC_bin_cb
|
||||
|
||||
if (FC_RB) {
|
||||
// row broadcast
|
||||
const uint i0 = tgpig.y*args.ne00 + tgpig.x;
|
||||
const uint i1 = FC_CB ? tgpig.x%args.ne10 : tgpig.x;
|
||||
|
||||
device const T0 * src0_row = (device const T0 *) (src0);
|
||||
device T * dst_row = (device T *) (dst);
|
||||
|
||||
if (FC_F == 1) {
|
||||
device const T1 * src1_row = (device const T1 *) (src1 + args.o1[0]);
|
||||
|
||||
if (FC_OP == 0) {
|
||||
dst_row[i0] = src0_row[i0] + src1_row[i1];
|
||||
}
|
||||
|
||||
if (FC_OP == 1) {
|
||||
dst_row[i0] = src0_row[i0] - src1_row[i1];
|
||||
}
|
||||
|
||||
if (FC_OP == 2) {
|
||||
dst_row[i0] = src0_row[i0] * src1_row[i1];
|
||||
}
|
||||
|
||||
if (FC_OP == 3) {
|
||||
dst_row[i0] = src0_row[i0] / src1_row[i1];
|
||||
}
|
||||
} else {
|
||||
T0 res = src0_row[i0];
|
||||
|
||||
if (FC_OP == 0) {
|
||||
FOR_UNROLL (short j = 0; j < FC_F; ++j) {
|
||||
res += ((device const T1 *) (src1 + args.o1[j]))[i1];
|
||||
}
|
||||
}
|
||||
|
||||
if (FC_OP == 1) {
|
||||
FOR_UNROLL (short j = 0; j < FC_F; ++j) {
|
||||
res -= ((device const T1 *) (src1 + args.o1[j]))[i1];
|
||||
}
|
||||
}
|
||||
|
||||
if (FC_OP == 2) {
|
||||
FOR_UNROLL (short j = 0; j < FC_F; ++j) {
|
||||
res *= ((device const T1 *) (src1 + args.o1[j]))[i1];
|
||||
}
|
||||
}
|
||||
|
||||
if (FC_OP == 3) {
|
||||
FOR_UNROLL (short j = 0; j < FC_F; ++j) {
|
||||
res /= ((device const T1 *) (src1 + args.o1[j]))[i1];
|
||||
}
|
||||
}
|
||||
|
||||
dst_row[i0] = res;
|
||||
}
|
||||
} else {
|
||||
const int i03 = tgpig.z;
|
||||
const int i02 = tgpig.y;
|
||||
const int i01 = tgpig.x;
|
||||
|
||||
if (i01 >= args.ne01) {
|
||||
return;
|
||||
}
|
||||
|
||||
const int i13 = i03%args.ne13;
|
||||
const int i12 = i02%args.ne12;
|
||||
const int i11 = i01%args.ne11;
|
||||
|
||||
device const T0 * src0_ptr = (device const T0 *) (src0 + i03*args.nb03 + i02*args.nb02 + i01*args.nb01 + args.offs);
|
||||
device T * dst_ptr = (device T *) (dst + i03*args.nb3 + i02*args.nb2 + i01*args.nb1 + args.offs);
|
||||
|
||||
if (FC_F == 1) {
|
||||
device const T1 * src1_ptr = (device const T1 *) (src1 + args.o1[0] + i13*args.nb13 + i12*args.nb12 + i11*args.nb11);
|
||||
|
||||
for (int i0 = tpitg.x; i0 < args.ne0; i0 += ntg.x) {
|
||||
const int i10 = FC_CB ? i0%args.ne10 : i0;
|
||||
|
||||
if (FC_OP == 0) {
|
||||
dst_ptr[i0] = src0_ptr[i0] + src1_ptr[i10];
|
||||
}
|
||||
|
||||
if (FC_OP == 1) {
|
||||
dst_ptr[i0] = src0_ptr[i0] - src1_ptr[i10];
|
||||
}
|
||||
|
||||
if (FC_OP == 2) {
|
||||
dst_ptr[i0] = src0_ptr[i0] * src1_ptr[i10];
|
||||
}
|
||||
|
||||
if (FC_OP == 3) {
|
||||
dst_ptr[i0] = src0_ptr[i0] / src1_ptr[i10];
|
||||
}
|
||||
}
|
||||
} else {
|
||||
device const T1 * src1_ptr[8];
|
||||
FOR_UNROLL (short j = 0; j < FC_F; ++j) {
|
||||
src1_ptr[j] = (device const T1 *) (src1 + args.o1[j] + i13*args.nb13 + i12*args.nb12 + i11*args.nb11);
|
||||
}
|
||||
|
||||
for (int i0 = tpitg.x; i0 < args.ne0; i0 += ntg.x) {
|
||||
const int i10 = FC_CB ? i0%args.ne10 : i0;
|
||||
|
||||
T res = src0_ptr[i0];
|
||||
|
||||
if (FC_OP == 0) {
|
||||
FOR_UNROLL (short j = 0; j < FC_F; ++j) {
|
||||
res += src1_ptr[j][i10];
|
||||
}
|
||||
}
|
||||
|
||||
if (FC_OP == 1) {
|
||||
FOR_UNROLL (short j = 0; j < FC_F; ++j) {
|
||||
res -= src1_ptr[j][i10];
|
||||
}
|
||||
}
|
||||
|
||||
if (FC_OP == 2) {
|
||||
FOR_UNROLL (short j = 0; j < FC_F; ++j) {
|
||||
res *= src1_ptr[j][i10];
|
||||
}
|
||||
}
|
||||
|
||||
if (FC_OP == 3) {
|
||||
FOR_UNROLL (short j = 0; j < FC_F; ++j) {
|
||||
res /= src1_ptr[j][i10];
|
||||
}
|
||||
}
|
||||
|
||||
dst_ptr[i0] = res;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
#undef FC_OP
|
||||
#undef FC_F
|
||||
#undef FC_RB
|
||||
#undef FC_CB
|
||||
}
|
||||
|
||||
typedef decltype(kernel_bin_fuse_impl<float, float, float>) kernel_bin_fuse_t;
|
||||
|
||||
template [[host_name("kernel_bin_fuse_f32_f32_f32")]] kernel kernel_bin_fuse_t kernel_bin_fuse_impl<float, float, float>;
|
||||
template [[host_name("kernel_bin_fuse_f32_f32_f32_4")]] kernel kernel_bin_fuse_t kernel_bin_fuse_impl<float4, float4, float4>;
|
||||
|
||||
kernel void kernel_add_id(
|
||||
constant ggml_metal_kargs_add_id & args,
|
||||
device const char * src0,
|
||||
device const char * src1,
|
||||
device const char * src2,
|
||||
device char * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
ushort3 tpitg[[thread_position_in_threadgroup]],
|
||||
ushort3 ntg[[threads_per_threadgroup]]) {
|
||||
const int i1 = tgpig.x;
|
||||
const int i2 = tgpig.y;
|
||||
|
||||
const int i11 = *((device const int32_t *) (src2 + i1*sizeof(int32_t) + i2*args.nb21));
|
||||
|
||||
const size_t nb1 = args.ne0 * sizeof(float);
|
||||
const size_t nb2 = args.ne1 * nb1;
|
||||
|
||||
device float * dst_row = (device float *)((device char *)dst + i1*nb1 + i2*nb2);
|
||||
device const float * src0_row = (device const float *)((device char *)src0 + i1*args.nb01 + i2*args.nb02);
|
||||
device const float * src1_row = (device const float *)((device char *)src1 + i11*args.nb11);
|
||||
|
||||
for (int i0 = tpitg.x; i0 < args.ne0; i0 += ntg.x) {
|
||||
dst_row[i0] = src0_row[i0] + src1_row[i0];
|
||||
}
|
||||
}
|
||||
|
||||
template<typename T>
|
||||
kernel void kernel_repeat(
|
||||
constant ggml_metal_kargs_repeat & args,
|
||||
device const char * src0,
|
||||
device char * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
ushort3 tpitg[[thread_position_in_threadgroup]],
|
||||
ushort3 ntg[[threads_per_threadgroup]]) {
|
||||
const int i3 = tgpig.z;
|
||||
const int i2 = tgpig.y;
|
||||
const int i1 = tgpig.x;
|
||||
|
||||
const int i03 = i3%args.ne03;
|
||||
const int i02 = i2%args.ne02;
|
||||
const int i01 = i1%args.ne01;
|
||||
|
||||
device const char * src0_ptr = src0 + i03*args.nb03 + i02*args.nb02 + i01*args.nb01;
|
||||
device char * dst_ptr = dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1;
|
||||
|
||||
for (int i0 = tpitg.x; i0 < args.ne0; i0 += ntg.x) {
|
||||
const int i00 = i0%args.ne00;
|
||||
*((device T *)(dst_ptr + i0*args.nb0)) = *((device T *)(src0_ptr + i00*args.nb00));
|
||||
}
|
||||
}
|
||||
|
||||
typedef decltype(kernel_repeat<float>) kernel_repeat_t;
|
||||
|
||||
template [[host_name("kernel_repeat_f32")]] kernel kernel_repeat_t kernel_repeat<float>;
|
||||
template [[host_name("kernel_repeat_f16")]] kernel kernel_repeat_t kernel_repeat<half>;
|
||||
#if defined(GGML_METAL_HAS_BF16)
|
||||
template [[host_name("kernel_repeat_bf16")]] kernel kernel_repeat_t kernel_repeat<bfloat>;
|
||||
#endif
|
||||
template [[host_name("kernel_repeat_i32")]] kernel kernel_repeat_t kernel_repeat<int>;
|
||||
template [[host_name("kernel_repeat_i16")]] kernel kernel_repeat_t kernel_repeat<short>;
|
||||
@@ -0,0 +1,126 @@
|
||||
#pragma once
|
||||
|
||||
#include "ggml-metal-impl.h"
|
||||
|
||||
#include <metal_stdlib>
|
||||
|
||||
#ifdef GGML_METAL_HAS_TENSOR
|
||||
#include <metal_tensor>
|
||||
|
||||
#include <MetalPerformancePrimitives/MetalPerformancePrimitives.h>
|
||||
#endif
|
||||
|
||||
using namespace metal;
|
||||
|
||||
#define MAX(x, y) ((x) > (y) ? (x) : (y))
|
||||
#define MIN(x, y) ((x) < (y) ? (x) : (y))
|
||||
#define SWAP(x, y) { auto tmp = (x); (x) = (y); (y) = tmp; }
|
||||
|
||||
#define PAD2(x, n) (((x) + (n) - 1) & ~((n) - 1))
|
||||
|
||||
#define FOR_UNROLL(x) _Pragma("clang loop unroll(full)") for (x)
|
||||
|
||||
#define N_SIMDWIDTH 32 // assuming SIMD group size is 32
|
||||
|
||||
// ref: https://developer.apple.com/metal/Metal-Shading-Language-Specification.pdf
|
||||
//
|
||||
// cmd:
|
||||
// .../usr/bin/metal -dM -E -c ggml/src/ggml-metal/kernels/<src>.metal
|
||||
// .../usr/bin/metal -dM -E -c -target air64-apple-ios14.0 ggml/src/ggml-metal/kernels/<src>.metal
|
||||
//
|
||||
#if __METAL_VERSION__ < 310 && defined(GGML_METAL_HAS_BF16)
|
||||
#undef GGML_METAL_HAS_BF16
|
||||
#endif
|
||||
|
||||
#if defined(GGML_METAL_HAS_BF16)
|
||||
typedef matrix<bfloat, 4, 4> bfloat4x4;
|
||||
typedef matrix<bfloat, 2, 4> bfloat2x4;
|
||||
#endif
|
||||
|
||||
constexpr constant static float kvalues_iq4nl_f[16] = {
|
||||
-127.f, -104.f, -83.f, -65.f, -49.f, -35.f, -22.f, -10.f, 1.f, 13.f, 25.f, 38.f, 53.f, 69.f, 89.f, 113.f
|
||||
};
|
||||
|
||||
constexpr constant static float kvalues_mxfp4_f[16] = {
|
||||
0, .5f, 1.f, 1.5f, 2.f, 3.f, 4.f, 6.f, -0, -.5f, -1.f, -1.5f, -2.f, -3.f, -4.f, -6.f
|
||||
};
|
||||
|
||||
static inline int best_index_int8(int n, constant float * val, float x) {
|
||||
if (x <= val[0]) return 0;
|
||||
if (x >= val[n-1]) return n-1;
|
||||
int ml = 0, mu = n-1;
|
||||
while (mu-ml > 1) {
|
||||
int mav = (ml+mu)/2;
|
||||
if (x < val[mav]) mu = mav; else ml = mav;
|
||||
}
|
||||
return x - val[mu-1] < val[mu] - x ? mu-1 : mu;
|
||||
}
|
||||
|
||||
static inline float e8m0_to_fp32(uint8_t x) {
|
||||
uint32_t bits;
|
||||
|
||||
if (x == 0) {
|
||||
bits = 0x00400000;
|
||||
} else {
|
||||
bits = (uint32_t) x << 23;
|
||||
}
|
||||
|
||||
return as_type<float>(bits);
|
||||
}
|
||||
|
||||
static inline float dot(float x, float y) {
|
||||
return x*y;
|
||||
}
|
||||
|
||||
static inline float sum(float x) {
|
||||
return x;
|
||||
}
|
||||
|
||||
static inline float sum(float4 x) {
|
||||
return x[0] + x[1] + x[2] + x[3];
|
||||
}
|
||||
|
||||
enum ggml_sort_order {
|
||||
GGML_SORT_ORDER_ASC,
|
||||
GGML_SORT_ORDER_DESC,
|
||||
};
|
||||
|
||||
constant float GELU_COEF_A = 0.044715f;
|
||||
constant float GELU_QUICK_COEF = -1.702f;
|
||||
constant float SQRT_2_OVER_PI = 0.79788456080286535587989211986876f;
|
||||
constant float SQRT_2_INV = 0.70710678118654752440084436210484f;
|
||||
|
||||
// based on Abramowitz and Stegun formula 7.1.26 or similar Hastings' approximation
|
||||
// ref: https://www.johndcook.com/blog/python_erf/
|
||||
constant float p_erf = 0.3275911f;
|
||||
constant float a1_erf = 0.254829592f;
|
||||
constant float a2_erf = -0.284496736f;
|
||||
constant float a3_erf = 1.421413741f;
|
||||
constant float a4_erf = -1.453152027f;
|
||||
constant float a5_erf = 1.061405429f;
|
||||
|
||||
template<typename T>
|
||||
inline T erf_approx(T x) {
|
||||
T sign_x = sign(x);
|
||||
x = fabs(x);
|
||||
T t = 1.0f / (1.0f + p_erf * x);
|
||||
T y = 1.0f - (((((a5_erf * t + a4_erf) * t) + a3_erf) * t + a2_erf) * t + a1_erf) * t * exp(-x * x);
|
||||
return sign_x * y;
|
||||
}
|
||||
|
||||
template<typename T> T elu_approx(T x);
|
||||
|
||||
template<> inline float elu_approx<float>(float x) {
|
||||
return (x > 0.f) ? x : (exp(x) - 1);
|
||||
}
|
||||
|
||||
template<> inline float4 elu_approx<float4>(float4 x) {
|
||||
float4 res;
|
||||
|
||||
res[0] = (x[0] > 0.0f) ? x[0] : (exp(x[0]) - 1.0f);
|
||||
res[1] = (x[1] > 0.0f) ? x[1] : (exp(x[1]) - 1.0f);
|
||||
res[2] = (x[2] > 0.0f) ? x[2] : (exp(x[2]) - 1.0f);
|
||||
res[3] = (x[3] > 0.0f) ? x[3] : (exp(x[3]) - 1.0f);
|
||||
|
||||
return res;
|
||||
}
|
||||
@@ -0,0 +1,527 @@
|
||||
#include "common.h"
|
||||
|
||||
typedef void (im2col_t)(
|
||||
constant ggml_metal_kargs_im2col & args,
|
||||
device const float * x,
|
||||
device char * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
uint3 tgpg[[threadgroups_per_grid]],
|
||||
uint3 tpitg[[thread_position_in_threadgroup]],
|
||||
uint3 ntg[[threads_per_threadgroup]]);
|
||||
|
||||
template <typename T>
|
||||
kernel void kernel_im2col(
|
||||
constant ggml_metal_kargs_im2col & args,
|
||||
device const float * x,
|
||||
device char * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
uint3 tgpg[[threadgroups_per_grid]],
|
||||
uint3 tpitg[[thread_position_in_threadgroup]],
|
||||
uint3 ntg[[threads_per_threadgroup]]) {
|
||||
// const int64_t IC = tgpg[0];
|
||||
const int64_t OH = tgpg[1];
|
||||
const int64_t OW = tgpg[2];
|
||||
|
||||
const int64_t KH = ntg[1];
|
||||
const int64_t KW = ntg[2];
|
||||
|
||||
int64_t in = tpitg[0];
|
||||
const int64_t ikh = tpitg[1];
|
||||
const int64_t ikw = tpitg[2];
|
||||
|
||||
const int64_t iic = tgpig[0];
|
||||
const int64_t ioh = tgpig[1];
|
||||
const int64_t iow = tgpig[2];
|
||||
|
||||
const int64_t iiw = iow*args.s0 + ikw*args.d0 - args.p0;
|
||||
const int64_t iih = ioh*args.s1 + ikh*args.d1 - args.p1;
|
||||
|
||||
int64_t offset_dst = (in*OH*OW + ioh*OW + iow)*args.CHW + (iic*(KH*KW) + ikh*KW + ikw);
|
||||
|
||||
device T * pdst = (device T *) (dst);
|
||||
|
||||
if (iih < 0 || iih >= args.IH || iiw < 0 || iiw >= args.IW) {
|
||||
while (in < args.N) {
|
||||
pdst[offset_dst] = 0.0f;
|
||||
offset_dst += ntg[0]*args.CHW*OH*OW;
|
||||
|
||||
in += ntg[0];
|
||||
}
|
||||
} else {
|
||||
int64_t offset_src = in*args.ofs0 + iic*args.ofs1 + iih*args.IW + iiw;
|
||||
|
||||
while (in < args.N) {
|
||||
pdst[offset_dst] = x[offset_src];
|
||||
|
||||
offset_dst += ntg[0]*args.CHW*OH*OW;
|
||||
offset_src += ntg[0]*args.ofs0;
|
||||
|
||||
in += ntg[0];
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
template [[host_name("kernel_im2col_f32")]] kernel im2col_t kernel_im2col<float>;
|
||||
template [[host_name("kernel_im2col_f16")]] kernel im2col_t kernel_im2col<half>;
|
||||
|
||||
// TODO: optimize
|
||||
typedef void (im2col_ext_t)(
|
||||
constant ggml_metal_kargs_im2col & args,
|
||||
device const float * x,
|
||||
device char * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
uint3 tgpg[[threadgroups_per_grid]],
|
||||
uint3 tpitg[[thread_position_in_threadgroup]],
|
||||
uint3 ntg[[threads_per_threadgroup]]);
|
||||
|
||||
template <typename T>
|
||||
kernel void kernel_im2col_ext(
|
||||
constant ggml_metal_kargs_im2col & args,
|
||||
device const float * x,
|
||||
device char * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
uint3 tgpg[[threadgroups_per_grid]], // tgpg[0] = D x IC x KH x KW, CHW = IC x KH x KW
|
||||
uint3 tpitg[[thread_position_in_threadgroup]],
|
||||
uint3 ntg[[threads_per_threadgroup]]) { // [M, 1, 1]
|
||||
const int64_t KHW = (int64_t)args.KHW;
|
||||
|
||||
const int64_t d = tgpig[0] / args.CHW;
|
||||
const int64_t chw = tgpig[0] % args.CHW;
|
||||
const int64_t tgpig_0 = chw / KHW; // 0 ~ (IC - 1)
|
||||
const int64_t HW = tgpig[0] % KHW;
|
||||
|
||||
const int64_t tpitg_0 = (d * ntg[0]) + tpitg[0];
|
||||
if (tpitg_0 >= args.N) {
|
||||
return;
|
||||
}
|
||||
|
||||
const int64_t tpitg_1 = HW / args.KW;
|
||||
const int64_t tpitg_2 = HW % args.KW;
|
||||
|
||||
const int64_t iiw = tgpig[2] * args.s0 + tpitg_2 * args.d0 - args.p0;
|
||||
const int64_t iih = tgpig[1] * args.s1 + tpitg_1 * args.d1 - args.p1;
|
||||
|
||||
const int64_t offset_dst =
|
||||
(tpitg_0 * tgpg[1] * tgpg[2] + tgpig[1] * tgpg[2] + tgpig[2]) * args.CHW +
|
||||
(tgpig_0 * KHW + tpitg_1 * args.KW + tpitg_2);
|
||||
|
||||
device T * pdst = (device T *) (dst);
|
||||
|
||||
if (iih < 0 || iih >= args.IH || iiw < 0 || iiw >= args.IW) {
|
||||
pdst[offset_dst] = 0.0f;
|
||||
} else {
|
||||
const int64_t offset_src = tpitg_0 * args.ofs0 + tgpig_0 * args.ofs1;
|
||||
pdst[offset_dst] = x[offset_src + iih * args.IW + iiw];
|
||||
}
|
||||
}
|
||||
|
||||
template [[host_name("kernel_im2col_ext_f32")]] kernel im2col_ext_t kernel_im2col_ext<float>;
|
||||
template [[host_name("kernel_im2col_ext_f16")]] kernel im2col_ext_t kernel_im2col_ext<half>;
|
||||
|
||||
template <typename T>
|
||||
kernel void kernel_col2im_1d(
|
||||
constant ggml_metal_kargs_col2im_1d & args,
|
||||
device const T * col,
|
||||
device T * dst,
|
||||
uint tgpig [[threadgroup_position_in_grid]],
|
||||
uint tpitg [[thread_position_in_threadgroup]],
|
||||
uint ntg [[threads_per_threadgroup]]) {
|
||||
|
||||
const int idx = tgpig * ntg + tpitg;
|
||||
if (idx >= args.T_out * args.OC) {
|
||||
return;
|
||||
}
|
||||
|
||||
const int t_out = idx % args.T_out;
|
||||
const int oc = idx / args.T_out;
|
||||
const int t_abs = t_out + args.p0; // absolute position in uncropped signal
|
||||
|
||||
int t_in_min = (t_abs - args.K + args.s0) / args.s0; // ceil((t_abs - K + 1) / s0)
|
||||
if (t_in_min < 0) {
|
||||
t_in_min = 0;
|
||||
}
|
||||
int t_in_max = t_abs / args.s0;
|
||||
if (t_in_max >= args.T_in) {
|
||||
t_in_max = args.T_in - 1;
|
||||
}
|
||||
|
||||
float sum = 0.0f;
|
||||
for (int t_in = t_in_min; t_in <= t_in_max; t_in++) {
|
||||
const int k = t_abs - t_in * args.s0;
|
||||
sum += float(col[(oc * args.K + k) + t_in * args.K_OC]);
|
||||
}
|
||||
|
||||
dst[t_out + oc * args.T_out] = T(sum);
|
||||
}
|
||||
|
||||
template [[host_name("kernel_col2im_1d_f32")]] kernel void kernel_col2im_1d<float>(constant ggml_metal_kargs_col2im_1d &, device const float *, device float *, uint, uint, uint);
|
||||
template [[host_name("kernel_col2im_1d_f16")]] kernel void kernel_col2im_1d<half>(constant ggml_metal_kargs_col2im_1d &, device const half *, device half *, uint, uint, uint);
|
||||
#if defined(GGML_METAL_HAS_BF16)
|
||||
template [[host_name("kernel_col2im_1d_bf16")]] kernel void kernel_col2im_1d<bfloat>(constant ggml_metal_kargs_col2im_1d &, device const bfloat *, device bfloat *, uint, uint, uint);
|
||||
#endif
|
||||
|
||||
template <typename TK>
|
||||
kernel void kernel_conv_2d(
|
||||
constant ggml_metal_kargs_conv_2d & args,
|
||||
device const char * weights,
|
||||
device const char * src,
|
||||
device char * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
uint3 tgpg[[threadgroups_per_grid]],
|
||||
uint3 tpitg[[thread_position_in_threadgroup]],
|
||||
uint3 ntg[[threads_per_threadgroup]]) {
|
||||
|
||||
const uint threads_per_tg = ntg.x * ntg.y * ntg.z;
|
||||
const uint tg_index = (tgpig.z * tgpg.y + tgpig.y) * tgpg.x + tgpig.x;
|
||||
const uint local_thread = tpitg.z * (ntg.x * ntg.y) + tpitg.y * ntg.x + tpitg.x;
|
||||
const uint thread_index = tg_index * threads_per_tg + local_thread;
|
||||
const uint64_t total_threads = (uint64_t) threads_per_tg * tgpg.x * tgpg.y * tgpg.z;
|
||||
const uint64_t total_outputs = (uint64_t) args.N * args.OC * args.OH * args.OW;
|
||||
|
||||
for (uint64_t index = thread_index; index < total_outputs; index += total_threads) {
|
||||
uint64_t tmp = index;
|
||||
|
||||
const int32_t ow = tmp % args.OW; tmp /= args.OW;
|
||||
const int32_t oh = tmp % args.OH; tmp /= args.OH;
|
||||
const int32_t oc = tmp % args.OC; tmp /= args.OC;
|
||||
const int32_t n = tmp;
|
||||
|
||||
float acc = 0.0f;
|
||||
|
||||
const int32_t base_x = ow*args.s0 - args.p0;
|
||||
const int32_t base_y = oh*args.s1 - args.p1;
|
||||
|
||||
int32_t ky_start = 0;
|
||||
if (base_y < 0) {
|
||||
ky_start = (-base_y + args.d1 - 1)/args.d1;
|
||||
}
|
||||
int32_t ky_end = args.KH;
|
||||
const int32_t y_max = args.IH - 1 - base_y;
|
||||
if (y_max < 0) {
|
||||
ky_end = ky_start;
|
||||
} else if (base_y + (args.KH - 1)*args.d1 >= args.IH) {
|
||||
ky_end = min(ky_end, y_max/args.d1 + 1);
|
||||
}
|
||||
|
||||
int32_t kx_start = 0;
|
||||
if (base_x < 0) {
|
||||
kx_start = (-base_x + args.d0 - 1)/args.d0;
|
||||
}
|
||||
int32_t kx_end = args.KW;
|
||||
const int32_t x_max = args.IW - 1 - base_x;
|
||||
if (x_max < 0) {
|
||||
kx_end = kx_start;
|
||||
} else if (base_x + (args.KW - 1)*args.d0 >= args.IW) {
|
||||
kx_end = min(kx_end, x_max/args.d0 + 1);
|
||||
}
|
||||
|
||||
if (ky_start < ky_end && kx_start < kx_end) {
|
||||
const uint64_t src_base_n = (uint64_t) n * args.nb13;
|
||||
const uint64_t w_base_oc = (uint64_t) oc * args.nb03;
|
||||
|
||||
for (int32_t ic = 0; ic < args.IC; ++ic) {
|
||||
const uint64_t src_base_nc = src_base_n + (uint64_t) ic * args.nb12;
|
||||
const uint64_t w_base_ocic = w_base_oc + (uint64_t) ic * args.nb02;
|
||||
|
||||
for (int32_t ky = ky_start; ky < ky_end; ++ky) {
|
||||
const int32_t iy = base_y + ky*args.d1;
|
||||
const uint64_t src_base_row = src_base_nc + (uint64_t) iy * args.nb11;
|
||||
const uint64_t w_base_row = w_base_ocic + (uint64_t) ky * args.nb01;
|
||||
|
||||
for (int32_t kx = kx_start; kx < kx_end; ++kx) {
|
||||
const int32_t ix = base_x + kx*args.d0;
|
||||
const uint64_t src_offs = src_base_row + (uint64_t) ix * args.nb10;
|
||||
const uint64_t w_offs = w_base_row + (uint64_t) kx * args.nb00;
|
||||
|
||||
const float x = *(device const float *)(src + src_offs);
|
||||
const float w = (float) (*(device const TK *)(weights + w_offs));
|
||||
|
||||
acc += x * w;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
const uint64_t dst_offs =
|
||||
(uint64_t) n * args.nb3 +
|
||||
(uint64_t) oc * args.nb2 +
|
||||
(uint64_t) oh * args.nb1 +
|
||||
(uint64_t) ow * args.nb0;
|
||||
|
||||
*(device float *)(dst + dst_offs) = acc;
|
||||
}
|
||||
}
|
||||
|
||||
template [[host_name("kernel_conv_2d_f32_f32")]]
|
||||
kernel void kernel_conv_2d<float>(
|
||||
constant ggml_metal_kargs_conv_2d & args,
|
||||
device const char * weights,
|
||||
device const char * src,
|
||||
device char * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
uint3 tgpg[[threadgroups_per_grid]],
|
||||
uint3 tpitg[[thread_position_in_threadgroup]],
|
||||
uint3 ntg[[threads_per_threadgroup]]);
|
||||
|
||||
template [[host_name("kernel_conv_2d_f16_f32")]]
|
||||
kernel void kernel_conv_2d<half>(
|
||||
constant ggml_metal_kargs_conv_2d & args,
|
||||
device const char * weights,
|
||||
device const char * src,
|
||||
device char * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
uint3 tgpg[[threadgroups_per_grid]],
|
||||
uint3 tpitg[[thread_position_in_threadgroup]],
|
||||
uint3 ntg[[threads_per_threadgroup]]);
|
||||
|
||||
typedef void (conv_transpose_1d_t)(
|
||||
constant ggml_metal_kargs_conv_transpose_1d & args,
|
||||
device const float * src0,
|
||||
device const float * src1,
|
||||
device char * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
uint3 tgpg[[threadgroups_per_grid]]);
|
||||
|
||||
template <typename T>
|
||||
kernel void kernel_conv_transpose_1d(
|
||||
constant ggml_metal_kargs_conv_transpose_1d & args,
|
||||
device const T * src0,
|
||||
device const float * src1,
|
||||
device char * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
uint3 tgpg[[threadgroups_per_grid]]) {
|
||||
|
||||
// For output position j on the time axis, only input positions
|
||||
// i such that i*s0 <= j < i*s0 + K
|
||||
// contribute -- i.e. i in [ceil((j - K + 1)/s0), floor(j/s0)]
|
||||
// intersected with [0, IL-1]. That's at most ceil(K/s0) values
|
||||
// (typically 2 for stride==K/2 transposed convs).
|
||||
const int32_t j = tgpig[0];
|
||||
const int32_t s0 = args.s0;
|
||||
const int32_t K = args.K;
|
||||
const int32_t IL = args.IL;
|
||||
|
||||
int32_t i_min;
|
||||
{
|
||||
int32_t a = j - K + 1;
|
||||
i_min = a <= 0 ? 0 : (a + s0 - 1) / s0; // ceil(a/s0) for a>0
|
||||
}
|
||||
int32_t i_max = j / s0;
|
||||
if (i_max > IL - 1) i_max = IL - 1;
|
||||
|
||||
float v = 0.0f;
|
||||
if (i_min <= i_max) {
|
||||
for (int64_t c = 0; c < args.IC; c++) {
|
||||
const int32_t kernel_offset = c * tgpg[1] * K + K * tgpig[1];
|
||||
const int32_t input_offset = c * IL;
|
||||
|
||||
for (int32_t i = i_min; i <= i_max; i++) {
|
||||
v += float(src0[kernel_offset + j - i * s0]) * src1[input_offset + i];
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
device float * dst_ptr = (device float *) (dst + tgpig[0] * args.nb0 + tgpig[1] * args.nb1);
|
||||
|
||||
dst_ptr[0] = v;
|
||||
}
|
||||
|
||||
template [[host_name("kernel_conv_transpose_1d_f32_f32")]]
|
||||
kernel void kernel_conv_transpose_1d<float>(
|
||||
constant ggml_metal_kargs_conv_transpose_1d & args,
|
||||
device const float * src0,
|
||||
device const float * src1,
|
||||
device char * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
uint3 tgpg[[threadgroups_per_grid]]);
|
||||
|
||||
template [[host_name("kernel_conv_transpose_1d_f16_f32")]]
|
||||
kernel void kernel_conv_transpose_1d<half>(
|
||||
constant ggml_metal_kargs_conv_transpose_1d & args,
|
||||
device const half * src0,
|
||||
device const float * src1,
|
||||
device char * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
uint3 tgpg[[threadgroups_per_grid]]);
|
||||
|
||||
|
||||
typedef void (conv_transpose_2d_t)(
|
||||
constant ggml_metal_kargs_conv_transpose_2d & args,
|
||||
device const float * src0,
|
||||
device const float * src1,
|
||||
device char * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
uint3 tgpg[[threadgroups_per_grid]]);
|
||||
|
||||
template <typename T>
|
||||
kernel void kernel_conv_transpose_2d(
|
||||
constant ggml_metal_kargs_conv_transpose_2d & args,
|
||||
device const T * src0,
|
||||
device const float * src1,
|
||||
device char * dst,
|
||||
threadgroup float * shared_sum [[threadgroup(0)]],
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
uint3 tpitg[[thread_position_in_threadgroup]],
|
||||
uint3 ntg[[threads_per_threadgroup]]) {
|
||||
|
||||
const int64_t out_x = tgpig[0];
|
||||
const int64_t out_y = tgpig[1];
|
||||
const int64_t out_c = tgpig[2];
|
||||
|
||||
const int64_t kw = tpitg[0];
|
||||
const int64_t kh = tpitg[1];
|
||||
|
||||
float v = 0.0f;
|
||||
|
||||
for (int64_t in_c = 0; in_c < args.IC; in_c++) {
|
||||
int64_t in_y = out_y - kh;
|
||||
|
||||
if (in_y < 0 || in_y % args.s0) continue;
|
||||
|
||||
in_y /= args.s0;
|
||||
|
||||
if (in_y >= args.IH) continue;
|
||||
|
||||
int64_t in_x = out_x - kw;
|
||||
|
||||
if (in_x < 0 || in_x % args.s0) continue;
|
||||
|
||||
in_x /= args.s0;
|
||||
|
||||
if (in_x >= args.IW) continue;
|
||||
|
||||
const int64_t input_idx = (args.IW * args.IH) * in_c + (args.IW) * in_y + in_x;
|
||||
const int64_t kernel_idx = (args.KH * args.KW * args.OC) * in_c + (args.KH * args.KW) * out_c + (args.KW) * kh + kw;
|
||||
|
||||
v += (float)src0[kernel_idx] * src1[input_idx];
|
||||
}
|
||||
|
||||
const uint tid = tpitg.y * ntg.x + tpitg.x;
|
||||
shared_sum[tid] = v;
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
if (tid == 0) {
|
||||
float total = 0.0f;
|
||||
const uint num_threads = ntg.x * ntg.y;
|
||||
for (uint i = 0; i < num_threads; i++) {
|
||||
total += shared_sum[i];
|
||||
}
|
||||
|
||||
device float * dst_ptr = (device float *) (dst + out_x*args.nb0 + out_y * args.nb1 + out_c*args.nb2);
|
||||
dst_ptr[0] = total;
|
||||
}
|
||||
}
|
||||
|
||||
template [[host_name("kernel_conv_transpose_2d_f32_f32")]]
|
||||
kernel void kernel_conv_transpose_2d<float>(
|
||||
constant ggml_metal_kargs_conv_transpose_2d & args,
|
||||
device const float * src0,
|
||||
device const float * src1,
|
||||
device char * dst,
|
||||
threadgroup float * shared_sum [[threadgroup(0)]],
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
uint3 tpitg[[thread_position_in_threadgroup]],
|
||||
uint3 ntg[[threads_per_threadgroup]]);
|
||||
|
||||
template [[host_name("kernel_conv_transpose_2d_f16_f32")]]
|
||||
kernel void kernel_conv_transpose_2d<half>(
|
||||
constant ggml_metal_kargs_conv_transpose_2d & args,
|
||||
device const half * src0,
|
||||
device const float * src1,
|
||||
device char * dst,
|
||||
threadgroup float * shared_sum [[threadgroup(0)]],
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
uint3 tpitg[[thread_position_in_threadgroup]],
|
||||
uint3 ntg[[threads_per_threadgroup]]);
|
||||
|
||||
template <typename T>
|
||||
kernel void kernel_conv_3d(
|
||||
constant ggml_metal_kargs_conv_3d & args,
|
||||
device const char * src0, // Weights [IC * OC, KD, KH, KW]
|
||||
device const char * src1, // Inputs [IC * N, ID, IH, IW]
|
||||
device char * dst, // Outputs [OC * N, OD, OH, OW]
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
uint3 tpitg[[thread_position_in_threadgroup]]) {
|
||||
|
||||
// 1. Un-flatten the spatial dimension from Grid X
|
||||
int64_t spatial_idx = tgpig.x * 32 + tpitg.x;
|
||||
|
||||
if (spatial_idx >= args.OW * args.OH * args.OD) {
|
||||
return; // Thread falls outside the spatial volume
|
||||
}
|
||||
|
||||
int64_t od = spatial_idx / (args.OW * args.OH);
|
||||
int64_t oh = (spatial_idx / args.OW) % args.OH;
|
||||
int64_t ow = spatial_idx % args.OW;
|
||||
|
||||
// 2. Map Y to Channels, Z to Batch
|
||||
int64_t oc = tgpig.y;
|
||||
int64_t batch_idx = tgpig.z;
|
||||
|
||||
// 3. Calculate anchor coordinates in the Input volume
|
||||
int64_t i_w_base = ow * args.s0 - args.p0;
|
||||
int64_t i_h_base = oh * args.s1 - args.p1;
|
||||
int64_t i_d_base = od * args.s2 - args.p2;
|
||||
|
||||
float sum = 0.0f;
|
||||
|
||||
// 4. Gather Loop (Iterate over Input Channels -> Depth -> Height -> Width)
|
||||
for (int64_t ic = 0; ic < args.IC; ++ic) {
|
||||
|
||||
// ggml packs batch and channel together in the 4th dimension
|
||||
int64_t src_cn_idx = batch_idx * args.IC + ic;
|
||||
int64_t w_cn_idx = oc * args.IC + ic;
|
||||
|
||||
for (int64_t kz = 0; kz < args.KD; ++kz) {
|
||||
int64_t id = i_d_base + kz * args.d2;
|
||||
if (id < 0 || id >= args.ID) continue; // Boundary check (Padding)
|
||||
|
||||
for (int64_t ky = 0; ky < args.KH; ++ky) {
|
||||
int64_t ih = i_h_base + ky * args.d1;
|
||||
if (ih < 0 || ih >= args.IH) continue;
|
||||
|
||||
for (int64_t kx = 0; kx < args.KW; ++kx) {
|
||||
int64_t iw = i_w_base + kx * args.d0;
|
||||
if (iw < 0 || iw >= args.IW) continue;
|
||||
|
||||
// Convert multi-dimensional coordinates to flat byte offsets
|
||||
int64_t w_idx = kx*args.nb00 + ky*args.nb01 + kz*args.nb02 + w_cn_idx*args.nb03;
|
||||
int64_t i_idx = iw*args.nb10 + ih*args.nb11 + id*args.nb12 + src_cn_idx*args.nb13;
|
||||
|
||||
// Dereference memory and cast weights to f32 if they were f16
|
||||
float w_val = (float)*(device const T*)((device const char*)src0 + w_idx);
|
||||
float i_val = *(device const float*)((device const char*)src1 + i_idx);
|
||||
|
||||
sum += w_val * i_val;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// 5. Write the accumulated value out to RAM
|
||||
int64_t dst_cn_idx = batch_idx * args.OC + oc;
|
||||
int64_t d_idx = ow*args.nb0 + oh*args.nb1 + od*args.nb2 + dst_cn_idx*args.nb3;
|
||||
|
||||
*(device float*)(dst + d_idx) = sum;
|
||||
}
|
||||
|
||||
// Explicit instantiations so the JIT compiler can find them by name
|
||||
template [[host_name("kernel_conv_3d_f32_f32")]]
|
||||
kernel void kernel_conv_3d<float>(
|
||||
constant ggml_metal_kargs_conv_3d & args,
|
||||
device const char * src0,
|
||||
device const char * src1,
|
||||
device char * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
uint3 tpitg[[thread_position_in_threadgroup]]);
|
||||
|
||||
// Explicit instantiation for f16 weights
|
||||
template [[host_name("kernel_conv_3d_f16_f32")]]
|
||||
kernel void kernel_conv_3d<half>(
|
||||
constant ggml_metal_kargs_conv_3d & args,
|
||||
device const char * src0,
|
||||
device const char * src1,
|
||||
device char * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
uint3 tpitg[[thread_position_in_threadgroup]]);
|
||||
@@ -0,0 +1,686 @@
|
||||
#pragma once
|
||||
|
||||
#include "common.h"
|
||||
|
||||
#define GGML_COMMON_DECL_METAL
|
||||
#define GGML_COMMON_IMPL_METAL
|
||||
#if defined(GGML_METAL_EMBED_LIBRARY)
|
||||
__embed_ggml-common.h__
|
||||
#else
|
||||
#include "ggml-common.h"
|
||||
#endif
|
||||
|
||||
#define QK_NL 16 // shared by mul_mm and get_rows_q instantiations
|
||||
|
||||
// NOTE: this is not dequantizing - we are simply fitting the template
|
||||
template <typename type4x4>
|
||||
void dequantize_f32(device const float4x4 * src, short il, thread type4x4 & reg) {
|
||||
reg = (type4x4)(*src);
|
||||
}
|
||||
|
||||
template <typename type4>
|
||||
void dequantize_f32_t4(device const float4 * src, short il, thread type4 & reg) {
|
||||
reg = (type4)(*src);
|
||||
}
|
||||
|
||||
template <typename type4x4>
|
||||
void dequantize_f16(device const half4x4 * src, short il, thread type4x4 & reg) {
|
||||
reg = (type4x4)(*src);
|
||||
}
|
||||
|
||||
template <typename type4>
|
||||
void dequantize_f16_t4(device const half4 * src, short il, thread type4 & reg) {
|
||||
reg = (type4)(*(src));
|
||||
}
|
||||
|
||||
#if defined(GGML_METAL_HAS_BF16)
|
||||
template <typename type4x4>
|
||||
void dequantize_bf16(device const bfloat4x4 * src, short il, thread type4x4 & reg) {
|
||||
reg = (type4x4)(*src);
|
||||
}
|
||||
|
||||
template <typename type4>
|
||||
void dequantize_bf16_t4(device const bfloat4 * src, short il, thread type4 & reg) {
|
||||
reg = (type4)(*(src));
|
||||
}
|
||||
#endif
|
||||
|
||||
template <typename type4x4>
|
||||
void dequantize_q1_0(device const block_q1_0 * xb, short il, thread type4x4 & reg) {
|
||||
device const uint8_t * qs = xb->qs;
|
||||
const float d = xb->d;
|
||||
const float neg_d = -d;
|
||||
|
||||
const int byte_offset = il * 2; // il*16 bits = il*2 bytes
|
||||
const uint8_t b0 = qs[byte_offset];
|
||||
const uint8_t b1 = qs[byte_offset + 1];
|
||||
|
||||
float4x4 reg_f;
|
||||
|
||||
reg_f[0][0] = select(neg_d, d, bool(b0 & 0x01));
|
||||
reg_f[0][1] = select(neg_d, d, bool(b0 & 0x02));
|
||||
reg_f[0][2] = select(neg_d, d, bool(b0 & 0x04));
|
||||
reg_f[0][3] = select(neg_d, d, bool(b0 & 0x08));
|
||||
reg_f[1][0] = select(neg_d, d, bool(b0 & 0x10));
|
||||
reg_f[1][1] = select(neg_d, d, bool(b0 & 0x20));
|
||||
reg_f[1][2] = select(neg_d, d, bool(b0 & 0x40));
|
||||
reg_f[1][3] = select(neg_d, d, bool(b0 & 0x80));
|
||||
|
||||
reg_f[2][0] = select(neg_d, d, bool(b1 & 0x01));
|
||||
reg_f[2][1] = select(neg_d, d, bool(b1 & 0x02));
|
||||
reg_f[2][2] = select(neg_d, d, bool(b1 & 0x04));
|
||||
reg_f[2][3] = select(neg_d, d, bool(b1 & 0x08));
|
||||
reg_f[3][0] = select(neg_d, d, bool(b1 & 0x10));
|
||||
reg_f[3][1] = select(neg_d, d, bool(b1 & 0x20));
|
||||
reg_f[3][2] = select(neg_d, d, bool(b1 & 0x40));
|
||||
reg_f[3][3] = select(neg_d, d, bool(b1 & 0x80));
|
||||
|
||||
reg = (type4x4) reg_f;
|
||||
}
|
||||
|
||||
template <typename type4>
|
||||
void dequantize_q1_0_t4(device const block_q1_0 * xb, short il, thread type4 & reg) {
|
||||
const float d = xb->d;
|
||||
const float neg_d = -d;
|
||||
const int base = il * 4;
|
||||
const uint8_t byte = xb->qs[base / 8];
|
||||
const int s = base % 8;
|
||||
|
||||
float4 reg_f;
|
||||
reg_f[0] = select(neg_d, d, bool((byte >> (s )) & 1));
|
||||
reg_f[1] = select(neg_d, d, bool((byte >> (s + 1)) & 1));
|
||||
reg_f[2] = select(neg_d, d, bool((byte >> (s + 2)) & 1));
|
||||
reg_f[3] = select(neg_d, d, bool((byte >> (s + 3)) & 1));
|
||||
|
||||
reg = (type4) reg_f;
|
||||
}
|
||||
|
||||
template <typename type4x4>
|
||||
void dequantize_q4_0(device const block_q4_0 * xb, short il, thread type4x4 & reg) {
|
||||
device const uint16_t * qs = ((device const uint16_t *)xb + 1);
|
||||
const float d1 = il ? (xb->d / 16.h) : xb->d;
|
||||
const float d2 = d1 / 256.f;
|
||||
const float md = -8.h * xb->d;
|
||||
const ushort mask0 = il ? 0x00F0 : 0x000F;
|
||||
const ushort mask1 = mask0 << 8;
|
||||
|
||||
float4x4 reg_f;
|
||||
|
||||
for (int i = 0; i < 8; i++) {
|
||||
reg_f[i/2][2*(i%2) + 0] = d1 * (qs[i] & mask0) + md;
|
||||
reg_f[i/2][2*(i%2) + 1] = d2 * (qs[i] & mask1) + md;
|
||||
}
|
||||
|
||||
reg = (type4x4) reg_f;
|
||||
}
|
||||
|
||||
template <typename type4>
|
||||
void dequantize_q4_0_t4(device const block_q4_0 * xb, short il, thread type4 & reg) {
|
||||
device const uint16_t * qs = ((device const uint16_t *)xb + 1);
|
||||
const float d1 = (il/4) ? (xb->d / 16.h) : xb->d;
|
||||
const float d2 = d1 / 256.f;
|
||||
const float md = -8.h * xb->d;
|
||||
const ushort mask0 = (il/4) ? 0x00F0 : 0x000F;
|
||||
const ushort mask1 = mask0 << 8;
|
||||
|
||||
for (int i = 0; i < 2; i++) {
|
||||
reg[2*i + 0] = d1 * (qs[2*(il%4) + i] & mask0) + md;
|
||||
reg[2*i + 1] = d2 * (qs[2*(il%4) + i] & mask1) + md;
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
|
||||
template <typename type4x4>
|
||||
void dequantize_q4_1(device const block_q4_1 * xb, short il, thread type4x4 & reg) {
|
||||
device const uint16_t * qs = ((device const uint16_t *)xb + 2);
|
||||
const float d1 = il ? (xb->d / 16.h) : xb->d;
|
||||
const float d2 = d1 / 256.f;
|
||||
const float m = xb->m;
|
||||
const ushort mask0 = il ? 0x00F0 : 0x000F;
|
||||
const ushort mask1 = mask0 << 8;
|
||||
|
||||
float4x4 reg_f;
|
||||
|
||||
for (int i = 0; i < 8; i++) {
|
||||
reg_f[i/2][2*(i%2) + 0] = ((qs[i] & mask0) * d1) + m;
|
||||
reg_f[i/2][2*(i%2) + 1] = ((qs[i] & mask1) * d2) + m;
|
||||
}
|
||||
|
||||
reg = (type4x4) reg_f;
|
||||
}
|
||||
|
||||
template <typename type4>
|
||||
void dequantize_q4_1_t4(device const block_q4_1 * xb, short il, thread type4 & reg) {
|
||||
device const uint16_t * qs = ((device const uint16_t *)xb + 2);
|
||||
const float d1 = (il/4) ? (xb->d / 16.h) : xb->d;
|
||||
const float d2 = d1 / 256.f;
|
||||
const float m = xb->m;
|
||||
const ushort mask0 = (il/4) ? 0x00F0 : 0x000F;
|
||||
const ushort mask1 = mask0 << 8;
|
||||
|
||||
for (int i = 0; i < 2; i++) {
|
||||
reg[2*i + 0] = d1 * (qs[2*(il%4) + i] & mask0) + m;
|
||||
reg[2*i + 1] = d2 * (qs[2*(il%4) + i] & mask1) + m;
|
||||
}
|
||||
}
|
||||
|
||||
template <typename type4x4>
|
||||
void dequantize_q5_0(device const block_q5_0 * xb, short il, thread type4x4 & reg) {
|
||||
device const uint16_t * qs = ((device const uint16_t *)xb + 3);
|
||||
const float d = xb->d;
|
||||
const float md = -16.h * xb->d;
|
||||
const ushort mask = il ? 0x00F0 : 0x000F;
|
||||
|
||||
const uint32_t qh = *((device const uint32_t *)xb->qh);
|
||||
|
||||
const int x_mv = il ? 4 : 0;
|
||||
|
||||
const int gh_mv = il ? 12 : 0;
|
||||
const int gh_bk = il ? 0 : 4;
|
||||
|
||||
float4x4 reg_f;
|
||||
|
||||
for (int i = 0; i < 8; i++) {
|
||||
// extract the 5-th bits for x0 and x1
|
||||
const uint8_t xh_0 = ((qh >> (gh_mv + 2*i )) << gh_bk) & 0x10;
|
||||
const uint8_t xh_1 = ((qh >> (gh_mv + 2*i+1)) << gh_bk) & 0x10;
|
||||
|
||||
// combine the 4-bits from qs with the 5th bit
|
||||
const int32_t x0 = ((((qs[i] ) & mask) >> x_mv) | xh_0);
|
||||
const int32_t x1 = ((((qs[i] >> 8) & mask) >> x_mv) | xh_1);
|
||||
|
||||
reg_f[i/2][2*(i%2) + 0] = d * x0 + md;
|
||||
reg_f[i/2][2*(i%2) + 1] = d * x1 + md;
|
||||
}
|
||||
|
||||
reg = (type4x4) reg_f;
|
||||
}
|
||||
|
||||
template <typename type4>
|
||||
void dequantize_q5_0_t4(device const block_q5_0 * xb, short il, thread type4 & reg) {
|
||||
device const uint16_t * qs = ((device const uint16_t *)xb + 3);
|
||||
const float d = xb->d;
|
||||
const float md = -16.h * xb->d;
|
||||
const ushort mask = (il/4) ? 0x00F0 : 0x000F;
|
||||
|
||||
const uint32_t qh = *((device const uint32_t *)xb->qh);
|
||||
|
||||
const int x_mv = (il/4) ? 4 : 0;
|
||||
|
||||
const int gh_mv = (il/4) ? 12 : 0;
|
||||
const int gh_bk = (il/4) ? 0 : 4;
|
||||
|
||||
for (int ii = 0; ii < 2; ii++) {
|
||||
int i = 2*(il%4) + ii;
|
||||
|
||||
// extract the 5-th bits for x0 and x1
|
||||
const uint8_t xh_0 = ((qh >> (gh_mv + 2*i )) << gh_bk) & 0x10;
|
||||
const uint8_t xh_1 = ((qh >> (gh_mv + 2*i+1)) << gh_bk) & 0x10;
|
||||
|
||||
// combine the 4-bits from qs with the 5th bit
|
||||
const int32_t x0 = ((((qs[i] ) & mask) >> x_mv) | xh_0);
|
||||
const int32_t x1 = ((((qs[i] >> 8) & mask) >> x_mv) | xh_1);
|
||||
|
||||
reg[2*ii + 0] = d * x0 + md;
|
||||
reg[2*ii + 1] = d * x1 + md;
|
||||
}
|
||||
}
|
||||
|
||||
template <typename type4x4>
|
||||
void dequantize_q5_1(device const block_q5_1 * xb, short il, thread type4x4 & reg) {
|
||||
device const uint16_t * qs = ((device const uint16_t *)xb + 4);
|
||||
const float d = xb->d;
|
||||
const float m = xb->m;
|
||||
const ushort mask = il ? 0x00F0 : 0x000F;
|
||||
|
||||
const uint32_t qh = *((device const uint32_t *)xb->qh);
|
||||
|
||||
const int x_mv = il ? 4 : 0;
|
||||
|
||||
const int gh_mv = il ? 12 : 0;
|
||||
const int gh_bk = il ? 0 : 4;
|
||||
|
||||
float4x4 reg_f;
|
||||
|
||||
for (int i = 0; i < 8; i++) {
|
||||
// extract the 5-th bits for x0 and x1
|
||||
const uint8_t xh_0 = ((qh >> (gh_mv + 2*i )) << gh_bk) & 0x10;
|
||||
const uint8_t xh_1 = ((qh >> (gh_mv + 2*i+1)) << gh_bk) & 0x10;
|
||||
|
||||
// combine the 4-bits from qs with the 5th bit
|
||||
const int32_t x0 = ((((qs[i] ) & mask) >> x_mv) | xh_0);
|
||||
const int32_t x1 = ((((qs[i] >> 8) & mask) >> x_mv) | xh_1);
|
||||
|
||||
reg_f[i/2][2*(i%2) + 0] = d * x0 + m;
|
||||
reg_f[i/2][2*(i%2) + 1] = d * x1 + m;
|
||||
}
|
||||
|
||||
reg = (type4x4) reg_f;
|
||||
}
|
||||
|
||||
template <typename type4>
|
||||
void dequantize_q5_1_t4(device const block_q5_1 * xb, short il, thread type4 & reg) {
|
||||
device const uint16_t * qs = ((device const uint16_t *)xb + 4);
|
||||
const float d = xb->d;
|
||||
const float m = xb->m;
|
||||
const ushort mask = (il/4) ? 0x00F0 : 0x000F;
|
||||
|
||||
const uint32_t qh = *((device const uint32_t *)xb->qh);
|
||||
|
||||
const int x_mv = (il/4) ? 4 : 0;
|
||||
|
||||
const int gh_mv = (il/4) ? 12 : 0;
|
||||
const int gh_bk = (il/4) ? 0 : 4;
|
||||
|
||||
for (int ii = 0; ii < 2; ii++) {
|
||||
int i = 2*(il%4) + ii;
|
||||
|
||||
// extract the 5-th bits for x0 and x1
|
||||
const uint8_t xh_0 = ((qh >> (gh_mv + 2*i )) << gh_bk) & 0x10;
|
||||
const uint8_t xh_1 = ((qh >> (gh_mv + 2*i+1)) << gh_bk) & 0x10;
|
||||
|
||||
// combine the 4-bits from qs with the 5th bit
|
||||
const int32_t x0 = ((((qs[i] ) & mask) >> x_mv) | xh_0);
|
||||
const int32_t x1 = ((((qs[i] >> 8) & mask) >> x_mv) | xh_1);
|
||||
|
||||
reg[2*ii + 0] = d * x0 + m;
|
||||
reg[2*ii + 1] = d * x1 + m;
|
||||
}
|
||||
}
|
||||
|
||||
template <typename type4x4>
|
||||
void dequantize_q8_0(device const block_q8_0 *xb, short il, thread type4x4 & reg) {
|
||||
device const int8_t * qs = ((device const int8_t *)xb->qs);
|
||||
const float d = xb->d;
|
||||
|
||||
float4x4 reg_f;
|
||||
|
||||
for (int i = 0; i < 16; i++) {
|
||||
reg_f[i/4][i%4] = (qs[i + 16*il] * d);
|
||||
}
|
||||
|
||||
reg = (type4x4) reg_f;
|
||||
}
|
||||
|
||||
template <typename type4>
|
||||
void dequantize_q8_0_t4(device const block_q8_0 *xb, short il, thread type4 & reg) {
|
||||
device const int8_t * qs = ((device const int8_t *)xb->qs);
|
||||
const float d = xb->d;
|
||||
|
||||
for (int i = 0; i < 4; i++) {
|
||||
reg[i] = (qs[4*(il%4) + i + 16*(il/4)] * d);
|
||||
}
|
||||
}
|
||||
|
||||
template <typename type4x4>
|
||||
void dequantize_mxfp4(device const block_mxfp4 * xb, short il, thread type4x4 & reg) {
|
||||
device const uint8_t * q2 = (device const uint8_t *)xb->qs;
|
||||
|
||||
const float d = e8m0_to_fp32(xb->e);
|
||||
const uint8_t shr = il >= 1 ? 4 : 0;
|
||||
|
||||
for (int i = 0; i < 4; ++i) {
|
||||
reg[i][0] = d * kvalues_mxfp4_f[(q2[4*i + 0] >> shr) & 0x0F];
|
||||
reg[i][1] = d * kvalues_mxfp4_f[(q2[4*i + 1] >> shr) & 0x0F];
|
||||
reg[i][2] = d * kvalues_mxfp4_f[(q2[4*i + 2] >> shr) & 0x0F];
|
||||
reg[i][3] = d * kvalues_mxfp4_f[(q2[4*i + 3] >> shr) & 0x0F];
|
||||
}
|
||||
}
|
||||
|
||||
template <typename type4>
|
||||
void dequantize_mxfp4_t4(device const block_mxfp4 * xb, short il, thread type4 & reg) {
|
||||
device const uint8_t * q2 = (device const uint8_t *)xb->qs;
|
||||
|
||||
const float d = e8m0_to_fp32(xb->e);
|
||||
const short il4 = il%4;
|
||||
|
||||
const uint8_t shr = il >= 4 ? 4 : 0;
|
||||
|
||||
reg[0] = d * kvalues_mxfp4_f[(q2[4*il4 + 0] >> shr) & 0x0F];
|
||||
reg[1] = d * kvalues_mxfp4_f[(q2[4*il4 + 1] >> shr) & 0x0F];
|
||||
reg[2] = d * kvalues_mxfp4_f[(q2[4*il4 + 2] >> shr) & 0x0F];
|
||||
reg[3] = d * kvalues_mxfp4_f[(q2[4*il4 + 3] >> shr) & 0x0F];
|
||||
}
|
||||
|
||||
template <typename type4x4>
|
||||
void dequantize_q2_K(device const block_q2_K *xb, short il, thread type4x4 & reg) {
|
||||
const float d = xb->d;
|
||||
const float min = xb->dmin;
|
||||
device const uint8_t * q = (device const uint8_t *)xb->qs;
|
||||
float dl, ml;
|
||||
uint8_t sc = xb->scales[il];
|
||||
|
||||
q = q + 32*(il/8) + 16*(il&1);
|
||||
il = (il/2)%4;
|
||||
|
||||
half coef = il>1 ? (il>2 ? 1/64.h : 1/16.h) : (il>0 ? 1/4.h : 1.h);
|
||||
uchar mask = il>1 ? (il>2 ? 192 : 48) : (il>0 ? 12 : 3);
|
||||
dl = d * (sc & 0xF) * coef, ml = min * (sc >> 4);
|
||||
for (int i = 0; i < 16; ++i) {
|
||||
reg[i/4][i%4] = dl * (q[i] & mask) - ml;
|
||||
}
|
||||
}
|
||||
|
||||
template <typename type4x4>
|
||||
void dequantize_q3_K(device const block_q3_K *xb, short il, thread type4x4 & reg) {
|
||||
const half d_all = xb->d;
|
||||
device const uint8_t * q = (device const uint8_t *)xb->qs;
|
||||
device const uint8_t * h = (device const uint8_t *)xb->hmask;
|
||||
device const int8_t * scales = (device const int8_t *)xb->scales;
|
||||
|
||||
q = q + 32 * (il/8) + 16 * (il&1);
|
||||
h = h + 16 * (il&1);
|
||||
uint8_t m = 1 << (il/2);
|
||||
uint16_t kmask1 = (il/4)>1 ? ((il/4)>2 ? 192 : 48) : \
|
||||
((il/4)>0 ? 12 : 3);
|
||||
uint16_t kmask2 = il/8 ? 0xF0 : 0x0F;
|
||||
uint16_t scale_2 = scales[il%8], scale_1 = scales[8 + il%4];
|
||||
int16_t dl_int = (il/4)&1 ? (scale_2&kmask2) | ((scale_1&kmask1) << 2)
|
||||
: (scale_2&kmask2) | ((scale_1&kmask1) << 4);
|
||||
float dl = il<8 ? d_all * (dl_int - 32.f) : d_all * (dl_int / 16.f - 32.f);
|
||||
const float ml = 4.f * dl;
|
||||
|
||||
il = (il/2) & 3;
|
||||
const half coef = il>1 ? (il>2 ? 1/64.h : 1/16.h) : (il>0 ? 1/4.h : 1.h);
|
||||
const uint8_t mask = il>1 ? (il>2 ? 192 : 48) : (il>0 ? 12 : 3);
|
||||
dl *= coef;
|
||||
|
||||
for (int i = 0; i < 16; ++i) {
|
||||
reg[i/4][i%4] = dl * (q[i] & mask) - (h[i] & m ? 0 : ml);
|
||||
}
|
||||
}
|
||||
|
||||
static inline uchar2 get_scale_min_k4_just2(int j, int k, device const uchar * q) {
|
||||
return j < 4 ? uchar2{uchar(q[j+0+k] & 63), uchar(q[j+4+k] & 63)}
|
||||
: uchar2{uchar((q[j+4+k] & 0xF) | ((q[j-4+k] & 0xc0) >> 2)), uchar((q[j+4+k] >> 4) | ((q[j-0+k] & 0xc0) >> 2))};
|
||||
}
|
||||
|
||||
template <typename type4x4>
|
||||
void dequantize_q4_K(device const block_q4_K * xb, short il, thread type4x4 & reg) {
|
||||
device const uchar * q = xb->qs;
|
||||
|
||||
short is = (il/4) * 2;
|
||||
q = q + (il/4) * 32 + 16 * (il&1);
|
||||
il = il & 3;
|
||||
const uchar2 sc = get_scale_min_k4_just2(is, il/2, xb->scales);
|
||||
const float d = il < 2 ? xb->d : xb->d / 16.h;
|
||||
const float min = xb->dmin;
|
||||
const float dl = d * sc[0];
|
||||
const float ml = min * sc[1];
|
||||
|
||||
const ushort mask = il < 2 ? 0x0F : 0xF0;
|
||||
for (int i = 0; i < 16; ++i) {
|
||||
reg[i/4][i%4] = dl * (q[i] & mask) - ml;
|
||||
}
|
||||
}
|
||||
|
||||
template <typename type4x4>
|
||||
void dequantize_q5_K(device const block_q5_K *xb, short il, thread type4x4 & reg) {
|
||||
device const uint8_t * q = xb->qs;
|
||||
device const uint8_t * qh = xb->qh;
|
||||
|
||||
short is = (il/4) * 2;
|
||||
q = q + 32 * (il/4) + 16 * (il&1);
|
||||
qh = qh + 16 * (il&1);
|
||||
uint8_t ul = 1 << (il/2);
|
||||
il = il & 3;
|
||||
const uchar2 sc = get_scale_min_k4_just2(is, il/2, xb->scales);
|
||||
const float d = il < 2 ? xb->d : xb->d / 16.f;
|
||||
const float min = xb->dmin;
|
||||
const float dl = d * sc[0];
|
||||
const float ml = min * sc[1];
|
||||
|
||||
const ushort mask = il<2 ? 0x0F : 0xF0;
|
||||
const float qh_val = il<2 ? 16.f : 256.f;
|
||||
for (int i = 0; i < 16; ++i) {
|
||||
reg[i/4][i%4] = dl * ((q[i] & mask) + (qh[i] & ul ? qh_val : 0)) - ml;
|
||||
}
|
||||
}
|
||||
|
||||
template <typename type4x4>
|
||||
void dequantize_q6_K(device const block_q6_K *xb, short il, thread type4x4 & reg) {
|
||||
const half d_all = xb->d;
|
||||
device const uint16_t * ql = (device const uint16_t *)xb->ql;
|
||||
device const uint16_t * qh = (device const uint16_t *)xb->qh;
|
||||
device const int8_t * scales = (device const int8_t *)xb->scales;
|
||||
|
||||
ql = ql + 32*(il/8) + 16*((il/2)&1) + 8*(il&1);
|
||||
qh = qh + 16*(il/8) + 8*(il&1);
|
||||
float sc = scales[(il%2) + 2 * ((il/2))];
|
||||
il = (il/2) & 3;
|
||||
|
||||
const uint32_t kmask1 = il>1 ? (il>2 ? 0xC0C0C0C0 : 0x30303030) : (il>0 ? 0x0C0C0C0C : 0x03030303);
|
||||
const uint32_t kmask2 = il>1 ? 0xF0F0F0F0 : 0x0F0F0F0F;
|
||||
const float ml = d_all * sc * 32.f;
|
||||
const float dl0 = d_all * sc;
|
||||
const float dl1 = dl0 / 256.f;
|
||||
const float dl2 = dl0 / (256.f * 256.f);
|
||||
const float dl3 = dl0 / (256.f * 256.f * 256.f);
|
||||
const uint8_t shr_h = il>2 ? 2 : 0;
|
||||
const uint8_t shl_h = il>1 ? 0 : (il>0 ? 2 : 4);
|
||||
const uint8_t shr_l = il>1 ? 4 : 0;
|
||||
for (int i = 0; i < 4; ++i) {
|
||||
const uint32_t low = (ql[2*i] | (uint32_t)(ql[2*i+1] << 16)) & kmask2;
|
||||
const uint32_t high = (qh[2*i] | (uint32_t)(qh[2*i+1] << 16)) & kmask1;
|
||||
const uint32_t q = ((high << shl_h) >> shr_h) | (low >> shr_l);
|
||||
reg[i][0] = dl0 * ((half)(q & 0xFF)) - ml;
|
||||
reg[i][1] = dl1 * ((float)(q & 0xFF00)) - ml;
|
||||
reg[i][2] = dl2 * ((float)(q & 0xFF0000)) - ml;
|
||||
reg[i][3] = dl3 * ((float)(q & 0xFF000000)) - ml;
|
||||
}
|
||||
}
|
||||
|
||||
template <typename type4x4>
|
||||
void dequantize_iq2_xxs(device const block_iq2_xxs * xb, short il, thread type4x4 & reg) {
|
||||
// il is 0...15 for QK_K = 256 => index of block of 32 is il/2
|
||||
const float d = xb->d;
|
||||
const int ib32 = il/2;
|
||||
il = il%2;
|
||||
// il = 0 or 1. il = 0 processes the first 16 quants in a block of 32, il = 1 the second 16
|
||||
// each block of 32 needs 2 uint32_t's for the quants & scale, so 4 uint16_t's.
|
||||
device const uint16_t * q2 = xb->qs + 4*ib32;
|
||||
const uint32_t aux32_g = q2[0] | (q2[1] << 16);
|
||||
const uint32_t aux32_s = q2[2] | (q2[3] << 16);
|
||||
thread const uint8_t * aux8 = (thread const uint8_t *)&aux32_g;
|
||||
const float dl = d * (0.5f + (aux32_s >> 28)) * 0.25f;
|
||||
constant uint8_t * grid = (constant uint8_t *)(iq2xxs_grid + aux8[2*il+0]);
|
||||
uint8_t signs = ksigns_iq2xs[(aux32_s >> 14*il) & 127];
|
||||
for (int i = 0; i < 8; ++i) {
|
||||
reg[i/4][i%4] = dl * grid[i] * (signs & kmask_iq2xs[i] ? -1.f : 1.f);
|
||||
}
|
||||
grid = (constant uint8_t *)(iq2xxs_grid + aux8[2*il+1]);
|
||||
signs = ksigns_iq2xs[(aux32_s >> (14*il+7)) & 127];
|
||||
for (int i = 0; i < 8; ++i) {
|
||||
reg[2+i/4][i%4] = dl * grid[i] * (signs & kmask_iq2xs[i] ? -1.f : 1.f);
|
||||
}
|
||||
}
|
||||
|
||||
template <typename type4x4>
|
||||
void dequantize_iq2_xs(device const block_iq2_xs * xb, short il, thread type4x4 & reg) {
|
||||
// il is 0...15 for QK_K = 256 => index of block of 32 is il/2
|
||||
const float d = xb->d;
|
||||
const int ib32 = il/2;
|
||||
il = il%2;
|
||||
// il = 0 or 1. il = 0 processes the first 16 quants in a block of 32, il = 1 the second 16
|
||||
device const uint16_t * q2 = xb->qs + 4*ib32;
|
||||
const float dl = d * (0.5f + ((xb->scales[ib32] >> 4*il) & 0xf)) * 0.25f;
|
||||
constant uint8_t * grid = (constant uint8_t *)(iq2xs_grid + (q2[2*il+0] & 511));
|
||||
uint8_t signs = ksigns_iq2xs[q2[2*il+0] >> 9];
|
||||
for (int i = 0; i < 8; ++i) {
|
||||
reg[i/4][i%4] = dl * grid[i] * (signs & kmask_iq2xs[i] ? -1.f : 1.f);
|
||||
}
|
||||
grid = (constant uint8_t *)(iq2xs_grid + (q2[2*il+1] & 511));
|
||||
signs = ksigns_iq2xs[q2[2*il+1] >> 9];
|
||||
for (int i = 0; i < 8; ++i) {
|
||||
reg[2+i/4][i%4] = dl * grid[i] * (signs & kmask_iq2xs[i] ? -1.f : 1.f);
|
||||
}
|
||||
}
|
||||
|
||||
template <typename type4x4>
|
||||
void dequantize_iq3_xxs(device const block_iq3_xxs * xb, short il, thread type4x4 & reg) {
|
||||
// il is 0...15 for QK_K = 256 => index of block of 32 is il/2
|
||||
const float d = xb->d;
|
||||
const int ib32 = il/2;
|
||||
il = il%2;
|
||||
// il = 0 or 1. il = 0 processes the first 16 quants in a block of 32, il = 1 the second 16
|
||||
device const uint8_t * q3 = xb->qs + 8*ib32;
|
||||
device const uint16_t * gas = (device const uint16_t *)(xb->qs + QK_K/4) + 2*ib32;
|
||||
const uint32_t aux32 = gas[0] | (gas[1] << 16);
|
||||
const float dl = d * (0.5f + (aux32 >> 28)) * 0.5f;
|
||||
constant uint8_t * grid1 = (constant uint8_t *)(iq3xxs_grid + q3[4*il+0]);
|
||||
constant uint8_t * grid2 = (constant uint8_t *)(iq3xxs_grid + q3[4*il+1]);
|
||||
uint8_t signs = ksigns_iq2xs[(aux32 >> 14*il) & 127];
|
||||
for (int i = 0; i < 4; ++i) {
|
||||
reg[0][i] = dl * grid1[i] * (signs & kmask_iq2xs[i+0] ? -1.f : 1.f);
|
||||
reg[1][i] = dl * grid2[i] * (signs & kmask_iq2xs[i+4] ? -1.f : 1.f);
|
||||
}
|
||||
grid1 = (constant uint8_t *)(iq3xxs_grid + q3[4*il+2]);
|
||||
grid2 = (constant uint8_t *)(iq3xxs_grid + q3[4*il+3]);
|
||||
signs = ksigns_iq2xs[(aux32 >> (14*il+7)) & 127];
|
||||
for (int i = 0; i < 4; ++i) {
|
||||
reg[2][i] = dl * grid1[i] * (signs & kmask_iq2xs[i+0] ? -1.f : 1.f);
|
||||
reg[3][i] = dl * grid2[i] * (signs & kmask_iq2xs[i+4] ? -1.f : 1.f);
|
||||
}
|
||||
}
|
||||
|
||||
template <typename type4x4>
|
||||
void dequantize_iq3_s(device const block_iq3_s * xb, short il, thread type4x4 & reg) {
|
||||
// il is 0...15 for QK_K = 256 => index of block of 32 is il/2
|
||||
const float d = xb->d;
|
||||
const int ib32 = il/2;
|
||||
il = il%2;
|
||||
// il = 0 or 1. il = 0 processes the first 16 quants in a block of 32, il = 1 the second 16
|
||||
device const uint8_t * qs = xb->qs + 8*ib32;
|
||||
device const uint8_t * signs = xb->signs + 4*ib32 + 2*il;
|
||||
const uint8_t qh = xb->qh[ib32] >> 4*il;
|
||||
const float dl = d * (1 + 2*((xb->scales[ib32/2] >> 4*(ib32%2)) & 0xf));
|
||||
constant uint8_t * grid1 = (constant uint8_t *)(iq3s_grid + (qs[4*il+0] | ((qh << 8) & 256)));
|
||||
constant uint8_t * grid2 = (constant uint8_t *)(iq3s_grid + (qs[4*il+1] | ((qh << 7) & 256)));
|
||||
for (int i = 0; i < 4; ++i) {
|
||||
reg[0][i] = dl * grid1[i] * select(1, -1, signs[0] & kmask_iq2xs[i+0]);
|
||||
reg[1][i] = dl * grid2[i] * select(1, -1, signs[0] & kmask_iq2xs[i+4]);
|
||||
}
|
||||
grid1 = (constant uint8_t *)(iq3s_grid + (qs[4*il+2] | ((qh << 6) & 256)));
|
||||
grid2 = (constant uint8_t *)(iq3s_grid + (qs[4*il+3] | ((qh << 5) & 256)));
|
||||
for (int i = 0; i < 4; ++i) {
|
||||
reg[2][i] = dl * grid1[i] * select(1, -1, signs[1] & kmask_iq2xs[i+0]);
|
||||
reg[3][i] = dl * grid2[i] * select(1, -1, signs[1] & kmask_iq2xs[i+4]);
|
||||
}
|
||||
}
|
||||
|
||||
template <typename type4x4>
|
||||
void dequantize_iq2_s(device const block_iq2_s * xb, short il, thread type4x4 & reg) {
|
||||
// il is 0...15 for QK_K = 256 => index of block of 32 is il/2
|
||||
const float d = xb->d;
|
||||
const int ib32 = il/2;
|
||||
il = il%2;
|
||||
// il = 0 or 1. il = 0 processes the first 16 quants in a block of 32, il = 1 the second 16
|
||||
device const uint8_t * qs = xb->qs + 4*ib32 + 2*il;
|
||||
device const uint8_t * signs = qs + QK_K/8;
|
||||
const uint8_t qh = xb->qh[ib32] >> 4*il;
|
||||
const float dl = d * (0.5f + ((xb->scales[ib32] >> 4*il) & 0xf)) * 0.25f;
|
||||
constant uint8_t * grid1 = (constant uint8_t *)(iq2s_grid + (qs[0] | ((qh << 8) & 0x300)));
|
||||
constant uint8_t * grid2 = (constant uint8_t *)(iq2s_grid + (qs[1] | ((qh << 6) & 0x300)));
|
||||
for (int i = 0; i < 8; ++i) {
|
||||
reg[i/4+0][i%4] = dl * grid1[i] * select(1, -1, signs[0] & kmask_iq2xs[i]);
|
||||
reg[i/4+2][i%4] = dl * grid2[i] * select(1, -1, signs[1] & kmask_iq2xs[i]);
|
||||
}
|
||||
}
|
||||
|
||||
template <typename type4x4>
|
||||
void dequantize_iq1_s(device const block_iq1_s * xb, short il, thread type4x4 & reg) {
|
||||
// il is 0...15 for QK_K = 256 => index of block of 32 is il/2
|
||||
const int ib32 = il/2;
|
||||
il = il%2;
|
||||
const float d = xb->d;
|
||||
device const uint8_t * qs = xb->qs + 4*ib32 + 2*il;
|
||||
device const uint16_t * qh = xb->qh;
|
||||
const float dl = d * (2*((qh[ib32] >> 12) & 7) + 1);
|
||||
const float ml = dl * (qh[ib32] & 0x8000 ? -1 - IQ1S_DELTA : -1 + IQ1S_DELTA);
|
||||
const uint16_t h = qh[ib32] >> 6*il;
|
||||
constant uint8_t * grid1 = (constant uint8_t *)(iq1s_grid_gpu + (qs[0] | ((h << 8) & 0x700)));
|
||||
constant uint8_t * grid2 = (constant uint8_t *)(iq1s_grid_gpu + (qs[1] | ((h << 5) & 0x700)));
|
||||
for (int i = 0; i < 4; ++i) {
|
||||
reg[0][i] = dl * (grid1[i] & 0xf) + ml;
|
||||
reg[1][i] = dl * (grid1[i] >> 4) + ml;
|
||||
reg[2][i] = dl * (grid2[i] & 0xf) + ml;
|
||||
reg[3][i] = dl * (grid2[i] >> 4) + ml;
|
||||
}
|
||||
}
|
||||
|
||||
template <typename type4x4>
|
||||
void dequantize_iq1_m(device const block_iq1_m * xb, short il, thread type4x4 & reg) {
|
||||
// il is 0...15 for QK_K = 256 => index of block of 32 is il/2
|
||||
const int ib32 = il/2;
|
||||
il = il%2;
|
||||
device const uint16_t * sc = (device const uint16_t *)xb->scales;
|
||||
|
||||
iq1m_scale_t scale;
|
||||
scale.u16 = (sc[0] >> 12) | ((sc[1] >> 8) & 0x00f0) | ((sc[2] >> 4) & 0x0f00) | (sc[3] & 0xf000);
|
||||
const float d = scale.f16;
|
||||
|
||||
device const uint8_t * qs = xb->qs + 4*ib32 + 2*il;
|
||||
device const uint8_t * qh = xb->qh + 2*ib32 + il;
|
||||
|
||||
const float dl = d * (2*((sc[ib32/2] >> (6*(ib32%2)+3*il)) & 7) + 1);
|
||||
const float ml1 = dl * (qh[0] & 0x08 ? -1 - IQ1M_DELTA : -1 + IQ1M_DELTA);
|
||||
const float ml2 = dl * (qh[0] & 0x80 ? -1 - IQ1M_DELTA : -1 + IQ1M_DELTA);
|
||||
constant uint8_t * grid1 = (constant uint8_t *)(iq1s_grid_gpu + (qs[0] | ((qh[0] << 8) & 0x700)));
|
||||
constant uint8_t * grid2 = (constant uint8_t *)(iq1s_grid_gpu + (qs[1] | ((qh[0] << 4) & 0x700)));
|
||||
for (int i = 0; i < 4; ++i) {
|
||||
reg[0][i] = dl * (grid1[i] & 0xf) + ml1;
|
||||
reg[1][i] = dl * (grid1[i] >> 4) + ml1;
|
||||
reg[2][i] = dl * (grid2[i] & 0xf) + ml2;
|
||||
reg[3][i] = dl * (grid2[i] >> 4) + ml2;
|
||||
}
|
||||
}
|
||||
|
||||
template <typename type4x4>
|
||||
void dequantize_iq4_nl(device const block_iq4_nl * xb, short il, thread type4x4 & reg) {
|
||||
device const uint16_t * q4 = (device const uint16_t *)xb->qs;
|
||||
const float d = xb->d;
|
||||
uint32_t aux32;
|
||||
thread const uint8_t * q8 = (thread const uint8_t *)&aux32;
|
||||
for (int i = 0; i < 4; ++i) {
|
||||
aux32 = ((q4[2*i] | (q4[2*i+1] << 16)) >> 4*il) & 0x0f0f0f0f;
|
||||
reg[i][0] = d * kvalues_iq4nl_f[q8[0]];
|
||||
reg[i][1] = d * kvalues_iq4nl_f[q8[1]];
|
||||
reg[i][2] = d * kvalues_iq4nl_f[q8[2]];
|
||||
reg[i][3] = d * kvalues_iq4nl_f[q8[3]];
|
||||
}
|
||||
}
|
||||
|
||||
template <typename type4>
|
||||
void dequantize_iq4_nl_t4(device const block_iq4_nl * xb, short il, thread type4 & reg) {
|
||||
device const uint16_t * q4 = (device const uint16_t *)xb->qs;
|
||||
const float d = xb->d;
|
||||
uint32_t aux32;
|
||||
thread const uint8_t * q8 = (thread const uint8_t *)&aux32;
|
||||
aux32 = ((q4[2*(il%4)] | (q4[2*(il%4)+1] << 16)) >> 4*(il/4)) & 0x0f0f0f0f;
|
||||
reg[0] = d * kvalues_iq4nl_f[q8[0]];
|
||||
reg[1] = d * kvalues_iq4nl_f[q8[1]];
|
||||
reg[2] = d * kvalues_iq4nl_f[q8[2]];
|
||||
reg[3] = d * kvalues_iq4nl_f[q8[3]];
|
||||
}
|
||||
|
||||
template <typename type4x4>
|
||||
void dequantize_iq4_xs(device const block_iq4_xs * xb, short il, thread type4x4 & reg) {
|
||||
// il is 0...15 for QK_K = 256 => index of block of 32 is il/2
|
||||
const int ib32 = il/2;
|
||||
il = il%2;
|
||||
// il = 0 or 1. il = 0 processes the first 16 quants in a block of 32, il = 1 the second 16
|
||||
device const uint32_t * q4 = (device const uint32_t *)xb->qs + 4*ib32;
|
||||
const int ls = ((xb->scales_l[ib32/2] >> 4*(ib32%2)) & 0xf) | (((xb->scales_h >> 2*ib32) & 3) << 4);
|
||||
const float d = (float)xb->d * (ls - 32);
|
||||
uint32_t aux32;
|
||||
thread const uint8_t * q8 = (thread const uint8_t *)&aux32;
|
||||
for (int i = 0; i < 4; ++i) {
|
||||
aux32 = (q4[i] >> 4*il) & 0x0f0f0f0f;
|
||||
reg[i][0] = d * kvalues_iq4nl_f[q8[0]];
|
||||
reg[i][1] = d * kvalues_iq4nl_f[q8[1]];
|
||||
reg[i][2] = d * kvalues_iq4nl_f[q8[2]];
|
||||
reg[i][3] = d * kvalues_iq4nl_f[q8[3]];
|
||||
}
|
||||
}
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
@@ -0,0 +1,250 @@
|
||||
#include "common.h"
|
||||
|
||||
constant short FC_gated_delta_net_ne20 [[function_constant(FC_GATED_DELTA_NET + 0)]];
|
||||
constant short FC_gated_delta_net_ne30 [[function_constant(FC_GATED_DELTA_NET + 1)]];
|
||||
constant short FC_gated_delta_net_K [[function_constant(FC_GATED_DELTA_NET + 2)]];
|
||||
|
||||
#if 1
|
||||
template<short NSG>
|
||||
kernel void kernel_gated_delta_net_impl(
|
||||
constant ggml_metal_kargs_gated_delta_net & args,
|
||||
device const char * q,
|
||||
device const char * k,
|
||||
device const char * v,
|
||||
device const char * g,
|
||||
device const char * b,
|
||||
device const char * s,
|
||||
device char * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
uint3 tpitg[[thread_position_in_threadgroup]],
|
||||
uint3 ntg[[threads_per_threadgroup]]) {
|
||||
#define S_v FC_gated_delta_net_ne20
|
||||
#define G FC_gated_delta_net_ne30
|
||||
#define K FC_gated_delta_net_K
|
||||
|
||||
const uint tx = tpitg.x;
|
||||
const uint ty = tpitg.y;
|
||||
|
||||
const uint i23 = tgpig.z; // B (n_seqs)
|
||||
const uint i21 = tgpig.y; // H (head)
|
||||
const uint i20 = tgpig.x*NSG + ty; // row within S_v
|
||||
|
||||
const uint i01 = i21 % args.ne01;
|
||||
const uint i11 = i21 % args.ne11;
|
||||
|
||||
const float scale = 1.0f / sqrt((float)S_v);
|
||||
|
||||
// input state layout [S_v, S_v, H, n_seqs] (s0 only): per-seq stride is H*D.
|
||||
// state is stored transposed: M[i20][is] = S[is][i20], so row i20 is contiguous
|
||||
const uint state_in_base = (i23*args.ne21 + i21)*S_v*S_v + i20*S_v;
|
||||
device const float * s_ptr = (device const float *) (s) + state_in_base;
|
||||
|
||||
float ls[NSG];
|
||||
|
||||
FOR_UNROLL (short j = 0; j < NSG; j++) {
|
||||
const short is = tx*NSG + j;
|
||||
ls[j] = s_ptr[is];
|
||||
}
|
||||
|
||||
device float * dst_attn = (device float *) (dst) + (i23*args.ne22*args.ne21 + i21)*S_v + i20;
|
||||
|
||||
device const float * q_ptr = (device const float *) (q + i23*args.nb03 + i01*args.nb01);
|
||||
device const float * k_ptr = (device const float *) (k + i23*args.nb13 + i11*args.nb11);
|
||||
device const float * v_ptr = (device const float *) (v + i23*args.nb23 + i21*args.nb21);
|
||||
|
||||
device const float * b_ptr = (device const float *) (b) + (i23*args.ne22*args.ne21 + i21);
|
||||
device const float * g_ptr = (device const float *) (g) + (i23*args.ne22*args.ne21 + i21)*G;
|
||||
|
||||
// snapshot slot mapping: slot 0 = most recent state, slot s = s tokens back.
|
||||
// When n_tokens < K, only slots 0..n_tokens-1 are written; older slots are caller-owned.
|
||||
|
||||
// output state base offset: after attention scores
|
||||
const uint attn_size = args.ne22 * args.ne21 * S_v * args.ne23;
|
||||
// output state per-slot size: S_v * S_v * H * n_seqs
|
||||
const uint state_size_per_snap = S_v * S_v * args.ne21 * args.ne23;
|
||||
// per-(seq,head) offset within a slot
|
||||
const uint state_out_base = (i23*args.ne21 + i21)*S_v*S_v + i20*S_v;
|
||||
|
||||
for (short t = 0; t < args.ne22; t++) {
|
||||
float s_k = 0.0f;
|
||||
|
||||
if (G == 1) {
|
||||
const float g_exp = exp(g_ptr[0]);
|
||||
|
||||
FOR_UNROLL (short j = 0; j < NSG; j++) {
|
||||
const short is = tx*NSG + j;
|
||||
ls[j] *= g_exp;
|
||||
|
||||
s_k += ls[j]*k_ptr[is];
|
||||
}
|
||||
} else {
|
||||
// KDA
|
||||
FOR_UNROLL (short j = 0; j < NSG; j++) {
|
||||
const short is = tx*NSG + j;
|
||||
ls[j] *= exp(g_ptr[is]);
|
||||
|
||||
s_k += ls[j]*k_ptr[is];
|
||||
}
|
||||
}
|
||||
|
||||
s_k = simd_sum(s_k);
|
||||
|
||||
const float d = (v_ptr[i20] - s_k)*b_ptr[0];
|
||||
|
||||
float y = 0.0f;
|
||||
|
||||
FOR_UNROLL (short j = 0; j < NSG; j++) {
|
||||
const short is = tx*NSG + j;
|
||||
ls[j] += k_ptr[is]*d;
|
||||
|
||||
y += ls[j]*q_ptr[is];
|
||||
}
|
||||
|
||||
y = simd_sum(y);
|
||||
|
||||
if (tx == 0) {
|
||||
dst_attn[t*args.ne21*S_v] = y*scale;
|
||||
}
|
||||
|
||||
q_ptr += args.ns02;
|
||||
k_ptr += args.ns12;
|
||||
v_ptr += args.ns22;
|
||||
|
||||
b_ptr += args.ne21;
|
||||
g_ptr += args.ne21*G;
|
||||
|
||||
if (K > 1) {
|
||||
const int target_slot = (int)args.ne22 - 1 - (int)t;
|
||||
if (target_slot >= 0 && target_slot < (int)K) {
|
||||
device float * dst_state = (device float *) (dst) + attn_size + (uint)target_slot * state_size_per_snap + state_out_base;
|
||||
FOR_UNROLL (short j = 0; j < NSG; j++) {
|
||||
const short is = tx*NSG + j;
|
||||
dst_state[is] = ls[j];
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if (K == 1) {
|
||||
device float * dst_state = (device float *) (dst) + attn_size + state_out_base;
|
||||
FOR_UNROLL (short j = 0; j < NSG; j++) {
|
||||
const short is = tx*NSG + j;
|
||||
dst_state[is] = ls[j];
|
||||
}
|
||||
}
|
||||
|
||||
#undef S_v
|
||||
#undef G
|
||||
#undef K
|
||||
}
|
||||
|
||||
typedef decltype(kernel_gated_delta_net_impl<4>) kernel_gated_delta_net_t;
|
||||
|
||||
template [[host_name("kernel_gated_delta_net_f32_1")]] kernel kernel_gated_delta_net_t kernel_gated_delta_net_impl<1>;
|
||||
template [[host_name("kernel_gated_delta_net_f32_2")]] kernel kernel_gated_delta_net_t kernel_gated_delta_net_impl<2>;
|
||||
template [[host_name("kernel_gated_delta_net_f32_4")]] kernel kernel_gated_delta_net_t kernel_gated_delta_net_impl<4>;
|
||||
|
||||
#else
|
||||
// a simplified version of the above
|
||||
// no performance improvement, so keep the above version for now
|
||||
|
||||
template<typename T, short NSG>
|
||||
kernel void kernel_gated_delta_net_impl(
|
||||
constant ggml_metal_kargs_gated_delta_net & args,
|
||||
device const char * q,
|
||||
device const char * k,
|
||||
device const char * v,
|
||||
device const char * g,
|
||||
device const char * b,
|
||||
device const char * s,
|
||||
device char * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
uint3 tpitg[[thread_position_in_threadgroup]],
|
||||
uint3 ntg[[threads_per_threadgroup]]) {
|
||||
#define S_v FC_gated_delta_net_ne20
|
||||
#define G FC_gated_delta_net_ne30
|
||||
|
||||
const uint tx = tpitg.x;
|
||||
const uint ty = tpitg.y;
|
||||
|
||||
const uint i23 = tgpig.z; // B
|
||||
const uint i21 = tgpig.y; // H
|
||||
const uint i20 = tgpig.x*NSG + ty;
|
||||
|
||||
const uint i01 = i21 % args.ne01;
|
||||
const uint i11 = i21 % args.ne11;
|
||||
|
||||
const float scale = 1.0f / sqrt((float)S_v);
|
||||
|
||||
device const float * s_ptr = (device const float *) (s) + (i23*args.ne21 + i21)*S_v*S_v + i20;
|
||||
|
||||
float lsf[NSG];
|
||||
|
||||
FOR_UNROLL (short j = 0; j < NSG; j++) {
|
||||
const short is = tx*NSG + j;
|
||||
lsf[j] = s_ptr[is*S_v];
|
||||
}
|
||||
|
||||
thread T * ls = (thread T *) (lsf);
|
||||
|
||||
device float * dst_attn = (device float *) (dst) + (i23*args.ne22*args.ne21 + i21)*S_v + i20;
|
||||
|
||||
device const float * q_ptr = (device const float *) (q + i23*args.nb03 + i01*args.nb01);
|
||||
device const float * k_ptr = (device const float *) (k + i23*args.nb13 + i11*args.nb11);
|
||||
device const float * v_ptr = (device const float *) (v + i23*args.nb23 + i21*args.nb21);
|
||||
|
||||
device const float * b_ptr = (device const float *) (b) + (i23*args.ne22*args.ne21 + i21);
|
||||
device const float * g_ptr = (device const float *) (g) + (i23*args.ne22*args.ne21 + i21)*G;
|
||||
|
||||
for (short t = 0; t < args.ne22; t++) {
|
||||
device const T * qt_ptr = (device const T *) (q_ptr);
|
||||
device const T * kt_ptr = (device const T *) (k_ptr);
|
||||
device const T * gt_ptr = (device const T *) (g_ptr);
|
||||
|
||||
if (G == 1) {
|
||||
*ls *= exp(g_ptr[0]);
|
||||
} else {
|
||||
// KDA
|
||||
*ls *= exp(gt_ptr[tx]);
|
||||
}
|
||||
|
||||
const float s_k = simd_sum(dot(*ls, kt_ptr[tx]));
|
||||
|
||||
const float d = (v_ptr[i20] - s_k)*b_ptr[0];
|
||||
|
||||
*ls += kt_ptr[tx]*d;
|
||||
|
||||
const float y = simd_sum(dot(*ls, qt_ptr[tx]));
|
||||
|
||||
if (tx == 0) {
|
||||
*dst_attn = y*scale;
|
||||
}
|
||||
|
||||
q_ptr += args.ns02;
|
||||
k_ptr += args.ns12;
|
||||
v_ptr += args.ns22;
|
||||
|
||||
b_ptr += args.ne21;
|
||||
g_ptr += args.ne21*G;
|
||||
|
||||
dst_attn += args.ne21*S_v;
|
||||
}
|
||||
|
||||
device float * dst_state = (device float *) (dst) + args.ne23*args.ne22*args.ne21*S_v + (i23*args.ne21 + i21)*S_v*S_v + i20;
|
||||
device T * dstt_state = (device T *) (dst_state);
|
||||
|
||||
FOR_UNROLL (short j = 0; j < NSG; j++) {
|
||||
const short is = tx*NSG + j;
|
||||
dst_state[is*S_v] = lsf[j];
|
||||
}
|
||||
|
||||
#undef S_v
|
||||
#undef G
|
||||
}
|
||||
|
||||
typedef decltype(kernel_gated_delta_net_impl<float4, 4>) kernel_gated_delta_net_t;
|
||||
|
||||
template [[host_name("kernel_gated_delta_net_f32_1")]] kernel kernel_gated_delta_net_t kernel_gated_delta_net_impl<float, 1>;
|
||||
template [[host_name("kernel_gated_delta_net_f32_2")]] kernel kernel_gated_delta_net_t kernel_gated_delta_net_impl<float2, 2>;
|
||||
template [[host_name("kernel_gated_delta_net_f32_4")]] kernel kernel_gated_delta_net_t kernel_gated_delta_net_impl<float4, 4>;
|
||||
#endif
|
||||
@@ -0,0 +1,347 @@
|
||||
#include "common.h"
|
||||
|
||||
kernel void kernel_argmax_f32(
|
||||
constant ggml_metal_kargs_argmax & args,
|
||||
device const char * src0,
|
||||
device char * dst,
|
||||
threadgroup char * shmem [[threadgroup(0)]],
|
||||
uint tgpig[[threadgroup_position_in_grid]],
|
||||
uint tpitg[[thread_position_in_threadgroup]],
|
||||
uint sgitg[[simdgroup_index_in_threadgroup]],
|
||||
uint tiisg[[thread_index_in_simdgroup]],
|
||||
uint ntg[[threads_per_threadgroup]]) {
|
||||
device const float * x_row = (device const float *) ((device const char *) src0 + tgpig * args.nb01);
|
||||
|
||||
float lmax = -INFINITY;
|
||||
int32_t larg = -1;
|
||||
|
||||
for (int i00 = tpitg; i00 < args.ne00; i00 += ntg) {
|
||||
if (x_row[i00] > lmax) {
|
||||
lmax = x_row[i00];
|
||||
larg = i00;
|
||||
}
|
||||
}
|
||||
|
||||
// find the argmax value in the block
|
||||
float max_val = simd_max(lmax);
|
||||
int32_t arg_val = simd_max(select(-1, larg, lmax == max_val));
|
||||
|
||||
device int32_t * dst_i32 = (device int32_t *) dst;
|
||||
|
||||
threadgroup float * shared_maxval = (threadgroup float *) shmem;
|
||||
threadgroup int32_t * shared_argmax = (threadgroup int32_t *) shmem + N_SIMDWIDTH;
|
||||
|
||||
if (ntg > N_SIMDWIDTH) {
|
||||
if (sgitg == 0) {
|
||||
shared_maxval[tiisg] = -INFINITY;
|
||||
shared_argmax[tiisg] = -1;
|
||||
}
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
if (tiisg == 0) {
|
||||
shared_maxval[sgitg] = max_val;
|
||||
shared_argmax[sgitg] = arg_val;
|
||||
}
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
max_val = shared_maxval[tiisg];
|
||||
arg_val = shared_argmax[tiisg];
|
||||
|
||||
float max_val_reduced = simd_max(max_val);
|
||||
int32_t arg_val_reduced = simd_max(select(-1, arg_val, max_val == max_val_reduced));
|
||||
|
||||
dst_i32[tgpig] = arg_val_reduced;
|
||||
|
||||
return;
|
||||
}
|
||||
|
||||
dst_i32[tgpig] = arg_val;
|
||||
}
|
||||
|
||||
kernel void kernel_diag_f32(
|
||||
constant ggml_metal_kargs_diag & args,
|
||||
device const char * src0,
|
||||
device char * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
ushort tiitg[[thread_index_in_threadgroup]]) {
|
||||
constexpr short NW = N_SIMDWIDTH;
|
||||
|
||||
const int32_t i3 = tgpig.z;
|
||||
const int32_t i2 = tgpig.y;
|
||||
const int32_t i1 = tgpig.x;
|
||||
|
||||
device const float * src0_ptr = (device const float *)(src0 + i2*args.nb02 + i3*args.nb03);
|
||||
device float * dst_ptr = (device float *)(dst + i1*args.nb01 + i2*args.nb2 + i3*args.nb3);
|
||||
|
||||
for (int i0 = tiitg; i0 < args.ne0; i0 += NW) {
|
||||
dst_ptr[i0] = i0 == i1 ? src0_ptr[i0] : 0.0f;
|
||||
}
|
||||
}
|
||||
|
||||
kernel void kernel_roll_f32(
|
||||
constant ggml_metal_kargs_roll & args,
|
||||
device const char * src0,
|
||||
device char * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
uint3 tpitg[[thread_position_in_threadgroup]],
|
||||
uint3 ntg[[threads_per_threadgroup]]) {
|
||||
|
||||
const int64_t i3 = tgpig.z;
|
||||
const int64_t i2 = tgpig.y;
|
||||
const int64_t i1 = tgpig.x;
|
||||
|
||||
device const float * src0_ptr = (device const float *) src0;
|
||||
device float * dst_ptr = (device float *) dst;
|
||||
|
||||
for (int i0 = tpitg.x; i0 < args.ne0; i0 += ntg.x) {
|
||||
// apply shifts and wrap around
|
||||
int64_t i00 = i0 - args.s0;
|
||||
int64_t i01 = i1 - args.s1;
|
||||
int64_t i02 = i2 - args.s2;
|
||||
int64_t i03 = i3 - args.s3;
|
||||
|
||||
if (i00 < 0) { i00 += args.ne00; } else if (i00 >= args.ne00) { i00 -= args.ne00; }
|
||||
if (i01 < 0) { i01 += args.ne01; } else if (i01 >= args.ne01) { i01 -= args.ne01; }
|
||||
if (i02 < 0) { i02 += args.ne02; } else if (i02 >= args.ne02) { i02 -= args.ne02; }
|
||||
if (i03 < 0) { i03 += args.ne03; } else if (i03 >= args.ne03) { i03 -= args.ne03; }
|
||||
|
||||
int64_t src_idx = i03*args.ne02*args.ne01*args.ne00 + i02*args.ne01*args.ne00 + i01*args.ne00 + i00;
|
||||
int64_t dst_idx = i3 *args.ne2 *args.ne1 *args.ne0 + i2 *args.ne1 *args.ne0 + i1 *args.ne0 + i0;
|
||||
|
||||
dst_ptr[dst_idx] = src0_ptr[src_idx];
|
||||
}
|
||||
}
|
||||
|
||||
template <typename T>
|
||||
kernel void kernel_pad_impl(
|
||||
constant ggml_metal_kargs_pad & args,
|
||||
device const char * src0,
|
||||
device char * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
uint3 tpitg[[thread_position_in_threadgroup]],
|
||||
uint3 ntg[[threads_per_threadgroup]]) {
|
||||
const int32_t i3 = tgpig.z;
|
||||
const int32_t i2 = tgpig.y;
|
||||
const int32_t k0 = tgpig.x/args.ne1;
|
||||
const int32_t i1 = tgpig.x - k0*args.ne1;
|
||||
|
||||
const int32_t i03 = i3;
|
||||
const int32_t i02 = i2;
|
||||
const int32_t i01 = i1;
|
||||
|
||||
device const T * src0_ptr = (device const T *) (src0 + i03*args.nb03 + i02*args.nb02 + i01*args.nb01);
|
||||
device T * dst_ptr = (device T *) (dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1);
|
||||
|
||||
for (int32_t l0 = 0; l0 < 1024; l0 += ntg.x) {
|
||||
const int32_t i0 = k0*1024 + tpitg.x + l0;
|
||||
if (i0 >= args.ne0) {
|
||||
break;
|
||||
}
|
||||
|
||||
if (i0 < args.ne00 && i1 < args.ne01 && i2 < args.ne02 && i3 < args.ne03) {
|
||||
dst_ptr[i0] = src0_ptr[i0];
|
||||
} else {
|
||||
dst_ptr[i0] = 0.0f;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
typedef decltype(kernel_pad_impl<float>) kernel_pad_t;
|
||||
|
||||
template [[host_name("kernel_pad_f32")]] kernel kernel_pad_t kernel_pad_impl<float>;
|
||||
template [[host_name("kernel_pad_f32_4")]] kernel kernel_pad_t kernel_pad_impl<float4>;
|
||||
|
||||
// TODO: this is slow - optimize
|
||||
kernel void kernel_pad_reflect_1d_f32(
|
||||
constant ggml_metal_kargs_pad_reflect_1d & args,
|
||||
device const char * src0,
|
||||
device char * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
uint3 tgpg[[threadgroups_per_grid]],
|
||||
uint3 tpitg[[thread_position_in_threadgroup]],
|
||||
uint3 ntg[[threads_per_threadgroup]]) {
|
||||
|
||||
const int64_t i3 = tgpig.z;
|
||||
const int64_t i2 = tgpig.y;
|
||||
const int64_t i1 = tgpig.x;
|
||||
|
||||
const int64_t i03 = i3;
|
||||
const int64_t i02 = i2;
|
||||
const int64_t i01 = i1;
|
||||
|
||||
device const float * src0_ptr = (device const float *) (src0 + i03*args.nb03 + i02*args.nb02 + i01*args.nb01);
|
||||
device float * dst_ptr = (device float *) (dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1);
|
||||
|
||||
if (i1 < args.ne01 && i2 < args.ne02 && i3 < args.ne03) {
|
||||
for (int i0 = tpitg.x; i0 < args.ne0; i0 += ntg.x) {
|
||||
if (i0 < args.p0) {
|
||||
dst_ptr[i0] = src0_ptr[args.p0 - i0];
|
||||
} else if (i0 < args.ne0 - args.p1) {
|
||||
dst_ptr[i0] = src0_ptr[i0 - args.p0];
|
||||
} else {
|
||||
dst_ptr[i0] = src0_ptr[(args.ne0 - args.p1 - args.p0) - (args.p1 + 1 - (args.ne0 - i0)) - 1];
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
kernel void kernel_arange_f32(
|
||||
constant ggml_metal_kargs_arange & args,
|
||||
device char * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
uint3 tpitg[[thread_position_in_threadgroup]],
|
||||
uint3 ntg[[threads_per_threadgroup]]) {
|
||||
|
||||
device float * dst_ptr = (device float *) dst;
|
||||
|
||||
for (int i0 = tpitg.x; i0 < args.ne0; i0 += ntg.x) {
|
||||
dst_ptr[i0] = args.start + args.step * i0;
|
||||
}
|
||||
}
|
||||
|
||||
kernel void kernel_timestep_embedding_f32(
|
||||
constant ggml_metal_kargs_timestep_embedding & args,
|
||||
device const char * src0,
|
||||
device char * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
uint3 tpitg[[thread_position_in_threadgroup]],
|
||||
uint3 ntg[[threads_per_threadgroup]]) {
|
||||
|
||||
int i = tgpig.x;
|
||||
device float * embed_data = (device float *)(dst + i*args.nb1);
|
||||
|
||||
int half_ = args.dim / 2;
|
||||
for (int j = tpitg.x; j < half_; j += ntg.x) {
|
||||
float timestep = ((device float *)src0)[i];
|
||||
float freq = (float)exp(-log((float)args.max_period) * j / half_);
|
||||
float arg = timestep * freq;
|
||||
embed_data[j ] = cos(arg);
|
||||
embed_data[j + half_] = sin(arg);
|
||||
}
|
||||
|
||||
if (args.dim % 2 != 0 && tpitg.x == 0) {
|
||||
embed_data[2 * half_] = 0.f;
|
||||
}
|
||||
}
|
||||
|
||||
kernel void kernel_opt_step_adamw_f32(
|
||||
constant ggml_metal_kargs_opt_step_adamw & args,
|
||||
device float * x,
|
||||
device const float * g,
|
||||
device float * g_m,
|
||||
device float * g_v,
|
||||
device const float * pars,
|
||||
uint gid[[thread_position_in_grid]]) {
|
||||
|
||||
if (gid >= args.np) {
|
||||
return;
|
||||
}
|
||||
|
||||
const float alpha = pars[0];
|
||||
const float beta1 = pars[1];
|
||||
const float beta2 = pars[2];
|
||||
const float eps = pars[3];
|
||||
const float wd = pars[4];
|
||||
const float beta1h = pars[5];
|
||||
const float beta2h = pars[6];
|
||||
|
||||
const float gi = g[gid];
|
||||
const float gmi = g_m[gid] * beta1 + gi * (1.0f - beta1);
|
||||
const float gvi = g_v[gid] * beta2 + gi * gi * (1.0f - beta2);
|
||||
|
||||
g_m[gid] = gmi;
|
||||
g_v[gid] = gvi;
|
||||
|
||||
const float mh = gmi * beta1h;
|
||||
const float vh = sqrt(gvi * beta2h) + eps;
|
||||
|
||||
x[gid] = x[gid] * (1.0f - alpha * wd) - alpha * mh / vh;
|
||||
}
|
||||
|
||||
kernel void kernel_opt_step_sgd_f32(
|
||||
constant ggml_metal_kargs_opt_step_sgd & args,
|
||||
device float * x,
|
||||
device const float * g,
|
||||
device const float * pars,
|
||||
uint gid[[thread_position_in_grid]]) {
|
||||
|
||||
if (gid >= args.np) {
|
||||
return;
|
||||
}
|
||||
|
||||
x[gid] = x[gid] * (1.0f - pars[0] * pars[1]) - pars[0] * g[gid];
|
||||
}
|
||||
|
||||
template<typename T>
|
||||
kernel void kernel_memset(
|
||||
constant ggml_metal_kargs_memset & args,
|
||||
device T * dst,
|
||||
uint tpig[[thread_position_in_grid]]) {
|
||||
dst[tpig] = args.val;
|
||||
}
|
||||
|
||||
typedef decltype(kernel_memset<int64_t>) kernel_memset_t;
|
||||
|
||||
template [[host_name("kernel_memset_i64")]] kernel kernel_memset_t kernel_memset<int64_t>;
|
||||
|
||||
constant short FC_count_equal_nsg [[function_constant(FC_COUNT_EQUAL + 0)]];
|
||||
|
||||
template<typename T>
|
||||
kernel void kernel_count_equal(
|
||||
constant ggml_metal_kargs_count_equal & args,
|
||||
device const char * src0,
|
||||
device const char * src1,
|
||||
device atomic_int * dst,
|
||||
threadgroup int32_t * shmem_i32 [[threadgroup(0)]],
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
ushort3 tpitg[[thread_position_in_threadgroup]],
|
||||
ushort sgitg[[simdgroup_index_in_threadgroup]],
|
||||
ushort tiisg[[thread_index_in_simdgroup]],
|
||||
ushort3 ntg[[threads_per_threadgroup]]) {
|
||||
const short NSG = FC_count_equal_nsg;
|
||||
|
||||
const int i3 = tgpig.z;
|
||||
const int i2 = tgpig.y;
|
||||
const int i1 = tgpig.x;
|
||||
|
||||
if (i3 >= args.ne03 || i2 >= args.ne02 || i1 >= args.ne01) {
|
||||
return;
|
||||
}
|
||||
|
||||
int sum = 0;
|
||||
|
||||
device const char * base0 = src0 + i1*args.nb01 + i2*args.nb02 + i3*args.nb03;
|
||||
device const char * base1 = src1 + i1*args.nb11 + i2*args.nb12 + i3*args.nb13;
|
||||
|
||||
for (int64_t i0 = tpitg.x; i0 < args.ne00; i0 += ntg.x) {
|
||||
const T v0 = *(device const T *)(base0 + i0*args.nb00);
|
||||
const T v1 = *(device const T *)(base1 + i0*args.nb10);
|
||||
sum += (v0 == v1);
|
||||
}
|
||||
|
||||
sum = simd_sum(sum);
|
||||
|
||||
if (tiisg == 0) {
|
||||
shmem_i32[sgitg] = sum;
|
||||
}
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
if (sgitg == 0) {
|
||||
float v = 0.0f;
|
||||
if (tpitg.x < NSG) {
|
||||
v = shmem_i32[tpitg.x];
|
||||
}
|
||||
|
||||
float total = simd_sum(v);
|
||||
if (tpitg.x == 0) {
|
||||
atomic_fetch_add_explicit(dst, (int32_t) total, memory_order_relaxed);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
typedef decltype(kernel_count_equal<int32_t>) kernel_count_equal_t;
|
||||
|
||||
template [[host_name("kernel_count_equal_i32")]] kernel kernel_count_equal_t kernel_count_equal<int32_t>;
|
||||
@@ -0,0 +1,838 @@
|
||||
#include "common.h"
|
||||
#include "dequantize.h"
|
||||
|
||||
constant bool FC_mul_mm_bc_inp [[function_constant(FC_MUL_MM + 0)]];
|
||||
constant bool FC_mul_mm_bc_out [[function_constant(FC_MUL_MM + 1)]];
|
||||
constant short FC_mul_mm_ne12 [[function_constant(FC_MUL_MM + 2)]];
|
||||
constant short FC_mul_mm_ne13 [[function_constant(FC_MUL_MM + 3)]];
|
||||
constant short FC_mul_mm_r2 [[function_constant(FC_MUL_MM + 4)]];
|
||||
constant short FC_mul_mm_r3 [[function_constant(FC_MUL_MM + 5)]];
|
||||
|
||||
// each block_q contains 16*nl weights
|
||||
#ifdef GGML_METAL_HAS_TENSOR
|
||||
template<
|
||||
typename SA, typename SA_4x4, typename SA_8x8,
|
||||
typename SB, typename SB_2x4, typename SB_8x8,
|
||||
typename block_q, short nl, void (*dequantize_func)(device const block_q *, short, thread SA_4x4 &),
|
||||
typename T0, typename T0_4x4, typename T1, typename T1_2x4>
|
||||
kernel void kernel_mul_mm(
|
||||
constant ggml_metal_kargs_mul_mm & args,
|
||||
device const char * srcA,
|
||||
device const char * srcB,
|
||||
device char * dst,
|
||||
threadgroup char * shmem [[threadgroup(0)]],
|
||||
uint3 tgpig [[threadgroup_position_in_grid]],
|
||||
ushort tiitg [[thread_index_in_threadgroup]],
|
||||
ushort sgitg [[simdgroup_index_in_threadgroup]]) {
|
||||
(void) sgitg;
|
||||
|
||||
// Matrix dimensions: A(M,K) x B(K,N) -> C(M,N)
|
||||
const int K = args.ne00;
|
||||
const int M = args.ne0;
|
||||
const int N = args.ne1;
|
||||
|
||||
// Batch dimension handling
|
||||
const int im = tgpig.z;
|
||||
const int i12 = im % FC_mul_mm_ne12;
|
||||
const int i13 = im / FC_mul_mm_ne12;
|
||||
|
||||
// Batch offsets for srcA and srcB
|
||||
const uint64_t offset0 = (i12/FC_mul_mm_r2)*args.nb02 + (i13/FC_mul_mm_r3)*args.nb03;
|
||||
|
||||
// Tile dimensions
|
||||
constexpr int NRB = SZ_SIMDGROUP * N_MM_BLOCK_X * N_MM_SIMD_GROUP_X;
|
||||
constexpr int NRA = SZ_SIMDGROUP * N_MM_BLOCK_Y * N_MM_SIMD_GROUP_Y;
|
||||
|
||||
// Tile offsets in output matrix
|
||||
const int ra = tgpig.y * NRA;
|
||||
const int rb = tgpig.x * NRB;
|
||||
|
||||
// Threadgroup memory for dequantized A tile only
|
||||
threadgroup SA * sa = (threadgroup SA *)(shmem);
|
||||
|
||||
// Work-item count for A loading
|
||||
constexpr int A_WORK_ITEMS = NRA * N_MM_NK;
|
||||
constexpr int NUM_THREADS = N_SIMDWIDTH * N_MM_SIMD_GROUP_X * N_MM_SIMD_GROUP_Y;
|
||||
|
||||
// tA wraps threadgroup memory
|
||||
auto tA = tensor(sa, dextents<int32_t, 2>(N_MM_NK_TOTAL, NRA));
|
||||
|
||||
// tB wraps device memory directly
|
||||
device T1 * ptrB = (device T1 *)(srcB + args.nb12*i12 + args.nb13*i13);
|
||||
const int strideB = args.nb11 / sizeof(T1);
|
||||
auto tB = tensor(ptrB, dextents<int32_t, 2>(K, N), array<int, 2>({1, strideB}));
|
||||
|
||||
// Configure matmul operation
|
||||
mpp::tensor_ops::matmul2d<
|
||||
mpp::tensor_ops::matmul2d_descriptor(
|
||||
NRB, NRA, N_MM_NK_TOTAL, false, true, true,
|
||||
mpp::tensor_ops::matmul2d_descriptor::mode::multiply_accumulate),
|
||||
execution_simdgroups<N_MM_SIMD_GROUP_X * N_MM_SIMD_GROUP_Y>> mm;
|
||||
|
||||
auto cT = mm.get_destination_cooperative_tensor<decltype(tB), decltype(tA), float>();
|
||||
|
||||
// Accumulate partial results over K dimension
|
||||
for (int loop_k = 0; loop_k < K; loop_k += N_MM_NK_TOTAL) {
|
||||
// === PHASE 1: Dequantization of A into threadgroup memory ===
|
||||
for (int work = tiitg; work < A_WORK_ITEMS; work += NUM_THREADS) {
|
||||
const int row = work / N_MM_NK;
|
||||
const int k_chunk = work % N_MM_NK;
|
||||
const int k_pos = loop_k + k_chunk * 16;
|
||||
const short k_base = k_chunk * 16;
|
||||
|
||||
// Bounds check: skip device read if row is out of matrix bounds
|
||||
if (ra + row < M) {
|
||||
if (is_same<T0_4x4, block_q>::value && FC_mul_mm_bc_inp) {
|
||||
// Element-wise reads when K is not aligned (nb01 not aligned for half4x4/float4x4).
|
||||
// MSL spec Table 2.5: half4x4 requires 8-byte alignment. When K is odd,
|
||||
// nb01 = K*2 is not 8-byte aligned, so odd-row pointers are misaligned.
|
||||
// Mirrors the legacy kernel's existing guard.
|
||||
device const T0 * row_ptr = (device const T0 *)(srcA + args.nb01 * (ra + row) + offset0);
|
||||
|
||||
FOR_UNROLL (short i = 0; i < 16; i++) {
|
||||
sa[row * N_MM_NK_TOTAL + (k_base + i)] = (k_pos + i < K) ? (SA) row_ptr[k_pos + i] : (SA)0;
|
||||
}
|
||||
} else {
|
||||
const int block_idx = k_pos / (16 * nl);
|
||||
const short il = (k_pos / 16) % nl;
|
||||
|
||||
device const block_q * row_ptr = (device const block_q *)(srcA + args.nb01 * (ra + row) + offset0);
|
||||
|
||||
SA_4x4 temp_a;
|
||||
dequantize_func(row_ptr + block_idx, il, temp_a);
|
||||
|
||||
FOR_UNROLL (short i = 0; i < 16; i++) {
|
||||
// Zero-pad A for K positions beyond valid range (handles partial K iterations)
|
||||
sa[row * N_MM_NK_TOTAL + (k_base + i)] = (k_pos + i < K) ? temp_a[i/4][i%4] : (SA)0;
|
||||
}
|
||||
}
|
||||
} else {
|
||||
// Zero-pad rows beyond matrix bounds
|
||||
FOR_UNROLL (short i = 0; i < 16; i++) {
|
||||
sa[row * N_MM_NK_TOTAL + (k_base + i)] = (SA)0;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
// === PHASE 2: Tensor matmul ===
|
||||
auto mA = tA.slice(0, 0);
|
||||
auto mB = tB.slice(loop_k, rb);
|
||||
|
||||
mm.run(mB, mA, cT);
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
}
|
||||
|
||||
// Store result tile to output matrix (with batch offset)
|
||||
// cT.store handles bounds checking via tD's extents (M, N)
|
||||
device float * dstBatch = (device float *)dst + im * N * M;
|
||||
|
||||
auto tD = tensor(dstBatch, dextents<int32_t, 2>(M, N), array<int, 2>({1, M}));
|
||||
cT.store(tD.slice(ra, rb));
|
||||
}
|
||||
|
||||
#else
|
||||
|
||||
template<
|
||||
typename S0, typename S0_4x4, typename S0_8x8,
|
||||
typename S1, typename S1_2x4, typename S1_8x8,
|
||||
typename block_q, short nl, void (*dequantize_func)(device const block_q *, short, thread S0_4x4 &),
|
||||
typename T0, typename T0_4x4, typename T1, typename T1_2x4>
|
||||
kernel void kernel_mul_mm(
|
||||
constant ggml_metal_kargs_mul_mm & args,
|
||||
device const char * src0,
|
||||
device const char * src1,
|
||||
device char * dst,
|
||||
threadgroup char * shmem [[threadgroup(0)]],
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
ushort tiitg[[thread_index_in_threadgroup]],
|
||||
ushort sgitg[[simdgroup_index_in_threadgroup]]) {
|
||||
|
||||
threadgroup S0 * sa = (threadgroup S0 *)(shmem);
|
||||
threadgroup S1 * sb = (threadgroup S1 *)(shmem + 4096);
|
||||
|
||||
constexpr int NR0 = 64;
|
||||
constexpr int NR1 = 32;
|
||||
|
||||
constexpr int NK = 32;
|
||||
constexpr int NL0 = NK/16;
|
||||
constexpr int NL1 = NK/8;
|
||||
|
||||
const int im = tgpig.z;
|
||||
const int r0 = tgpig.y*NR0;
|
||||
const int r1 = tgpig.x*NR1;
|
||||
|
||||
// if this block is of 64x32 shape or smaller
|
||||
const short nr0 = (args.ne0 - r0 < NR0) ? (args.ne0 - r0) : NR0;
|
||||
const short nr1 = (args.ne1 - r1 < NR1) ? (args.ne1 - r1) : NR1;
|
||||
|
||||
// a thread shouldn't load data outside of the matrix
|
||||
const short lr0 = ((short)tiitg/NL0) < nr0 ? ((short)tiitg/NL0) : nr0 - 1; // 0 .. 63
|
||||
const short lr1 = ((short)tiitg/NL1) < nr1 ? ((short)tiitg/NL1) : nr1 - 1; // 0 .. 31
|
||||
|
||||
const short il0 = (tiitg % NL0);
|
||||
|
||||
short il = il0;
|
||||
|
||||
const int i12 = im % FC_mul_mm_ne12;
|
||||
const int i13 = im / FC_mul_mm_ne12;
|
||||
|
||||
const uint64_t offset0 = (i12/FC_mul_mm_r2)*args.nb02 + (i13/FC_mul_mm_r3)*args.nb03;
|
||||
const short offset1 = il0/nl;
|
||||
|
||||
device const block_q * x = (device const block_q *)(src0 + args.nb01*(r0 + lr0) + offset0) + offset1;
|
||||
|
||||
const short iy = 8*(tiitg % NL1);
|
||||
|
||||
device const T1 * y = (device const T1 *)(src1
|
||||
+ args.nb13*i13
|
||||
+ args.nb12*i12
|
||||
+ args.nb11*(r1 + lr1)
|
||||
+ args.nb10*iy);
|
||||
|
||||
S0_8x8 ma[4];
|
||||
S1_8x8 mb[2];
|
||||
|
||||
simdgroup_float8x8 mc[8];
|
||||
|
||||
for (short i = 0; i < 8; i++){
|
||||
mc[i] = make_filled_simdgroup_matrix<float, 8>(0.f);
|
||||
}
|
||||
|
||||
for (int loop_k = 0; loop_k < args.ne00; loop_k += NK) {
|
||||
// load data and store to threadgroup memory
|
||||
if (is_same<T0_4x4, block_q>::value && FC_mul_mm_bc_inp) {
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
// no need for dequantization
|
||||
for (short i = 0; i < 16; i++) {
|
||||
const short sx = 2*il0 + i/8;
|
||||
const short sy = (tiitg/NL0)/8;
|
||||
|
||||
//const short lx = i%8;
|
||||
//const short ly = (tiitg/NL0)%8;
|
||||
const short lx = (tiitg/NL0)%8;
|
||||
const short ly = i%8;
|
||||
|
||||
const short ib = 8*sx + sy;
|
||||
|
||||
*(sa + 64*ib + 8*ly + lx) = loop_k + 16*il + i < args.ne00 ? *((device T0 *) x + i) : 0;
|
||||
}
|
||||
} else {
|
||||
S0_4x4 temp_a;
|
||||
dequantize_func(x, il, temp_a);
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
FOR_UNROLL (short i = 0; i < 16; i++) {
|
||||
const short sx = 2*il0 + i/8;
|
||||
const short sy = (tiitg/NL0)/8;
|
||||
|
||||
//const short lx = i%8;
|
||||
//const short ly = (tiitg/NL0)%8;
|
||||
const short lx = (tiitg/NL0)%8;
|
||||
const short ly = i%8;
|
||||
|
||||
const short ib = 8*sx + sy;
|
||||
|
||||
// NOTE: this is massively slower.. WTF?
|
||||
//sa[64*ib + 8*ly + lx] = temp_a[i/4][i%4];
|
||||
|
||||
*(sa + 64*ib + 8*ly + lx) = temp_a[i/4][i%4];
|
||||
}
|
||||
}
|
||||
|
||||
if (FC_mul_mm_bc_inp) {
|
||||
for (short i = 0; i < 8; ++i) {
|
||||
const short sx = (tiitg%NL1);
|
||||
const short sy = (tiitg/NL1)/8;
|
||||
|
||||
const short lx = i;
|
||||
const short ly = (tiitg/NL1)%8;
|
||||
//const short lx = (tiitg/NL1)%8;
|
||||
//const short ly = i;
|
||||
|
||||
const short ib = 4*sx + sy;
|
||||
|
||||
*(sb + 64*ib + 8*ly + lx) = loop_k + iy + i < args.ne00 ? (S1) *((device T1 *) y + i) : 0;
|
||||
}
|
||||
} else {
|
||||
const short sx = (tiitg%NL1);
|
||||
const short sy = (tiitg/NL1)/8;
|
||||
|
||||
//const short dx = sx;
|
||||
//const short dy = sy;
|
||||
|
||||
const short ly = (tiitg/NL1)%8;
|
||||
|
||||
const short ib = 4*sx + sy;
|
||||
|
||||
*(threadgroup S1_2x4 *)(sb + 64*ib + 8*ly) = (S1_2x4)(*((device T1_2x4 *) y));
|
||||
}
|
||||
|
||||
il = (il + 2 < nl) ? il + 2 : il % 2;
|
||||
x = (il < 2) ? x + (2 + nl - 1)/nl : x;
|
||||
|
||||
y += NK;
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
// load matrices from threadgroup memory and conduct outer products
|
||||
threadgroup const S0 * lsma = (sa + 4*64*(sgitg%2));
|
||||
threadgroup const S1 * lsmb = (sb + 2*64*(sgitg/2));
|
||||
|
||||
FOR_UNROLL (short ik = 0; ik < NK/8; ik++) {
|
||||
simdgroup_barrier(mem_flags::mem_none);
|
||||
|
||||
FOR_UNROLL (short i = 0; i < 4; i++) {
|
||||
simdgroup_load(ma[i], lsma + 64*i, 8, 0, false);
|
||||
}
|
||||
|
||||
simdgroup_barrier(mem_flags::mem_none);
|
||||
|
||||
FOR_UNROLL (short i = 0; i < 2; i++) {
|
||||
simdgroup_load(mb[i], lsmb + 64*i, 8, 0, false);
|
||||
}
|
||||
|
||||
simdgroup_barrier(mem_flags::mem_none);
|
||||
|
||||
FOR_UNROLL (short i = 0; i < 8; i++){
|
||||
simdgroup_multiply_accumulate(mc[i], mb[i/4], ma[i%4], mc[i]);
|
||||
}
|
||||
|
||||
lsma += 8*64;
|
||||
lsmb += 4*64;
|
||||
}
|
||||
}
|
||||
|
||||
if (!FC_mul_mm_bc_out || (r0 + NR0 <= args.ne0 && r1 + NR1 <= args.ne1)) {
|
||||
// if no bounds checks on the output are needed, we can directly write to device memory
|
||||
device float * C = (device float *) dst +
|
||||
(r0 + 32*(sgitg & 1)) + \
|
||||
(r1 + 16*(sgitg >> 1)) * args.ne0 + im*args.ne1*args.ne0;
|
||||
|
||||
for (short i = 0; i < 8; i++) {
|
||||
simdgroup_store(mc[i], C + 8*(i%4) + 8*args.ne0*(i/4), args.ne0, 0, false);
|
||||
}
|
||||
} else {
|
||||
// block is smaller than 64x32, we should avoid writing data outside of the matrix
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
threadgroup float * temp_str = ((threadgroup float *) shmem) + 32*(sgitg&1) + (16*(sgitg >> 1))*NR0;
|
||||
|
||||
for (short i = 0; i < 8; i++) {
|
||||
simdgroup_store(mc[i], temp_str + 8*(i%4) + 8*NR0*(i/4), NR0, 0, false);
|
||||
}
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
if (sgitg == 0) {
|
||||
for (int j = tiitg; j < nr1; j += NR1) {
|
||||
device float * D = (device float *) dst + r0 + (r1 + j)*args.ne0 + im*args.ne1*args.ne0;
|
||||
device float4 * D4 = (device float4 *) D;
|
||||
|
||||
threadgroup float * C = temp_str + (j*NR0);
|
||||
threadgroup float4 * C4 = (threadgroup float4 *) C;
|
||||
|
||||
int i = 0;
|
||||
for (; i < nr0/4; i++) {
|
||||
*(D4 + i) = *(C4 + i);
|
||||
}
|
||||
|
||||
i *= 4;
|
||||
for (; i < nr0; i++) {
|
||||
*(D + i) = *(C + i);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
#endif // GGML_METAL_HAS_TENSOR
|
||||
|
||||
template<short ne20> // n_expert_used
|
||||
kernel void kernel_mul_mm_id_map0(
|
||||
constant ggml_metal_kargs_mul_mm_id_map0 & args,
|
||||
device const char * src2,
|
||||
device char * htpe,
|
||||
device char * hids,
|
||||
threadgroup char * shmem [[threadgroup(0)]],
|
||||
ushort tpitg[[thread_position_in_threadgroup]],
|
||||
ushort ntg[[threads_per_threadgroup]]) {
|
||||
const short ide = tpitg; // expert id
|
||||
|
||||
uint32_t n_all = 0;
|
||||
|
||||
device int32_t * ids_i32 = (device int32_t *) hids + ide*args.ne21;
|
||||
|
||||
for (int i21 = 0; i21 < args.ne21; i21 += ntg) { // n_tokens
|
||||
if (i21 + tpitg < args.ne21) {
|
||||
device const int32_t * src2_i32 = (device const int32_t *) (src2 + (i21 + tpitg)*args.nb21);
|
||||
|
||||
threadgroup uint16_t * sids = (threadgroup uint16_t *) shmem + tpitg*ne20;
|
||||
|
||||
#pragma unroll(ne20)
|
||||
for (short i20 = 0; i20 < ne20; i20++) {
|
||||
sids[i20] = src2_i32[i20];
|
||||
}
|
||||
}
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
for (short t = 0; t < ntg; t++) {
|
||||
if (i21 + t >= args.ne21) {
|
||||
break;
|
||||
}
|
||||
|
||||
threadgroup const uint16_t * sids = (threadgroup const uint16_t *) shmem + t*ne20;
|
||||
|
||||
short sel = 0;
|
||||
#pragma unroll(ne20)
|
||||
for (short i20 = 0; i20 < ne20; i20++) {
|
||||
sel += (sids[i20] == ide)*(i20 + 1);
|
||||
}
|
||||
|
||||
ids_i32[n_all] = (i21 + t)*ne20 + sel - 1;
|
||||
|
||||
n_all += sel > 0;
|
||||
}
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
}
|
||||
|
||||
device uint32_t * tpe_u32 = (device uint32_t *) (htpe);
|
||||
tpe_u32[ide] = n_all;
|
||||
}
|
||||
|
||||
typedef decltype(kernel_mul_mm_id_map0<1>) kernel_mul_mm_id_map0_t;
|
||||
|
||||
template [[host_name("kernel_mul_mm_id_map0_ne20_1" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<1>;
|
||||
template [[host_name("kernel_mul_mm_id_map0_ne20_2" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<2>;
|
||||
template [[host_name("kernel_mul_mm_id_map0_ne20_4" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<4>;
|
||||
template [[host_name("kernel_mul_mm_id_map0_ne20_5" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<5>;
|
||||
template [[host_name("kernel_mul_mm_id_map0_ne20_6" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<6>;
|
||||
template [[host_name("kernel_mul_mm_id_map0_ne20_8" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<8>;
|
||||
template [[host_name("kernel_mul_mm_id_map0_ne20_10")]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<10>;
|
||||
template [[host_name("kernel_mul_mm_id_map0_ne20_16")]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<16>;
|
||||
template [[host_name("kernel_mul_mm_id_map0_ne20_22")]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<22>;
|
||||
|
||||
template<typename S0, typename S0_4x4, typename S0_8x8, typename S1, typename S1_2x4, typename S1_8x8, typename block_q, short nl, void (*dequantize_func)(device const block_q *, short, thread S0_4x4 &), typename T0, typename T0_4x4, typename T1, typename T1_2x4>
|
||||
kernel void kernel_mul_mm_id(
|
||||
constant ggml_metal_kargs_mul_mm_id & args,
|
||||
device const char * src0,
|
||||
device const char * src1,
|
||||
device const char * htpe,
|
||||
device const char * hids,
|
||||
device char * dst,
|
||||
threadgroup char * shmem [[threadgroup(0)]],
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
ushort tiitg[[thread_index_in_threadgroup]],
|
||||
ushort tiisg[[thread_index_in_simdgroup]],
|
||||
ushort sgitg[[simdgroup_index_in_threadgroup]]) {
|
||||
threadgroup S0 * sa = (threadgroup S0 *)(shmem);
|
||||
threadgroup S1 * sb = (threadgroup S1 *)(shmem + 4096);
|
||||
|
||||
#ifdef GGML_METAL_HAS_TENSOR
|
||||
threadgroup float * sc = (threadgroup float *)(shmem);
|
||||
#endif
|
||||
|
||||
constexpr int NR0 = 64;
|
||||
constexpr int NR1 = 32;
|
||||
|
||||
constexpr int NK = 32;
|
||||
constexpr int NL0 = NK/16;
|
||||
constexpr int NL1 = NK/8;
|
||||
|
||||
const int im = tgpig.z; // expert
|
||||
const int r0 = tgpig.y*NR0;
|
||||
const int r1 = tgpig.x*NR1;
|
||||
|
||||
device const uint32_t * tpe_u32 = (device const uint32_t *) (htpe);
|
||||
device const int32_t * ids_i32 = (device const int32_t *) (hids);
|
||||
|
||||
const int32_t neh1 = tpe_u32[im];
|
||||
|
||||
if (r1 >= neh1) {
|
||||
return;
|
||||
}
|
||||
|
||||
// if this block is of 64x32 shape or smaller
|
||||
const short nr0 = (args.ne0 - r0 < NR0) ? (args.ne0 - r0) : NR0;
|
||||
const short nr1 = ( neh1 - r1 < NR1) ? ( neh1 - r1) : NR1;
|
||||
|
||||
// a thread shouldn't load data outside of the matrix
|
||||
const short lr0 = ((short)tiitg/NL0) < nr0 ? ((short)tiitg/NL0) : nr0 - 1; // 0 .. 63
|
||||
const short lr1 = ((short)tiitg/NL1) < nr1 ? ((short)tiitg/NL1) : nr1 - 1; // 0 .. 31
|
||||
|
||||
const short il0 = (tiitg % NL0);
|
||||
|
||||
short il = il0;
|
||||
|
||||
const int id = ids_i32[im*args.ne21 + r1 + lr1];
|
||||
|
||||
const short i11 = (id % args.ne20) % args.ne11;
|
||||
const short i12 = (id / args.ne20);
|
||||
const short i13 = 0;
|
||||
|
||||
const uint64_t offset0 = im*args.nb02 + i13*args.nb03;
|
||||
const short offset1 = il0/nl;
|
||||
|
||||
device const block_q * x = (device const block_q *)(src0 + args.nb01*(r0 + lr0) + offset0) + offset1;
|
||||
|
||||
const short iy = 8*(tiitg % NL1);
|
||||
|
||||
device const T1 * y = (device const T1 *)(src1
|
||||
+ args.nb13*i13
|
||||
+ args.nb12*i12
|
||||
+ args.nb11*i11
|
||||
+ args.nb10*iy);
|
||||
|
||||
#ifndef GGML_METAL_HAS_TENSOR
|
||||
S0_8x8 ma[4];
|
||||
S1_8x8 mb[2];
|
||||
|
||||
simdgroup_float8x8 mc[8];
|
||||
|
||||
for (short i = 0; i < 8; i++){
|
||||
mc[i] = make_filled_simdgroup_matrix<float, 8>(0.f);
|
||||
}
|
||||
#else
|
||||
auto tA = tensor<threadgroup S0, dextents<int32_t, 2>, tensor_inline>(sa, dextents<int32_t, 2>(NK, NR0));
|
||||
auto tB = tensor<threadgroup S1, dextents<int32_t, 2>, tensor_inline>(sb, dextents<int32_t, 2>(NR1, NK ));
|
||||
|
||||
mpp::tensor_ops::matmul2d<
|
||||
mpp::tensor_ops::matmul2d_descriptor(NR1, NR0, NK, false, true, false, mpp::tensor_ops::matmul2d_descriptor::mode::multiply_accumulate),
|
||||
execution_simdgroups<4>> mm;
|
||||
|
||||
auto cT = mm.get_destination_cooperative_tensor<decltype(tA), decltype(tB), float>();
|
||||
#endif
|
||||
|
||||
for (int loop_k = 0; loop_k < args.ne00; loop_k += NK) {
|
||||
#ifndef GGML_METAL_HAS_TENSOR
|
||||
// load data and store to threadgroup memory
|
||||
if (is_same<T0_4x4, block_q>::value && FC_mul_mm_bc_inp) {
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
// no need for dequantization
|
||||
for (short i = 0; i < 16; i++) {
|
||||
const short sx = 2*il0 + i/8;
|
||||
const short sy = (tiitg/NL0)/8;
|
||||
|
||||
//const short lx = i%8;
|
||||
//const short ly = (tiitg/NL0)%8;
|
||||
const short lx = (tiitg/NL0)%8;
|
||||
const short ly = i%8;
|
||||
|
||||
const short ib = 8*sx + sy;
|
||||
|
||||
*(sa + 64*ib + 8*ly + lx) = loop_k + 16*il + i < args.ne00 ? (S0) *((device T0 *) x + i) : (S0) 0;
|
||||
}
|
||||
} else {
|
||||
S0_4x4 temp_a;
|
||||
dequantize_func(x, il, temp_a);
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
FOR_UNROLL (short i = 0; i < 16; i++) {
|
||||
const short sx = 2*il0 + i/8;
|
||||
const short sy = (tiitg/NL0)/8;
|
||||
|
||||
//const short lx = i%8;
|
||||
//const short ly = (tiitg/NL0)%8;
|
||||
const short lx = (tiitg/NL0)%8;
|
||||
const short ly = i%8;
|
||||
|
||||
const short ib = 8*sx + sy;
|
||||
|
||||
// NOTE: this is massively slower.. WTF?
|
||||
//sa[64*ib + 8*ly + lx] = temp_a[i/4][i%4];
|
||||
|
||||
*(sa + 64*ib + 8*ly + lx) = temp_a[i/4][i%4];
|
||||
}
|
||||
}
|
||||
|
||||
if (FC_mul_mm_bc_inp) {
|
||||
for (short i = 0; i < 8; ++i) {
|
||||
const short sx = (tiitg%NL1);
|
||||
const short sy = (tiitg/NL1)/8;
|
||||
|
||||
const short lx = i;
|
||||
const short ly = (tiitg/NL1)%8;
|
||||
//const short lx = (tiitg/NL1)%8;
|
||||
//const short ly = i;
|
||||
|
||||
const short ib = 4*sx + sy;
|
||||
|
||||
*(sb + 64*ib + 8*ly + lx) = loop_k + iy + i < args.ne00 ? (S1) *((device T1 *) y + i) : 0;
|
||||
}
|
||||
} else {
|
||||
const short sx = (tiitg%NL1);
|
||||
const short sy = (tiitg/NL1)/8;
|
||||
|
||||
//const short dx = sx;
|
||||
//const short dy = sy;
|
||||
|
||||
const short ly = (tiitg/NL1)%8;
|
||||
|
||||
const short ib = 4*sx + sy;
|
||||
|
||||
*(threadgroup S1_2x4 *)(sb + 64*ib + 8*ly) = (S1_2x4)(*((device T1_2x4 *) y));
|
||||
}
|
||||
#else
|
||||
// load data and store to threadgroup memory
|
||||
if (is_same<T0_4x4, block_q>::value && FC_mul_mm_bc_inp) {
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
// no need for dequantization
|
||||
for (short i = 0; i < 16; i++) {
|
||||
const short sx = 2*il0 + i/8;
|
||||
const short sy = (tiitg/NL0)/8;
|
||||
|
||||
const short lx = i%8;
|
||||
const short ly = (tiitg/NL0)%8;
|
||||
//const short lx = (tiitg/NL0)%8;
|
||||
//const short ly = i%8;
|
||||
|
||||
*(sa + NK*(8*sy + ly) + 8*sx + lx) = loop_k + 16*il + i < args.ne00 ? *((device T0 *) x + i) : 0;
|
||||
}
|
||||
} else {
|
||||
S0_4x4 temp_a;
|
||||
dequantize_func(x, il, temp_a);
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
FOR_UNROLL (short i = 0; i < 16; i++) {
|
||||
const short sx = 2*il0 + i/8;
|
||||
const short sy = (tiitg/NL0)/8;
|
||||
|
||||
const short lx = i%8;
|
||||
const short ly = (tiitg/NL0)%8;
|
||||
//const short lx = (tiitg/NL0)%8;
|
||||
//const short ly = i%8;
|
||||
|
||||
*(sa + NK*(8*sy + ly) + 8*sx + lx) = temp_a[i/4][i%4];
|
||||
}
|
||||
}
|
||||
|
||||
if (FC_mul_mm_bc_inp) {
|
||||
for (short i = 0; i < 8; ++i) {
|
||||
const short sx = (tiitg%NL1);
|
||||
const short sy = (tiitg/NL1)/8;
|
||||
|
||||
const short lx = i;
|
||||
const short ly = (tiitg/NL1)%8;
|
||||
//const short lx = (tiitg/NL1)%8;
|
||||
//const short ly = i;
|
||||
|
||||
*(sb + NK*(8*sy + ly) + 8*sx + lx) = loop_k + iy + i < args.ne00 ? (S1) *((device T1 *) y + i) : 0;
|
||||
}
|
||||
} else {
|
||||
const short sx = (tiitg%NL1);
|
||||
const short sy = (tiitg/NL1)/8;
|
||||
|
||||
//const short lx = i;
|
||||
const short ly = (tiitg/NL1)%8;
|
||||
//const short lx = (tiitg/NL1)%8;
|
||||
//const short ly = i;
|
||||
|
||||
*(threadgroup S1_2x4 *)(sb + NK*(8*sy + ly) + 8*sx) = (S1_2x4)(*((device T1_2x4 *) y));
|
||||
}
|
||||
#endif
|
||||
|
||||
il = (il + 2 < nl) ? il + 2 : il % 2;
|
||||
x = (il < 2) ? x + (2 + nl - 1)/nl : x;
|
||||
|
||||
y += NK;
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
#ifndef GGML_METAL_HAS_TENSOR
|
||||
// load matrices from threadgroup memory and conduct outer products
|
||||
threadgroup const S0 * lsma = (sa + 4*64*(sgitg%2));
|
||||
threadgroup const S1 * lsmb = (sb + 2*64*(sgitg/2));
|
||||
|
||||
FOR_UNROLL (short ik = 0; ik < NK/8; ik++) {
|
||||
simdgroup_barrier(mem_flags::mem_none);
|
||||
|
||||
FOR_UNROLL (short i = 0; i < 4; i++) {
|
||||
simdgroup_load(ma[i], lsma + 64*i, 8, 0, false);
|
||||
}
|
||||
|
||||
simdgroup_barrier(mem_flags::mem_none);
|
||||
|
||||
FOR_UNROLL (short i = 0; i < 2; i++) {
|
||||
simdgroup_load(mb[i], lsmb + 64*i, 8, 0, false);
|
||||
}
|
||||
|
||||
simdgroup_barrier(mem_flags::mem_none);
|
||||
|
||||
FOR_UNROLL (short i = 0; i < 8; i++){
|
||||
simdgroup_multiply_accumulate(mc[i], mb[i/4], ma[i%4], mc[i]);
|
||||
}
|
||||
|
||||
lsma += 8*64;
|
||||
lsmb += 4*64;
|
||||
}
|
||||
#else
|
||||
auto sA = tA.slice(0, 0);
|
||||
auto sB = tB.slice(0, 0);
|
||||
|
||||
mm.run(sB, sA, cT);
|
||||
#endif
|
||||
}
|
||||
|
||||
// block is smaller than 64x32, we should avoid writing data outside of the matrix
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
#ifdef GGML_METAL_HAS_TENSOR
|
||||
auto tC = tensor<threadgroup float, dextents<int32_t, 2>, tensor_inline>(sc, dextents<int32_t, 2>(NR0, NR1));
|
||||
cT.store(tC);
|
||||
#else
|
||||
threadgroup float * temp_str = ((threadgroup float *) shmem) + 32*(sgitg&1) + (16*(sgitg >> 1))*NR0;
|
||||
|
||||
for (short i = 0; i < 8; i++) {
|
||||
simdgroup_store(mc[i], temp_str + 8*(i%4) + 8*NR0*(i/4), NR0, 0, false);
|
||||
}
|
||||
#endif
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
for (short j = sgitg; j < nr1; j += 4) {
|
||||
const int id = ids_i32[im*args.ne21 + r1 + j];
|
||||
|
||||
const short ide = id % args.ne20;
|
||||
const short idt = id / args.ne20;
|
||||
|
||||
device float * D = (device float *) dst + r0 + ide*args.ne0 + idt*args.ne1*args.ne0;
|
||||
device float4 * D4 = (device float4 *) D;
|
||||
|
||||
threadgroup float * C = (threadgroup float *) shmem + j*NR0;
|
||||
threadgroup float4 * C4 = (threadgroup float4 *) C;
|
||||
|
||||
int i = tiisg;
|
||||
for (; i < nr0/4; i += 32) {
|
||||
*(D4 + i) = *(C4 + i);
|
||||
}
|
||||
|
||||
i = (4*(nr0/4)) + tiisg;
|
||||
for (; i < nr0; i += 32) {
|
||||
*(D + i) = *(C + i);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
//
|
||||
// matrix-matrix multiplication
|
||||
//
|
||||
|
||||
typedef decltype(kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, float4x4, 1, dequantize_f32, float, float4x4, float, float2x4>) mul_mm_t;
|
||||
|
||||
template [[host_name("kernel_mul_mm_f32_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, float4x4, 1, dequantize_f32, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_f16_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, half4x4, 1, dequantize_f16, half, half4x4, float, float2x4>;
|
||||
#if defined(GGML_METAL_HAS_BF16)
|
||||
template [[host_name("kernel_mul_mm_bf16_f32")]] kernel mul_mm_t kernel_mul_mm<bfloat, bfloat4x4, simdgroup_bfloat8x8, bfloat, bfloat2x4, simdgroup_bfloat8x8, bfloat4x4, 1, dequantize_bf16, bfloat, bfloat4x4, float, float2x4>;
|
||||
#endif
|
||||
template [[host_name("kernel_mul_mm_q1_0_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q1_0, 8, dequantize_q1_0, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_q4_0_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q4_0, 2, dequantize_q4_0, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_q4_1_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q4_1, 2, dequantize_q4_1, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_q5_0_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q5_0, 2, dequantize_q5_0, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_q5_1_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q5_1, 2, dequantize_q5_1, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_q8_0_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q8_0, 2, dequantize_q8_0, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_mxfp4_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_mxfp4, 2, dequantize_mxfp4, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_q2_K_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q2_K, QK_NL, dequantize_q2_K, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_q3_K_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q3_K, QK_NL, dequantize_q3_K, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_q4_K_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q4_K, QK_NL, dequantize_q4_K, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_q5_K_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q5_K, QK_NL, dequantize_q5_K, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_q6_K_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q6_K, QK_NL, dequantize_q6_K, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_iq2_xxs_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq2_xxs, QK_NL, dequantize_iq2_xxs, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_iq2_xs_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq2_xs, QK_NL, dequantize_iq2_xs, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_iq3_xxs_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq3_xxs, QK_NL, dequantize_iq3_xxs, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_iq3_s_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq3_s, QK_NL, dequantize_iq3_s, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_iq2_s_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq2_s, QK_NL, dequantize_iq2_s, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_iq1_s_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq1_s, QK_NL, dequantize_iq1_s, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_iq1_m_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq1_m, QK_NL, dequantize_iq1_m, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_iq4_nl_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq4_nl, 2, dequantize_iq4_nl, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_iq4_xs_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq4_xs, QK_NL, dequantize_iq4_xs, float, float4x4, float, float2x4>;
|
||||
|
||||
template [[host_name("kernel_mul_mm_f32_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, float4x4, 1, dequantize_f32, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_f16_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, half4x4, 1, dequantize_f16, half, half4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_q1_0_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q1_0, 8, dequantize_q1_0, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_q4_0_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q4_0, 2, dequantize_q4_0, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_q4_1_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q4_1, 2, dequantize_q4_1, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_q5_0_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q5_0, 2, dequantize_q5_0, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_q5_1_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q5_1, 2, dequantize_q5_1, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_q8_0_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q8_0, 2, dequantize_q8_0, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_mxfp4_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_mxfp4, 2, dequantize_mxfp4, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_q2_K_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q2_K, QK_NL, dequantize_q2_K, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_q3_K_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q3_K, QK_NL, dequantize_q3_K, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_q4_K_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q4_K, QK_NL, dequantize_q4_K, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_q5_K_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q5_K, QK_NL, dequantize_q5_K, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_q6_K_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q6_K, QK_NL, dequantize_q6_K, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_iq2_xxs_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq2_xxs, QK_NL, dequantize_iq2_xxs, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_iq2_xs_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq2_xs, QK_NL, dequantize_iq2_xs, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_iq3_xxs_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq3_xxs, QK_NL, dequantize_iq3_xxs, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_iq3_s_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq3_s, QK_NL, dequantize_iq3_s, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_iq2_s_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq2_s, QK_NL, dequantize_iq2_s, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_iq1_s_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq1_s, QK_NL, dequantize_iq1_s, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_iq1_m_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq1_m, QK_NL, dequantize_iq1_m, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_iq4_nl_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq4_nl, 2, dequantize_iq4_nl, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_iq4_xs_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq4_xs, QK_NL, dequantize_iq4_xs, float, float4x4, half, half2x4>;
|
||||
|
||||
//
|
||||
// indirect matrix-matrix multiplication
|
||||
//
|
||||
|
||||
typedef decltype(kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, float4x4, 1, dequantize_f32, float, float4x4, float, float2x4>) mul_mm_id;
|
||||
|
||||
template [[host_name("kernel_mul_mm_id_f32_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, float4x4, 1, dequantize_f32, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_f16_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, half4x4, 1, dequantize_f16, half, half4x4, float, float2x4>;
|
||||
#if defined(GGML_METAL_HAS_BF16)
|
||||
template [[host_name("kernel_mul_mm_id_bf16_f32")]] kernel mul_mm_id kernel_mul_mm_id<bfloat, bfloat4x4, simdgroup_bfloat8x8, bfloat, bfloat2x4, simdgroup_bfloat8x8, bfloat4x4, 1, dequantize_bf16, bfloat, bfloat4x4, float, float2x4>;
|
||||
#endif
|
||||
template [[host_name("kernel_mul_mm_id_q1_0_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q1_0, 8, dequantize_q1_0, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_q4_0_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q4_0, 2, dequantize_q4_0, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_q4_1_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q4_1, 2, dequantize_q4_1, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_q5_0_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q5_0, 2, dequantize_q5_0, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_q5_1_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q5_1, 2, dequantize_q5_1, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_q8_0_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q8_0, 2, dequantize_q8_0, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_mxfp4_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_mxfp4, 2, dequantize_mxfp4, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_q2_K_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q2_K, QK_NL, dequantize_q2_K, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_q3_K_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q3_K, QK_NL, dequantize_q3_K, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_q4_K_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q4_K, QK_NL, dequantize_q4_K, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_q5_K_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q5_K, QK_NL, dequantize_q5_K, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_q6_K_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q6_K, QK_NL, dequantize_q6_K, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_iq2_xxs_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq2_xxs, QK_NL, dequantize_iq2_xxs, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_iq2_xs_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq2_xs, QK_NL, dequantize_iq2_xs, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_iq3_xxs_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq3_xxs, QK_NL, dequantize_iq3_xxs, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_iq3_s_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq3_s, QK_NL, dequantize_iq3_s, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_iq2_s_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq2_s, QK_NL, dequantize_iq2_s, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_iq1_s_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq1_s, QK_NL, dequantize_iq1_s, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_iq1_m_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq1_m, QK_NL, dequantize_iq1_m, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_iq4_nl_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq4_nl, 2, dequantize_iq4_nl, float, float4x4, float, float2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_iq4_xs_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq4_xs, QK_NL, dequantize_iq4_xs, float, float4x4, float, float2x4>;
|
||||
|
||||
template [[host_name("kernel_mul_mm_id_f32_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, float4x4, 1, dequantize_f32, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_f16_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, half4x4, 1, dequantize_f16, half, half4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_q1_0_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q1_0, 8, dequantize_q1_0, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_q4_0_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q4_0, 2, dequantize_q4_0, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_q4_1_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q4_1, 2, dequantize_q4_1, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_q5_0_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q5_0, 2, dequantize_q5_0, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_q5_1_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q5_1, 2, dequantize_q5_1, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_q8_0_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q8_0, 2, dequantize_q8_0, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_mxfp4_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_mxfp4, 2, dequantize_mxfp4, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_q2_K_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q2_K, QK_NL, dequantize_q2_K, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_q3_K_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q3_K, QK_NL, dequantize_q3_K, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_q4_K_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q4_K, QK_NL, dequantize_q4_K, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_q5_K_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q5_K, QK_NL, dequantize_q5_K, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_q6_K_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q6_K, QK_NL, dequantize_q6_K, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_iq2_xxs_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq2_xxs, QK_NL, dequantize_iq2_xxs, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_iq2_xs_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq2_xs, QK_NL, dequantize_iq2_xs, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_iq3_xxs_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq3_xxs, QK_NL, dequantize_iq3_xxs, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_iq3_s_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq3_s, QK_NL, dequantize_iq3_s, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_iq2_s_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq2_s, QK_NL, dequantize_iq2_s, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_iq1_s_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq1_s, QK_NL, dequantize_iq1_s, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_iq1_m_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq1_m, QK_NL, dequantize_iq1_m, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_iq4_nl_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq4_nl, 2, dequantize_iq4_nl, float, float4x4, half, half2x4>;
|
||||
template [[host_name("kernel_mul_mm_id_iq4_xs_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq4_xs, QK_NL, dequantize_iq4_xs, float, float4x4, half, half2x4>;
|
||||
File diff suppressed because it is too large
Load Diff
@@ -0,0 +1,308 @@
|
||||
#include "common.h"
|
||||
|
||||
// F == 1 : norm (no fuse)
|
||||
// F == 2 : norm + mul
|
||||
// F == 3 : norm + mul + add
|
||||
template <typename T, short F>
|
||||
kernel void kernel_norm_fuse_impl(
|
||||
constant ggml_metal_kargs_norm & args,
|
||||
device const char * src0,
|
||||
device const char * src1_0,
|
||||
device const char * src1_1,
|
||||
device char * dst,
|
||||
threadgroup float * shmem_f32 [[threadgroup(0)]],
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
ushort3 tpitg[[thread_position_in_threadgroup]],
|
||||
ushort sgitg[[simdgroup_index_in_threadgroup]],
|
||||
ushort tiisg[[thread_index_in_simdgroup]],
|
||||
ushort3 ntg[[threads_per_threadgroup]]) {
|
||||
if (sgitg == 0) {
|
||||
shmem_f32[tiisg] = 0.0f;
|
||||
}
|
||||
|
||||
const int i01 = tgpig.x;
|
||||
const int i02 = tgpig.y;
|
||||
const int i03 = tgpig.z;
|
||||
|
||||
device const T * x = (device const T *) (src0 + i03*args.nbf3[0] + i02*args.nbf2[0] + i01*args.nbf1[0]);
|
||||
|
||||
device const T * f0 = (device const T *) (src1_0 + (i03%args.nef3[1])*args.nbf3[1] + (i02%args.nef2[1])*args.nbf2[1] + (i01%args.nef1[1])*args.nbf1[1]);
|
||||
device const T * f1 = (device const T *) (src1_1 + (i03%args.nef3[2])*args.nbf3[2] + (i02%args.nef2[2])*args.nbf2[2] + (i01%args.nef1[2])*args.nbf1[2]);
|
||||
|
||||
T sumft(0.0f);
|
||||
|
||||
float sumf = 0.0f;
|
||||
|
||||
for (int i00 = tpitg.x; i00 < args.ne00_t; i00 += ntg.x) {
|
||||
sumft += x[i00];
|
||||
}
|
||||
sumf = dot(sumft, T(1.0f));
|
||||
sumf = simd_sum(sumf);
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
if (tiisg == 0) {
|
||||
shmem_f32[sgitg] = sumf;
|
||||
}
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
sumf = shmem_f32[tiisg];
|
||||
sumf = simd_sum(sumf);
|
||||
|
||||
const float mean = sumf/args.ne00;
|
||||
|
||||
device T * y = (device T *) (dst + i03*args.nb3 + i02*args.nb2 + i01*args.nb1);
|
||||
|
||||
sumf = 0.0f;
|
||||
for (int i00 = tpitg.x; i00 < args.ne00_t; i00 += ntg.x) {
|
||||
y[i00] = x[i00] - mean;
|
||||
sumf += dot(y[i00], y[i00]);
|
||||
}
|
||||
sumf = simd_sum(sumf);
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
if (tiisg == 0) {
|
||||
shmem_f32[sgitg] = sumf;
|
||||
}
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
sumf = shmem_f32[tiisg];
|
||||
sumf = simd_sum(sumf);
|
||||
|
||||
const float variance = sumf/args.ne00;
|
||||
|
||||
const float scale = 1.0f/sqrt(variance + args.eps);
|
||||
for (int i00 = tpitg.x; i00 < args.ne00_t; i00 += ntg.x) {
|
||||
if (F == 1) {
|
||||
y[i00] = (y[i00]*scale);
|
||||
}
|
||||
if (F == 2) {
|
||||
y[i00] = (y[i00]*scale)*f0[i00];
|
||||
}
|
||||
if (F == 3) {
|
||||
y[i00] = (y[i00]*scale)*f0[i00] + f1[i00];
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
typedef decltype(kernel_norm_fuse_impl<float4, 1>) kernel_norm_fuse_t;
|
||||
|
||||
template [[host_name("kernel_norm_f32")]] kernel kernel_norm_fuse_t kernel_norm_fuse_impl<float, 1>;
|
||||
template [[host_name("kernel_norm_mul_f32")]] kernel kernel_norm_fuse_t kernel_norm_fuse_impl<float, 2>;
|
||||
template [[host_name("kernel_norm_mul_add_f32")]] kernel kernel_norm_fuse_t kernel_norm_fuse_impl<float, 3>;
|
||||
|
||||
template [[host_name("kernel_norm_f32_4")]] kernel kernel_norm_fuse_t kernel_norm_fuse_impl<float4, 1>;
|
||||
template [[host_name("kernel_norm_mul_f32_4")]] kernel kernel_norm_fuse_t kernel_norm_fuse_impl<float4, 2>;
|
||||
template [[host_name("kernel_norm_mul_add_f32_4")]] kernel kernel_norm_fuse_t kernel_norm_fuse_impl<float4, 3>;
|
||||
|
||||
// F == 1 : rms_norm (no fuse)
|
||||
// F == 2 : rms_norm + mul
|
||||
// F == 3 : rms_norm + mul + add
|
||||
template <typename T, short F>
|
||||
kernel void kernel_rms_norm_fuse_impl(
|
||||
constant ggml_metal_kargs_norm & args,
|
||||
device const char * src0,
|
||||
device const char * src1_0,
|
||||
device const char * src1_1,
|
||||
device char * dst,
|
||||
threadgroup float * shmem_f32 [[threadgroup(0)]],
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
ushort3 tpitg[[thread_position_in_threadgroup]],
|
||||
ushort sgitg[[simdgroup_index_in_threadgroup]],
|
||||
ushort tiisg[[thread_index_in_simdgroup]],
|
||||
ushort3 ntg[[threads_per_threadgroup]]) {
|
||||
if (sgitg == 0) {
|
||||
shmem_f32[tiisg] = 0.0f;
|
||||
}
|
||||
|
||||
const int i01 = tgpig.x;
|
||||
const int i02 = tgpig.y;
|
||||
const int i03 = tgpig.z;
|
||||
|
||||
device const T * x = (device const T *) (src0 + i03*args.nbf3[0] + i02*args.nbf2[0] + i01*args.nbf1[0]);
|
||||
|
||||
device const T * f0 = (device const T *) (src1_0 + (i03%args.nef3[1])*args.nbf3[1] + (i02%args.nef2[1])*args.nbf2[1] + (i01%args.nef1[1])*args.nbf1[1]);
|
||||
device const T * f1 = (device const T *) (src1_1 + (i03%args.nef3[2])*args.nbf3[2] + (i02%args.nef2[2])*args.nbf2[2] + (i01%args.nef1[2])*args.nbf1[2]);
|
||||
|
||||
float sumf = 0.0f;
|
||||
|
||||
// parallel sum
|
||||
for (int i00 = tpitg.x; i00 < args.ne00_t; i00 += ntg.x) {
|
||||
sumf += dot(x[i00], x[i00]);
|
||||
}
|
||||
sumf = simd_sum(sumf);
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
if (tiisg == 0) {
|
||||
shmem_f32[sgitg] = sumf;
|
||||
}
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
sumf = shmem_f32[tiisg];
|
||||
sumf = simd_sum(sumf);
|
||||
|
||||
const float mean = sumf/args.ne00;
|
||||
const float scale = 1.0f/sqrt(mean + args.eps);
|
||||
|
||||
device T * y = (device T *) (dst + i03*args.nb3 + i02*args.nb2 + i01*args.nb1);
|
||||
for (int i00 = tpitg.x; i00 < args.ne00_t; i00 += ntg.x) {
|
||||
if (F == 1) {
|
||||
y[i00] = (x[i00]*scale);
|
||||
}
|
||||
if (F == 2) {
|
||||
y[i00] = (x[i00]*scale)*f0[i00];
|
||||
}
|
||||
if (F == 3) {
|
||||
y[i00] = (x[i00]*scale)*f0[i00] + f1[i00];
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
typedef decltype(kernel_rms_norm_fuse_impl<float4, 1>) kernel_rms_norm_fuse_t;
|
||||
|
||||
template [[host_name("kernel_rms_norm_f32")]] kernel kernel_rms_norm_fuse_t kernel_rms_norm_fuse_impl<float, 1>;
|
||||
template [[host_name("kernel_rms_norm_mul_f32")]] kernel kernel_rms_norm_fuse_t kernel_rms_norm_fuse_impl<float, 2>;
|
||||
template [[host_name("kernel_rms_norm_mul_add_f32")]] kernel kernel_rms_norm_fuse_t kernel_rms_norm_fuse_impl<float, 3>;
|
||||
|
||||
template [[host_name("kernel_rms_norm_f32_4")]] kernel kernel_rms_norm_fuse_t kernel_rms_norm_fuse_impl<float4, 1>;
|
||||
template [[host_name("kernel_rms_norm_mul_f32_4")]] kernel kernel_rms_norm_fuse_t kernel_rms_norm_fuse_impl<float4, 2>;
|
||||
template [[host_name("kernel_rms_norm_mul_add_f32_4")]] kernel kernel_rms_norm_fuse_t kernel_rms_norm_fuse_impl<float4, 3>;
|
||||
|
||||
template <typename T0, typename T>
|
||||
kernel void kernel_l2_norm_impl(
|
||||
constant ggml_metal_kargs_l2_norm & args,
|
||||
device const char * src0,
|
||||
device char * dst,
|
||||
threadgroup float * shmem_f32 [[threadgroup(0)]],
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
ushort3 tpitg[[thread_position_in_threadgroup]],
|
||||
ushort sgitg[[simdgroup_index_in_threadgroup]],
|
||||
ushort tiisg[[thread_index_in_simdgroup]],
|
||||
ushort3 ntg[[threads_per_threadgroup]]) {
|
||||
const int i03 = tgpig.z;
|
||||
const int i02 = tgpig.y;
|
||||
const int i01 = tgpig.x;
|
||||
|
||||
if (sgitg == 0) {
|
||||
shmem_f32[tiisg] = 0.0f;
|
||||
}
|
||||
|
||||
device const T0 * x = (device const T0 *) (src0 + i03*args.nb03 + i02*args.nb02 + i01*args.nb01);
|
||||
device T * y = (device T *) (dst + i03*args.nb3 + i02*args.nb2 + i01*args.nb1);
|
||||
|
||||
float sumf = 0.0f;
|
||||
|
||||
// parallel sum
|
||||
for (int i00 = tpitg.x; i00 < args.ne00; i00 += ntg.x) {
|
||||
sumf += dot(x[i00], x[i00]);
|
||||
}
|
||||
sumf = simd_sum(sumf);
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
if (tiisg == 0) {
|
||||
shmem_f32[sgitg] = sumf;
|
||||
}
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
sumf = shmem_f32[tiisg];
|
||||
sumf = simd_sum(sumf);
|
||||
|
||||
const float scale = 1.0f/max(sqrt(sumf), args.eps);
|
||||
|
||||
for (int i00 = tpitg.x; i00 < args.ne00; i00 += ntg.x) {
|
||||
y[i00] = x[i00] * scale;
|
||||
}
|
||||
}
|
||||
|
||||
typedef decltype(kernel_l2_norm_impl<float, float>) kernel_l2_norm_t;
|
||||
|
||||
template [[host_name("kernel_l2_norm_f32_f32")]] kernel kernel_l2_norm_t kernel_l2_norm_impl<float, float>;
|
||||
template [[host_name("kernel_l2_norm_f32_f32_4")]] kernel kernel_l2_norm_t kernel_l2_norm_impl<float4, float4>;
|
||||
|
||||
kernel void kernel_group_norm_f32(
|
||||
constant ggml_metal_kargs_group_norm & args,
|
||||
device const float * src0,
|
||||
device float * dst,
|
||||
threadgroup float * buf [[threadgroup(0)]],
|
||||
uint tgpig[[threadgroup_position_in_grid]],
|
||||
uint tpitg[[thread_position_in_threadgroup]],
|
||||
uint sgitg[[simdgroup_index_in_threadgroup]],
|
||||
uint tiisg[[thread_index_in_simdgroup]],
|
||||
uint ntg[[threads_per_threadgroup]]) {
|
||||
const int64_t ne = args.ne00*args.ne01*args.ne02;
|
||||
const int64_t gs = args.ne00*args.ne01*((args.ne02 + args.ngrp - 1) / args.ngrp);
|
||||
|
||||
int start = tgpig * gs;
|
||||
int end = start + gs;
|
||||
|
||||
start += tpitg;
|
||||
|
||||
if (end >= ne) {
|
||||
end = ne;
|
||||
}
|
||||
|
||||
float tmp = 0.0f; // partial sum for thread in warp
|
||||
|
||||
for (int j = start; j < end; j += ntg) {
|
||||
tmp += src0[j];
|
||||
}
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
tmp = simd_sum(tmp);
|
||||
if (ntg > N_SIMDWIDTH) {
|
||||
if (sgitg == 0) {
|
||||
buf[tiisg] = 0.0f;
|
||||
}
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
if (tiisg == 0) {
|
||||
buf[sgitg] = tmp;
|
||||
}
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
tmp = buf[tiisg];
|
||||
tmp = simd_sum(tmp);
|
||||
}
|
||||
|
||||
const float mean = tmp / gs;
|
||||
tmp = 0.0f;
|
||||
|
||||
for (int j = start; j < end; j += ntg) {
|
||||
float xi = src0[j] - mean;
|
||||
dst[j] = xi;
|
||||
tmp += xi * xi;
|
||||
}
|
||||
|
||||
tmp = simd_sum(tmp);
|
||||
if (ntg > N_SIMDWIDTH) {
|
||||
if (sgitg == 0) {
|
||||
buf[tiisg] = 0.0f;
|
||||
}
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
if (tiisg == 0) {
|
||||
buf[sgitg] = tmp;
|
||||
}
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
tmp = buf[tiisg];
|
||||
tmp = simd_sum(tmp);
|
||||
}
|
||||
|
||||
const float variance = tmp / gs;
|
||||
const float scale = 1.0f/sqrt(variance + args.eps);
|
||||
for (int j = start; j < end; j += ntg) {
|
||||
dst[j] *= scale;
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,148 @@
|
||||
#include "common.h"
|
||||
|
||||
kernel void kernel_pool_2d_max_f32(
|
||||
constant ggml_metal_kargs_pool_2d & args,
|
||||
device const float * src0,
|
||||
device float * dst,
|
||||
uint gid[[thread_position_in_grid]]) {
|
||||
|
||||
if (gid >= args.np) {
|
||||
return;
|
||||
}
|
||||
|
||||
const int idx = gid;
|
||||
const int I_HW = args.IH * args.IW;
|
||||
const int O_HW = args.OH * args.OW;
|
||||
const int nc = idx / O_HW;
|
||||
const int cur_oh = idx % O_HW / args.OW;
|
||||
const int cur_ow = idx % O_HW % args.OW;
|
||||
|
||||
device const float * i_ptr = src0 + nc * I_HW;
|
||||
device float * o_ptr = dst + nc * O_HW;
|
||||
|
||||
const int start_h = cur_oh * args.s1 - args.p1;
|
||||
const int bh = MAX(0, start_h);
|
||||
const int eh = MIN(args.IH, start_h + args.k1);
|
||||
const int start_w = cur_ow * args.s0 - args.p0;
|
||||
const int bw = MAX(0, start_w);
|
||||
const int ew = MIN(args.IW, start_w + args.k0);
|
||||
|
||||
float res = -INFINITY;
|
||||
|
||||
for (int i = bh; i < eh; i += 1) {
|
||||
for (int j = bw; j < ew; j += 1) {
|
||||
res = MAX(res, i_ptr[i * args.IW + j]);
|
||||
}
|
||||
}
|
||||
|
||||
o_ptr[cur_oh * args.OW + cur_ow] = res;
|
||||
}
|
||||
|
||||
kernel void kernel_pool_2d_avg_f32(
|
||||
constant ggml_metal_kargs_pool_2d & args,
|
||||
device const float * src0,
|
||||
device float * dst,
|
||||
uint gid[[thread_position_in_grid]]) {
|
||||
|
||||
if (gid >= args.np) {
|
||||
return;
|
||||
}
|
||||
|
||||
const int idx = gid;
|
||||
const int I_HW = args.IH * args.IW;
|
||||
const int O_HW = args.OH * args.OW;
|
||||
const int nc = idx / O_HW;
|
||||
const int cur_oh = idx % O_HW / args.OW;
|
||||
const int cur_ow = idx % O_HW % args.OW;
|
||||
|
||||
device const float * i_ptr = src0 + nc * I_HW;
|
||||
device float * o_ptr = dst + nc * O_HW;
|
||||
|
||||
const int start_h = cur_oh * args.s1 - args.p1;
|
||||
const int bh = MAX(0, start_h);
|
||||
const int eh = MIN(args.IH, start_h + args.k1);
|
||||
const int start_w = cur_ow * args.s0 - args.p0;
|
||||
const int bw = MAX(0, start_w);
|
||||
const int ew = MIN(args.IW, start_w + args.k0);
|
||||
// const float scale = 1. / ((eh - bh) * (ew - bw));
|
||||
const float scale = 1. / (args.k0 * args.k1);
|
||||
|
||||
float res = 0;
|
||||
|
||||
for (int i = bh; i < eh; i += 1) {
|
||||
for (int j = bw; j < ew; j += 1) {
|
||||
float cur = i_ptr[i * args.IW + j];
|
||||
res += cur * scale;
|
||||
}
|
||||
}
|
||||
|
||||
o_ptr[cur_oh * args.OW + cur_ow] = res;
|
||||
}
|
||||
|
||||
|
||||
kernel void kernel_pool_1d_max_f32(
|
||||
constant ggml_metal_kargs_pool_1d & args,
|
||||
device const float * src,
|
||||
device float * dst,
|
||||
uint gid [[thread_position_in_grid]]
|
||||
) {
|
||||
|
||||
if (gid >= args.np) {
|
||||
return;
|
||||
}
|
||||
|
||||
const int ow = (int)gid % args.OW;
|
||||
const int row = (int)gid / args.OW;
|
||||
|
||||
const int base = ow * args.s0 - args.p0;
|
||||
|
||||
float acc = -INFINITY;
|
||||
|
||||
const int src_off = row * args.IW;
|
||||
const int dst_off = row * args.OW;
|
||||
|
||||
for (int ki = 0; ki < args.k0; ++ki) {
|
||||
int j = base + ki;
|
||||
if (j < 0 || j >= args.IW){
|
||||
continue;
|
||||
}
|
||||
float v = src[src_off + j];
|
||||
acc = max(acc, v);
|
||||
}
|
||||
|
||||
dst[dst_off + ow] = acc;
|
||||
}
|
||||
|
||||
kernel void kernel_pool_1d_avg_f32(
|
||||
constant ggml_metal_kargs_pool_1d & args,
|
||||
device const float * src,
|
||||
device float * dst,
|
||||
uint gid [[thread_position_in_grid]]
|
||||
) {
|
||||
|
||||
if (gid >= args.np) {
|
||||
return;
|
||||
}
|
||||
|
||||
const int ow = (int)gid % args.OW;
|
||||
const int row = (int)gid / args.OW;
|
||||
|
||||
const int base = ow * args.s0 - args.p0;
|
||||
|
||||
float acc = 0.0f;
|
||||
int cnt = 0;
|
||||
|
||||
const int src_off = row * args.IW;
|
||||
const int dst_off = row * args.OW;
|
||||
|
||||
for (int ki = 0; ki < args.k0; ++ki) {
|
||||
const int j = base + ki;
|
||||
if (j < 0 || j >= args.IW) {
|
||||
continue;
|
||||
}
|
||||
acc += src[src_off + j];
|
||||
cnt += 1;
|
||||
}
|
||||
|
||||
dst[dst_off + ow] = (cnt > 0) ? (acc / (float)cnt) : 0.0f;
|
||||
}
|
||||
@@ -0,0 +1,213 @@
|
||||
#pragma once
|
||||
|
||||
#include "common.h"
|
||||
|
||||
void quantize_q1_0(device const float * src, device block_q1_0 & dst) {
|
||||
float sum_abs = 0.0f;
|
||||
for (int j = 0; j < QK1_0; j++) {
|
||||
sum_abs += fabs(src[j]);
|
||||
}
|
||||
dst.d = sum_abs / QK1_0;
|
||||
|
||||
for (int j = 0; j < QK1_0 / 8; j++) {
|
||||
dst.qs[j] = 0;
|
||||
}
|
||||
for (int j = 0; j < QK1_0; j++) {
|
||||
if (src[j] >= 0.0f) {
|
||||
dst.qs[j / 8] |= (1 << (j % 8));
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
void quantize_q4_0(device const float * src, device block_q4_0 & dst) {
|
||||
#pragma METAL fp math_mode(safe)
|
||||
float amax = 0.0f; // absolute max
|
||||
float max = 0.0f;
|
||||
|
||||
for (int j = 0; j < QK4_0; j++) {
|
||||
const float v = src[j];
|
||||
if (amax < fabs(v)) {
|
||||
amax = fabs(v);
|
||||
max = v;
|
||||
}
|
||||
}
|
||||
|
||||
const float d = max / -8;
|
||||
const float id = d ? 1.0f/d : 0.0f;
|
||||
|
||||
dst.d = d;
|
||||
|
||||
for (int j = 0; j < QK4_0/2; ++j) {
|
||||
const float x0 = src[0 + j]*id;
|
||||
const float x1 = src[QK4_0/2 + j]*id;
|
||||
|
||||
const uint8_t xi0 = MIN(15, (int8_t)(x0 + 8.5f));
|
||||
const uint8_t xi1 = MIN(15, (int8_t)(x1 + 8.5f));
|
||||
|
||||
dst.qs[j] = xi0;
|
||||
dst.qs[j] |= xi1 << 4;
|
||||
}
|
||||
}
|
||||
|
||||
void quantize_q4_1(device const float * src, device block_q4_1 & dst) {
|
||||
#pragma METAL fp math_mode(safe)
|
||||
float min = FLT_MAX;
|
||||
float max = -FLT_MAX;
|
||||
|
||||
for (int j = 0; j < QK4_1; j++) {
|
||||
const float v = src[j];
|
||||
if (min > v) min = v;
|
||||
if (max < v) max = v;
|
||||
}
|
||||
|
||||
const float d = (max - min) / ((1 << 4) - 1);
|
||||
const float id = d ? 1.0f/d : 0.0f;
|
||||
|
||||
dst.d = d;
|
||||
dst.m = min;
|
||||
|
||||
for (int j = 0; j < QK4_1/2; ++j) {
|
||||
const float x0 = (src[0 + j] - min)*id;
|
||||
const float x1 = (src[QK4_1/2 + j] - min)*id;
|
||||
|
||||
const uint8_t xi0 = MIN(15, (int8_t)(x0 + 0.5f));
|
||||
const uint8_t xi1 = MIN(15, (int8_t)(x1 + 0.5f));
|
||||
|
||||
dst.qs[j] = xi0;
|
||||
dst.qs[j] |= xi1 << 4;
|
||||
}
|
||||
}
|
||||
|
||||
void quantize_q5_0(device const float * src, device block_q5_0 & dst) {
|
||||
#pragma METAL fp math_mode(safe)
|
||||
float amax = 0.0f; // absolute max
|
||||
float max = 0.0f;
|
||||
|
||||
for (int j = 0; j < QK5_0; j++) {
|
||||
const float v = src[j];
|
||||
if (amax < fabs(v)) {
|
||||
amax = fabs(v);
|
||||
max = v;
|
||||
}
|
||||
}
|
||||
|
||||
const float d = max / -16;
|
||||
const float id = d ? 1.0f/d : 0.0f;
|
||||
|
||||
dst.d = d;
|
||||
|
||||
uint32_t qh = 0;
|
||||
for (int j = 0; j < QK5_0/2; ++j) {
|
||||
const float x0 = src[0 + j]*id;
|
||||
const float x1 = src[QK5_0/2 + j]*id;
|
||||
|
||||
const uint8_t xi0 = MIN(31, (int8_t)(x0 + 16.5f));
|
||||
const uint8_t xi1 = MIN(31, (int8_t)(x1 + 16.5f));
|
||||
|
||||
dst.qs[j] = (xi0 & 0xf) | ((xi1 & 0xf) << 4);
|
||||
qh |= ((xi0 & 0x10u) >> 4) << (j + 0);
|
||||
qh |= ((xi1 & 0x10u) >> 4) << (j + QK5_0/2);
|
||||
}
|
||||
|
||||
thread const uint8_t * qh8 = (thread const uint8_t *)&qh;
|
||||
|
||||
for (int j = 0; j < 4; ++j) {
|
||||
dst.qh[j] = qh8[j];
|
||||
}
|
||||
}
|
||||
|
||||
void quantize_q5_1(device const float * src, device block_q5_1 & dst) {
|
||||
#pragma METAL fp math_mode(safe)
|
||||
float max = src[0];
|
||||
float min = src[0];
|
||||
|
||||
for (int j = 1; j < QK5_1; j++) {
|
||||
const float v = src[j];
|
||||
min = v < min ? v : min;
|
||||
max = v > max ? v : max;
|
||||
}
|
||||
|
||||
const float d = (max - min) / 31;
|
||||
const float id = d ? 1.0f/d : 0.0f;
|
||||
|
||||
dst.d = d;
|
||||
dst.m = min;
|
||||
|
||||
uint32_t qh = 0;
|
||||
for (int j = 0; j < QK5_1/2; ++j) {
|
||||
const float x0 = (src[0 + j] - min)*id;
|
||||
const float x1 = (src[QK5_1/2 + j] - min)*id;
|
||||
|
||||
const uint8_t xi0 = (uint8_t)(x0 + 0.5f);
|
||||
const uint8_t xi1 = (uint8_t)(x1 + 0.5f);
|
||||
|
||||
dst.qs[j] = (xi0 & 0xf) | ((xi1 & 0xf) << 4);
|
||||
qh |= ((xi0 & 0x10u) >> 4) << (j + 0);
|
||||
qh |= ((xi1 & 0x10u) >> 4) << (j + QK5_1/2);
|
||||
}
|
||||
|
||||
thread const uint8_t * qh8 = (thread const uint8_t *)&qh;
|
||||
|
||||
for (int j = 0; j < 4; ++j) {
|
||||
dst.qh[j] = qh8[j];
|
||||
}
|
||||
}
|
||||
|
||||
void quantize_q8_0(device const float * src, device block_q8_0 & dst) {
|
||||
#pragma METAL fp math_mode(safe)
|
||||
float amax = 0.0f; // absolute max
|
||||
|
||||
for (int j = 0; j < QK8_0; j++) {
|
||||
const float v = src[j];
|
||||
amax = MAX(amax, fabs(v));
|
||||
}
|
||||
|
||||
const float d = amax / ((1 << 7) - 1);
|
||||
const float id = d ? 1.0f/d : 0.0f;
|
||||
|
||||
dst.d = d;
|
||||
|
||||
for (int j = 0; j < QK8_0; ++j) {
|
||||
const float x0 = src[j]*id;
|
||||
|
||||
dst.qs[j] = round(x0);
|
||||
}
|
||||
}
|
||||
|
||||
void quantize_iq4_nl(device const float * src, device block_iq4_nl & dst) {
|
||||
#pragma METAL fp math_mode(safe)
|
||||
float amax = 0.0f; // absolute max
|
||||
float max = 0.0f;
|
||||
|
||||
for (int j = 0; j < QK4_NL; j++) {
|
||||
const float v = src[j];
|
||||
if (amax < fabs(v)) {
|
||||
amax = fabs(v);
|
||||
max = v;
|
||||
}
|
||||
}
|
||||
|
||||
const float d = max / kvalues_iq4nl_f[0];
|
||||
const float id = d ? 1.0f/d : 0.0f;
|
||||
|
||||
float sumqx = 0, sumq2 = 0;
|
||||
for (int j = 0; j < QK4_NL/2; ++j) {
|
||||
const float x0 = src[0 + j]*id;
|
||||
const float x1 = src[QK4_NL/2 + j]*id;
|
||||
|
||||
const uint8_t xi0 = best_index_int8(16, kvalues_iq4nl_f, x0);
|
||||
const uint8_t xi1 = best_index_int8(16, kvalues_iq4nl_f, x1);
|
||||
|
||||
dst.qs[j] = xi0 | (xi1 << 4);
|
||||
|
||||
const float v0 = kvalues_iq4nl_f[xi0];
|
||||
const float v1 = kvalues_iq4nl_f[xi1];
|
||||
const float w0 = src[0 + j]*src[0 + j];
|
||||
const float w1 = src[QK4_NL/2 + j]*src[QK4_NL/2 + j];
|
||||
sumqx += w0*v0*src[j] + w1*v1*src[QK4_NL/2 + j];
|
||||
sumq2 += w0*v0*v0 + w1*v1*v1;
|
||||
|
||||
}
|
||||
|
||||
dst.d = sumq2 > 0 ? sumqx/sumq2 : d;
|
||||
}
|
||||
@@ -0,0 +1,389 @@
|
||||
#include "common.h"
|
||||
#include "dequantize.h"
|
||||
#include "quantize.h"
|
||||
|
||||
template<typename T0, typename T1>
|
||||
kernel void kernel_cpy_t_t(
|
||||
constant ggml_metal_kargs_cpy & args,
|
||||
device const char * src0,
|
||||
device char * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
ushort3 tpitg[[thread_position_in_threadgroup]],
|
||||
ushort3 ntg[[threads_per_threadgroup]]) {
|
||||
const int32_t i03 = tgpig[2];
|
||||
const int32_t i02 = tgpig[1];
|
||||
const int32_t i01 = ntg[1] == 1 ? tgpig[0]%args.ne01 : tgpig[0]*ntg[1] + tpitg.y;
|
||||
const int32_t iw0 = ntg[1] == 1 ? tgpig[0]/args.ne01 : 0;
|
||||
|
||||
if (i01 >= args.ne01) {
|
||||
return;
|
||||
}
|
||||
|
||||
const int64_t n = i03*args.ne02*args.ne01*args.ne00 + i02*args.ne01*args.ne00 + i01*args.ne00;
|
||||
|
||||
const int32_t i3 = n/(args.ne2*args.ne1*args.ne0);
|
||||
const int32_t i2 = (n - i3*args.ne2*args.ne1*args.ne0)/(args.ne1*args.ne0);
|
||||
const int32_t i1 = (n - i3*args.ne2*args.ne1*args.ne0 - i2*args.ne1*args.ne0)/args.ne0;
|
||||
const int32_t i0 = (n - i3*args.ne2*args.ne1*args.ne0 - i2*args.ne1*args.ne0 - i1*args.ne0);
|
||||
|
||||
device T1 * dst_data = (device T1 *) (dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1 + i0*args.nb0);
|
||||
|
||||
for (int32_t i00 = iw0*ntg[0] + tpitg.x; i00 < args.ne00;) {
|
||||
device const T0 * src = (device T0 *)(src0 + i03*args.nb03 + i02*args.nb02 + i01*args.nb01 + i00*args.nb00);
|
||||
dst_data[i00] = (T1) src[0];
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
typedef decltype(kernel_cpy_t_t<float, float>) kernel_cpy_t;
|
||||
|
||||
template [[host_name("kernel_cpy_f32_f32")]] kernel kernel_cpy_t kernel_cpy_t_t<float, float>;
|
||||
template [[host_name("kernel_cpy_f32_f16")]] kernel kernel_cpy_t kernel_cpy_t_t<float, half>;
|
||||
template [[host_name("kernel_cpy_f32_i32")]] kernel kernel_cpy_t kernel_cpy_t_t<float, int32_t>;
|
||||
template [[host_name("kernel_cpy_i32_f32")]] kernel kernel_cpy_t kernel_cpy_t_t<int32_t, float>;
|
||||
template [[host_name("kernel_cpy_i32_i32")]] kernel kernel_cpy_t kernel_cpy_t_t<int32_t, int32_t>;
|
||||
#if defined(GGML_METAL_HAS_BF16)
|
||||
template [[host_name("kernel_cpy_f32_bf16")]] kernel kernel_cpy_t kernel_cpy_t_t<float, bfloat>;
|
||||
#endif
|
||||
template [[host_name("kernel_cpy_f16_f32")]] kernel kernel_cpy_t kernel_cpy_t_t<half, float>;
|
||||
template [[host_name("kernel_cpy_f16_f16")]] kernel kernel_cpy_t kernel_cpy_t_t<half, half>;
|
||||
#if defined(GGML_METAL_HAS_BF16)
|
||||
template [[host_name("kernel_cpy_bf16_f32")]] kernel kernel_cpy_t kernel_cpy_t_t<bfloat, float>;
|
||||
template [[host_name("kernel_cpy_bf16_bf16")]] kernel kernel_cpy_t kernel_cpy_t_t<bfloat, bfloat>;
|
||||
#endif
|
||||
|
||||
template<short QK,
|
||||
typename block_q,
|
||||
void (*quantize_func)(device const float *, device block_q &)>
|
||||
kernel void kernel_cpy_f32_q(
|
||||
constant ggml_metal_kargs_cpy & args,
|
||||
device const char * src0,
|
||||
device char * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
ushort3 tpitg[[thread_position_in_threadgroup]],
|
||||
ushort3 ntg[[threads_per_threadgroup]]) {
|
||||
const int32_t i03 = tgpig[2];
|
||||
const int32_t i02 = tgpig[1];
|
||||
const int32_t i01 = ntg[1] == 1 ? tgpig[0]%args.ne01 : tgpig[0]*ntg[1] + tpitg.y;
|
||||
const int32_t iw0 = ntg[1] == 1 ? tgpig[0]/args.ne01 : 0;
|
||||
|
||||
if (i01 >= args.ne01) {
|
||||
return;
|
||||
}
|
||||
|
||||
const int64_t n = i03*args.ne02*args.ne01*args.ne00 + i02*args.ne01*args.ne00 + i01*args.ne00;
|
||||
|
||||
const int32_t i3 = n / (args.ne2*args.ne1*args.ne0);
|
||||
const int32_t i2 = (n - i3*args.ne2*args.ne1*args.ne0) / (args.ne1*args.ne0);
|
||||
const int32_t i1 = (n - i3*args.ne2*args.ne1*args.ne0 - i2*args.ne1*args.ne0) / args.ne0;
|
||||
const int32_t i0 = (n - i3*args.ne2*args.ne1*args.ne0 - i2*args.ne1*args.ne0 - i1*args.ne0)/QK;
|
||||
|
||||
device block_q * dst_data = (device block_q *)(dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1 + i0*args.nb0);
|
||||
|
||||
for (int32_t i00 = iw0*ntg[0] + tpitg.x; i00 < args.nk0;) {
|
||||
device const float * src = (device const float *)(src0 + i03*args.nb03 + i02*args.nb02 + i01*args.nb01 + (i00*QK)*args.nb00);
|
||||
|
||||
quantize_func(src, dst_data[i00]);
|
||||
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
typedef decltype(kernel_cpy_f32_q<QK8_0, block_q8_0, quantize_q8_0>) cpy_f_q_t;
|
||||
|
||||
template [[host_name("kernel_cpy_f32_q8_0")]] kernel cpy_f_q_t kernel_cpy_f32_q<QK8_0, block_q8_0, quantize_q8_0>;
|
||||
template [[host_name("kernel_cpy_f32_q1_0")]] kernel cpy_f_q_t kernel_cpy_f32_q<QK1_0, block_q1_0, quantize_q1_0>;
|
||||
template [[host_name("kernel_cpy_f32_q4_0")]] kernel cpy_f_q_t kernel_cpy_f32_q<QK4_0, block_q4_0, quantize_q4_0>;
|
||||
template [[host_name("kernel_cpy_f32_q4_1")]] kernel cpy_f_q_t kernel_cpy_f32_q<QK4_1, block_q4_1, quantize_q4_1>;
|
||||
template [[host_name("kernel_cpy_f32_q5_0")]] kernel cpy_f_q_t kernel_cpy_f32_q<QK5_0, block_q5_0, quantize_q5_0>;
|
||||
template [[host_name("kernel_cpy_f32_q5_1")]] kernel cpy_f_q_t kernel_cpy_f32_q<QK5_1, block_q5_1, quantize_q5_1>;
|
||||
template [[host_name("kernel_cpy_f32_iq4_nl")]] kernel cpy_f_q_t kernel_cpy_f32_q<QK4_NL, block_iq4_nl, quantize_iq4_nl>;
|
||||
|
||||
template<typename T4x4, typename block_q, short nl, void (*dequantize_func)(device const block_q *, short, thread T4x4 &)>
|
||||
kernel void kernel_cpy_q_f32(
|
||||
constant ggml_metal_kargs_cpy & args,
|
||||
device const char * src0,
|
||||
device char * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
ushort3 tpitg[[thread_position_in_threadgroup]],
|
||||
ushort3 ntg[[threads_per_threadgroup]]) {
|
||||
const int32_t i03 = tgpig[2];
|
||||
const int32_t i02 = tgpig[1];
|
||||
const int32_t i01 = ntg[1] == 1 ? tgpig[0]%args.ne01 : tgpig[0]*ntg[1] + tpitg.y;
|
||||
const int32_t iw0 = ntg[1] == 1 ? tgpig[0]/args.ne01 : 0;
|
||||
|
||||
if (i01 >= args.ne01) {
|
||||
return;
|
||||
}
|
||||
|
||||
const int64_t n = i03*args.ne02*args.ne01*args.ne00 + i02*args.ne01*args.ne00 + i01*args.ne00;
|
||||
|
||||
const int32_t i3 = n/(args.ne2*args.ne1*args.ne0);
|
||||
const int32_t i2 = (n - i3*args.ne2*args.ne1*args.ne0)/(args.ne1*args.ne0);
|
||||
const int32_t i1 = (n - i3*args.ne2*args.ne1*args.ne0 - i2*args.ne1*args.ne0)/args.ne0;
|
||||
const int32_t i0 = (n - i3*args.ne2*args.ne1*args.ne0 - i2*args.ne1*args.ne0 - i1*args.ne0);
|
||||
|
||||
device const block_q * src_data = (device const block_q *)(src0 + i03*args.nb03 + i02*args.nb02 + i01*args.nb01);
|
||||
device T4x4 * dst_data = (device T4x4 *)(dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1 + i0*args.nb0);
|
||||
|
||||
for (int32_t i00 = iw0*ntg[0] + tpitg.x; i00 < args.nk0;) {
|
||||
T4x4 temp;
|
||||
dequantize_func(src_data + i00/nl, i00%nl, temp);
|
||||
dst_data[i00] = temp;
|
||||
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
typedef decltype(kernel_cpy_q_f32<float4x4, block_q4_0, 2, dequantize_q4_0>) cpy_q_f_t;
|
||||
|
||||
template [[host_name("kernel_cpy_q1_0_f32")]] kernel cpy_q_f_t kernel_cpy_q_f32<float4x4, block_q1_0, 8, dequantize_q1_0>;
|
||||
template [[host_name("kernel_cpy_q4_0_f32")]] kernel cpy_q_f_t kernel_cpy_q_f32<float4x4, block_q4_0, 2, dequantize_q4_0>;
|
||||
template [[host_name("kernel_cpy_q4_1_f32")]] kernel cpy_q_f_t kernel_cpy_q_f32<float4x4, block_q4_1, 2, dequantize_q4_1>;
|
||||
template [[host_name("kernel_cpy_q5_0_f32")]] kernel cpy_q_f_t kernel_cpy_q_f32<float4x4, block_q5_0, 2, dequantize_q5_0>;
|
||||
template [[host_name("kernel_cpy_q5_1_f32")]] kernel cpy_q_f_t kernel_cpy_q_f32<float4x4, block_q5_1, 2, dequantize_q5_1>;
|
||||
template [[host_name("kernel_cpy_q8_0_f32")]] kernel cpy_q_f_t kernel_cpy_q_f32<float4x4, block_q8_0, 2, dequantize_q8_0>;
|
||||
|
||||
template [[host_name("kernel_cpy_q1_0_f16")]] kernel cpy_q_f_t kernel_cpy_q_f32<half4x4, block_q1_0, 8, dequantize_q1_0>;
|
||||
template [[host_name("kernel_cpy_q4_0_f16")]] kernel cpy_q_f_t kernel_cpy_q_f32<half4x4, block_q4_0, 2, dequantize_q4_0>;
|
||||
template [[host_name("kernel_cpy_q4_1_f16")]] kernel cpy_q_f_t kernel_cpy_q_f32<half4x4, block_q4_1, 2, dequantize_q4_1>;
|
||||
template [[host_name("kernel_cpy_q5_0_f16")]] kernel cpy_q_f_t kernel_cpy_q_f32<half4x4, block_q5_0, 2, dequantize_q5_0>;
|
||||
template [[host_name("kernel_cpy_q5_1_f16")]] kernel cpy_q_f_t kernel_cpy_q_f32<half4x4, block_q5_1, 2, dequantize_q5_1>;
|
||||
template [[host_name("kernel_cpy_q8_0_f16")]] kernel cpy_q_f_t kernel_cpy_q_f32<half4x4, block_q8_0, 2, dequantize_q8_0>;
|
||||
|
||||
template<typename T>
|
||||
kernel void kernel_concat(
|
||||
constant ggml_metal_kargs_concat & args,
|
||||
device const char * src0,
|
||||
device const char * src1,
|
||||
device char * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
ushort3 tpitg[[thread_position_in_threadgroup]],
|
||||
ushort3 ntg[[threads_per_threadgroup]]) {
|
||||
|
||||
const int i3 = tgpig.z;
|
||||
const int i2 = tgpig.y;
|
||||
const int i1 = ntg.y == 1 ? tgpig.x : tgpig.x*ntg.y + tpitg.y;
|
||||
|
||||
if (i1 >= args.ne1) {
|
||||
return;
|
||||
}
|
||||
|
||||
int o[4] = {0, 0, 0, 0};
|
||||
o[args.dim] = args.dim == 0 ? args.ne00 : (args.dim == 1 ? args.ne01 : (args.dim == 2 ? args.ne02 : args.ne03));
|
||||
|
||||
for (int i0 = tpitg.x; i0 < args.ne0; i0 += ntg.x) {
|
||||
device const T * x;
|
||||
|
||||
if (i0 < args.ne00 && i1 < args.ne01 && i2 < args.ne02 && i3 < args.ne03) {
|
||||
x = (device const T *)(src0 + (i3 )*args.nb03 + (i2 )*args.nb02 + (i1 )*args.nb01 + (i0 )*args.nb00);
|
||||
} else {
|
||||
x = (device const T *)(src1 + (i3 - o[3])*args.nb13 + (i2 - o[2])*args.nb12 + (i1 - o[1])*args.nb11 + (i0 - o[0])*args.nb10);
|
||||
}
|
||||
|
||||
device T * y = (device T *)(dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1 + i0*args.nb0);
|
||||
|
||||
*y = *x;
|
||||
}
|
||||
}
|
||||
|
||||
typedef decltype(kernel_concat<float>) kernel_concat_t;
|
||||
|
||||
template [[host_name("kernel_concat_f32")]] kernel kernel_concat_t kernel_concat<float>;
|
||||
template [[host_name("kernel_concat_f16")]] kernel kernel_concat_t kernel_concat<half>;
|
||||
#if defined(GGML_METAL_HAS_BF16)
|
||||
template [[host_name("kernel_concat_bf16")]] kernel kernel_concat_t kernel_concat<bfloat>;
|
||||
#endif
|
||||
template [[host_name("kernel_concat_i8")]] kernel kernel_concat_t kernel_concat<char>;
|
||||
template [[host_name("kernel_concat_i16")]] kernel kernel_concat_t kernel_concat<short>;
|
||||
template [[host_name("kernel_concat_i32")]] kernel kernel_concat_t kernel_concat<int>;
|
||||
template [[host_name("kernel_concat_i64")]] kernel kernel_concat_t kernel_concat<long>;
|
||||
|
||||
template<typename block_q, short nl, void (*dequantize_func)(device const block_q *, short, thread float4x4 &)>
|
||||
kernel void kernel_get_rows_q(
|
||||
constant ggml_metal_kargs_get_rows & args,
|
||||
device const void * src0,
|
||||
device const void * src1,
|
||||
device void * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
ushort tiitg[[thread_index_in_threadgroup]],
|
||||
ushort3 ntg [[threads_per_threadgroup]]) {
|
||||
const int32_t iw0 = tgpig.x/args.ne10;
|
||||
const int32_t i10 = tgpig.x%args.ne10;
|
||||
const int32_t i11 = tgpig.y;
|
||||
const int32_t i12 = tgpig.z;
|
||||
|
||||
const int32_t r = ((const device int32_t *) ((const device char *) src1 + i12*args.nb12 + i11*args.nb11 + i10*args.nb10))[0];
|
||||
|
||||
const int32_t i02 = i11;
|
||||
const int32_t i03 = i12;
|
||||
|
||||
auto psrc = (device const block_q *) ((const device char *) src0 + i03*args.nb03 + i02*args.nb02 + r*args.nb01);
|
||||
auto pdst = (device float4x4 *) (( device char *) dst + i12*args.nb3 + i11*args.nb2 + i10*args.nb1);
|
||||
|
||||
for (int ind = iw0*ntg.x + tiitg; ind < args.ne00t;) {
|
||||
float4x4 temp;
|
||||
dequantize_func(psrc + ind/nl, ind%nl, temp);
|
||||
pdst[ind] = temp;
|
||||
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
template<typename T0, typename T>
|
||||
kernel void kernel_get_rows_f(
|
||||
constant ggml_metal_kargs_get_rows & args,
|
||||
device const void * src0,
|
||||
device const void * src1,
|
||||
device void * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
ushort tiitg[[thread_index_in_threadgroup]],
|
||||
ushort3 ntg [[threads_per_threadgroup]]) {
|
||||
const int32_t iw0 = tgpig.x/args.ne10;
|
||||
const int32_t i10 = tgpig.x%args.ne10;
|
||||
const int32_t i11 = tgpig.y;
|
||||
const int32_t i12 = tgpig.z;
|
||||
|
||||
const int32_t r = ((const device int32_t *) ((const device char *) src1 + i12*args.nb12 + i11*args.nb11 + i10*args.nb10))[0];
|
||||
|
||||
const int32_t i02 = i11;
|
||||
const int32_t i03 = i12;
|
||||
|
||||
auto psrc = (const device T0 *) ((const device char *) src0 + i03*args.nb03 + i02*args.nb02 + r*args.nb01);
|
||||
auto pdst = ( device T *) (( device char *) dst + i12*args.nb3 + i11*args.nb2 + i10*args.nb1);
|
||||
|
||||
for (int ind = iw0*ntg.x + tiitg; ind < args.ne00t;) {
|
||||
pdst[ind] = psrc[ind];
|
||||
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
typedef decltype(kernel_get_rows_f<float, float>) get_rows_f_t;
|
||||
|
||||
template [[host_name("kernel_get_rows_f32")]] kernel get_rows_f_t kernel_get_rows_f<float, float>;
|
||||
template [[host_name("kernel_get_rows_f16")]] kernel get_rows_f_t kernel_get_rows_f<half, float>;
|
||||
template [[host_name("kernel_get_rows_i32")]] kernel get_rows_f_t kernel_get_rows_f<int32_t, int32_t>;
|
||||
#if defined(GGML_METAL_HAS_BF16)
|
||||
template [[host_name("kernel_get_rows_bf16")]] kernel get_rows_f_t kernel_get_rows_f<bfloat, float>;
|
||||
#endif
|
||||
|
||||
typedef decltype(kernel_get_rows_q<block_q4_0, 2, dequantize_q4_0>) get_rows_q_t;
|
||||
|
||||
template [[host_name("kernel_get_rows_q1_0")]] kernel get_rows_q_t kernel_get_rows_q<block_q1_0, 8, dequantize_q1_0>;
|
||||
template [[host_name("kernel_get_rows_q4_0")]] kernel get_rows_q_t kernel_get_rows_q<block_q4_0, 2, dequantize_q4_0>;
|
||||
template [[host_name("kernel_get_rows_q4_1")]] kernel get_rows_q_t kernel_get_rows_q<block_q4_1, 2, dequantize_q4_1>;
|
||||
template [[host_name("kernel_get_rows_q5_0")]] kernel get_rows_q_t kernel_get_rows_q<block_q5_0, 2, dequantize_q5_0>;
|
||||
template [[host_name("kernel_get_rows_q5_1")]] kernel get_rows_q_t kernel_get_rows_q<block_q5_1, 2, dequantize_q5_1>;
|
||||
template [[host_name("kernel_get_rows_q8_0")]] kernel get_rows_q_t kernel_get_rows_q<block_q8_0, 2, dequantize_q8_0>;
|
||||
template [[host_name("kernel_get_rows_mxfp4")]] kernel get_rows_q_t kernel_get_rows_q<block_mxfp4, 2, dequantize_mxfp4>;
|
||||
template [[host_name("kernel_get_rows_q2_K")]] kernel get_rows_q_t kernel_get_rows_q<block_q2_K, QK_NL, dequantize_q2_K>;
|
||||
template [[host_name("kernel_get_rows_q3_K")]] kernel get_rows_q_t kernel_get_rows_q<block_q3_K, QK_NL, dequantize_q3_K>;
|
||||
template [[host_name("kernel_get_rows_q4_K")]] kernel get_rows_q_t kernel_get_rows_q<block_q4_K, QK_NL, dequantize_q4_K>;
|
||||
template [[host_name("kernel_get_rows_q5_K")]] kernel get_rows_q_t kernel_get_rows_q<block_q5_K, QK_NL, dequantize_q5_K>;
|
||||
template [[host_name("kernel_get_rows_q6_K")]] kernel get_rows_q_t kernel_get_rows_q<block_q6_K, QK_NL, dequantize_q6_K>;
|
||||
template [[host_name("kernel_get_rows_iq2_xxs")]] kernel get_rows_q_t kernel_get_rows_q<block_iq2_xxs, QK_NL, dequantize_iq2_xxs>;
|
||||
template [[host_name("kernel_get_rows_iq2_xs")]] kernel get_rows_q_t kernel_get_rows_q<block_iq2_xs, QK_NL, dequantize_iq2_xs>;
|
||||
template [[host_name("kernel_get_rows_iq3_xxs")]] kernel get_rows_q_t kernel_get_rows_q<block_iq3_xxs, QK_NL, dequantize_iq3_xxs>;
|
||||
template [[host_name("kernel_get_rows_iq3_s")]] kernel get_rows_q_t kernel_get_rows_q<block_iq3_s, QK_NL, dequantize_iq3_s>;
|
||||
template [[host_name("kernel_get_rows_iq2_s")]] kernel get_rows_q_t kernel_get_rows_q<block_iq2_s, QK_NL, dequantize_iq2_s>;
|
||||
template [[host_name("kernel_get_rows_iq1_s")]] kernel get_rows_q_t kernel_get_rows_q<block_iq1_s, QK_NL, dequantize_iq1_s>;
|
||||
template [[host_name("kernel_get_rows_iq1_m")]] kernel get_rows_q_t kernel_get_rows_q<block_iq1_m, QK_NL, dequantize_iq1_m>;
|
||||
template [[host_name("kernel_get_rows_iq4_nl")]] kernel get_rows_q_t kernel_get_rows_q<block_iq4_nl, 2, dequantize_iq4_nl>;
|
||||
template [[host_name("kernel_get_rows_iq4_xs")]] kernel get_rows_q_t kernel_get_rows_q<block_iq4_xs, QK_NL, dequantize_iq4_xs>;
|
||||
|
||||
template<typename TS, typename TI, typename block_q, void (*quantize_func)(device const float *, device block_q &)>
|
||||
kernel void kernel_set_rows_q32(
|
||||
constant ggml_metal_kargs_set_rows & args,
|
||||
device const void * src0,
|
||||
device const void * src1,
|
||||
device float * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
uint tiitg[[thread_index_in_threadgroup]],
|
||||
uint3 tptg [[threads_per_threadgroup]]) {
|
||||
const int32_t i03 = tgpig.z;
|
||||
const int32_t i02 = tgpig.y;
|
||||
|
||||
const int32_t i12 = i03%args.ne12;
|
||||
const int32_t i11 = i02%args.ne11;
|
||||
|
||||
const int32_t i01 = tgpig.x*tptg.y + tiitg/tptg.x;
|
||||
if (i01 >= args.ne01) {
|
||||
return;
|
||||
}
|
||||
|
||||
const int32_t i10 = i01;
|
||||
const TI i1 = ((const device TI *) ((const device char *) src1 + i10*args.nb10 + i11*args.nb11 + i12*args.nb12))[0];
|
||||
|
||||
device block_q * dst_row = ( device block_q *) (( device char *) dst + i1*args.nb1 + i02*args.nb2 + i03*args.nb3);
|
||||
const device TS * src_row = (const device TS *) ((const device char *) src0 + i01*args.nb01 + i02*args.nb02 + i03*args.nb03);
|
||||
|
||||
for (int ind = tiitg%tptg.x; ind < args.nk0; ind += tptg.x) {
|
||||
quantize_func(src_row + 32*ind, dst_row[ind]);
|
||||
}
|
||||
}
|
||||
|
||||
template<typename TS, typename TI, typename TD>
|
||||
kernel void kernel_set_rows_f(
|
||||
constant ggml_metal_kargs_set_rows & args,
|
||||
device const void * src0,
|
||||
device const void * src1,
|
||||
device float * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
uint tiitg[[thread_index_in_threadgroup]],
|
||||
uint3 tptg [[threads_per_threadgroup]]) {
|
||||
const int32_t i03 = tgpig.z;
|
||||
const int32_t i02 = tgpig.y;
|
||||
|
||||
const int32_t i12 = i03%args.ne12;
|
||||
const int32_t i11 = i02%args.ne11;
|
||||
|
||||
const int32_t i01 = tgpig.x*tptg.y + tiitg/tptg.x;
|
||||
if (i01 >= args.ne01) {
|
||||
return;
|
||||
}
|
||||
|
||||
const int32_t i10 = i01;
|
||||
const TI i1 = ((const device TI *) ((const device char *) src1 + i10*args.nb10 + i11*args.nb11 + i12*args.nb12))[0];
|
||||
|
||||
device TD * dst_row = ( device TD *) (( device char *) dst + i1*args.nb1 + i02*args.nb2 + i03*args.nb3);
|
||||
const device TS * src_row = (const device TS *) ((const device char *) src0 + i01*args.nb01 + i02*args.nb02 + i03*args.nb03);
|
||||
|
||||
for (int ind = tiitg%tptg.x; ind < args.nk0; ind += tptg.x) {
|
||||
dst_row[ind] = (TD) src_row[ind];
|
||||
}
|
||||
}
|
||||
|
||||
typedef decltype(kernel_set_rows_f<float, int64_t, float>) set_rows_f_t;
|
||||
|
||||
template [[host_name("kernel_set_rows_f32_i64_f32")]] kernel set_rows_f_t kernel_set_rows_f<float, int64_t, float>;
|
||||
template [[host_name("kernel_set_rows_f32_i32_f32")]] kernel set_rows_f_t kernel_set_rows_f<float, int32_t, float>;
|
||||
template [[host_name("kernel_set_rows_f32_i64_f16")]] kernel set_rows_f_t kernel_set_rows_f<float, int64_t, half>;
|
||||
template [[host_name("kernel_set_rows_f32_i32_f16")]] kernel set_rows_f_t kernel_set_rows_f<float, int32_t, half>;
|
||||
#if defined(GGML_METAL_HAS_BF16)
|
||||
template [[host_name("kernel_set_rows_f32_i64_bf16")]] kernel set_rows_f_t kernel_set_rows_f<float, int64_t, bfloat>;
|
||||
template [[host_name("kernel_set_rows_f32_i32_bf16")]] kernel set_rows_f_t kernel_set_rows_f<float, int32_t, bfloat>;
|
||||
#endif
|
||||
|
||||
template [[host_name("kernel_set_rows_f16_i64_f16")]] kernel set_rows_f_t kernel_set_rows_f<half, int64_t, half>;
|
||||
template [[host_name("kernel_set_rows_f16_i32_f16")]] kernel set_rows_f_t kernel_set_rows_f<half, int32_t, half>;
|
||||
#if defined(GGML_METAL_HAS_BF16)
|
||||
template [[host_name("kernel_set_rows_bf16_i64_bf16")]] kernel set_rows_f_t kernel_set_rows_f<bfloat, int64_t, bfloat>;
|
||||
template [[host_name("kernel_set_rows_bf16_i32_bf16")]] kernel set_rows_f_t kernel_set_rows_f<bfloat, int32_t, bfloat>;
|
||||
#endif
|
||||
|
||||
typedef decltype(kernel_set_rows_q32<float, int64_t, block_q8_0, quantize_q8_0>) set_rows_q32_t;
|
||||
|
||||
template [[host_name("kernel_set_rows_f32_i64_q8_0")]] kernel set_rows_q32_t kernel_set_rows_q32<float, int64_t, block_q8_0, quantize_q8_0>;
|
||||
template [[host_name("kernel_set_rows_f32_i32_q8_0")]] kernel set_rows_q32_t kernel_set_rows_q32<float, int32_t, block_q8_0, quantize_q8_0>;
|
||||
template [[host_name("kernel_set_rows_f32_i64_q4_0")]] kernel set_rows_q32_t kernel_set_rows_q32<float, int64_t, block_q4_0, quantize_q4_0>;
|
||||
template [[host_name("kernel_set_rows_f32_i32_q4_0")]] kernel set_rows_q32_t kernel_set_rows_q32<float, int32_t, block_q4_0, quantize_q4_0>;
|
||||
template [[host_name("kernel_set_rows_f32_i64_q4_1")]] kernel set_rows_q32_t kernel_set_rows_q32<float, int64_t, block_q4_1, quantize_q4_1>;
|
||||
template [[host_name("kernel_set_rows_f32_i32_q4_1")]] kernel set_rows_q32_t kernel_set_rows_q32<float, int32_t, block_q4_1, quantize_q4_1>;
|
||||
template [[host_name("kernel_set_rows_f32_i64_q5_0")]] kernel set_rows_q32_t kernel_set_rows_q32<float, int64_t, block_q5_0, quantize_q5_0>;
|
||||
template [[host_name("kernel_set_rows_f32_i32_q5_0")]] kernel set_rows_q32_t kernel_set_rows_q32<float, int32_t, block_q5_0, quantize_q5_0>;
|
||||
template [[host_name("kernel_set_rows_f32_i64_q5_1")]] kernel set_rows_q32_t kernel_set_rows_q32<float, int64_t, block_q5_1, quantize_q5_1>;
|
||||
template [[host_name("kernel_set_rows_f32_i32_q5_1")]] kernel set_rows_q32_t kernel_set_rows_q32<float, int32_t, block_q5_1, quantize_q5_1>;
|
||||
template [[host_name("kernel_set_rows_f32_i64_iq4_nl")]] kernel set_rows_q32_t kernel_set_rows_q32<float, int64_t, block_iq4_nl, quantize_iq4_nl>;
|
||||
template [[host_name("kernel_set_rows_f32_i32_iq4_nl")]] kernel set_rows_q32_t kernel_set_rows_q32<float, int32_t, block_iq4_nl, quantize_iq4_nl>;
|
||||
|
||||
@@ -0,0 +1,228 @@
|
||||
#include "common.h"
|
||||
|
||||
kernel void kernel_op_sum_f32(
|
||||
constant ggml_metal_kargs_sum & args,
|
||||
device const float * src0,
|
||||
device float * dst,
|
||||
threadgroup float * shmem_f32 [[threadgroup(0)]],
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
ushort3 tpitg[[thread_position_in_threadgroup]],
|
||||
ushort sgitg[[simdgroup_index_in_threadgroup]],
|
||||
ushort tiisg[[thread_index_in_simdgroup]],
|
||||
ushort3 ntg[[threads_per_threadgroup]]) {
|
||||
|
||||
if (args.np == 0) {
|
||||
return;
|
||||
}
|
||||
|
||||
// TODO: become function constant
|
||||
const uint nsg = (ntg.x + 31) / 32;
|
||||
|
||||
float sumf = 0;
|
||||
|
||||
for (uint64_t i0 = tpitg.x; i0 < args.np; i0 += ntg.x) {
|
||||
sumf += src0[i0];
|
||||
}
|
||||
|
||||
sumf = simd_sum(sumf);
|
||||
|
||||
if (tiisg == 0) {
|
||||
shmem_f32[sgitg] = sumf;
|
||||
}
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
float total = 0;
|
||||
|
||||
if (sgitg == 0) {
|
||||
float v = 0;
|
||||
|
||||
if (tpitg.x < nsg) {
|
||||
v = shmem_f32[tpitg.x];
|
||||
}
|
||||
|
||||
total = simd_sum(v);
|
||||
|
||||
if (tpitg.x == 0) {
|
||||
dst[0] = total;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
constant short FC_sum_rows_op [[function_constant(FC_SUM_ROWS + 0)]];
|
||||
|
||||
template <typename T0, typename T>
|
||||
kernel void kernel_sum_rows_impl(
|
||||
constant ggml_metal_kargs_sum_rows & args,
|
||||
device const char * src0,
|
||||
device char * dst,
|
||||
threadgroup char * shmem [[threadgroup(0)]],
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
ushort3 tpitg[[thread_position_in_threadgroup]],
|
||||
ushort sgitg[[simdgroup_index_in_threadgroup]],
|
||||
ushort tiisg[[thread_index_in_simdgroup]],
|
||||
ushort3 ntg[[threads_per_threadgroup]]) {
|
||||
#define FC_OP FC_sum_rows_op
|
||||
|
||||
const int i3 = tgpig.z;
|
||||
const int i2 = tgpig.y;
|
||||
const int i1 = tgpig.x;
|
||||
|
||||
threadgroup T0 * shmem_t = (threadgroup T0 *) shmem;
|
||||
|
||||
if (sgitg == 0) {
|
||||
shmem_t[tiisg] = 0.0f;
|
||||
}
|
||||
|
||||
device const T0 * src_row = (device const T0 *) (src0 + i1*args.nb01 + i2*args.nb02 + i3*args.nb03);
|
||||
device T * dst_row = (device T *) (dst + i1*args.nb1 + i2*args.nb2 + i3*args.nb3);
|
||||
|
||||
T0 sumf = T0(0.0f);
|
||||
|
||||
for (int64_t i0 = tpitg.x; i0 < args.ne00; i0 += ntg.x) {
|
||||
sumf += src_row[i0];
|
||||
}
|
||||
|
||||
sumf = simd_sum(sumf);
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
if (tiisg == 0) {
|
||||
shmem_t[sgitg] = sumf;
|
||||
}
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
sumf = shmem_t[tiisg];
|
||||
sumf = simd_sum(sumf);
|
||||
|
||||
if (tpitg.x == 0) {
|
||||
if (FC_OP == OP_SUM_ROWS_NUM_MEAN) {
|
||||
if (is_same<float4, T0>::value) {
|
||||
dst_row[0] = sum(sumf) / (4*args.ne00);
|
||||
} else {
|
||||
dst_row[0] = sum(sumf) / args.ne00;
|
||||
}
|
||||
} else {
|
||||
dst_row[0] = sum(sumf);
|
||||
}
|
||||
}
|
||||
|
||||
#undef FC_OP
|
||||
}
|
||||
|
||||
typedef decltype(kernel_sum_rows_impl<float, float>) kernel_sum_rows_t;
|
||||
|
||||
template [[host_name("kernel_sum_rows_f32_f32")]] kernel kernel_sum_rows_t kernel_sum_rows_impl<float, float>;
|
||||
template [[host_name("kernel_sum_rows_f32_f32_4")]] kernel kernel_sum_rows_t kernel_sum_rows_impl<float4, float>;
|
||||
|
||||
template<typename T>
|
||||
kernel void kernel_cumsum_blk(
|
||||
constant ggml_metal_kargs_cumsum_blk & args,
|
||||
device const char * src0,
|
||||
device char * tmp,
|
||||
device char * dst,
|
||||
threadgroup char * shmem [[threadgroup(0)]],
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
ushort3 tpitg[[thread_position_in_threadgroup]],
|
||||
ushort sgitg[[simdgroup_index_in_threadgroup]],
|
||||
ushort tiisg[[thread_index_in_simdgroup]],
|
||||
ushort3 ntg[[threads_per_threadgroup]]) {
|
||||
const int ib = tgpig[0]/args.ne01;
|
||||
|
||||
const int i00 = ib*ntg.x;
|
||||
const int i01 = tgpig[0]%args.ne01;
|
||||
const int i02 = tgpig[1];
|
||||
const int i03 = tgpig[2];
|
||||
|
||||
device const float * src0_row = (device const float *) (src0 +
|
||||
args.nb01*i01 +
|
||||
args.nb02*i02 +
|
||||
args.nb03*i03);
|
||||
|
||||
threadgroup float * shmem_f32 = (threadgroup float *) shmem;
|
||||
|
||||
float v = 0.0f;
|
||||
|
||||
if (i00 + tpitg.x < args.ne00) {
|
||||
v = src0_row[i00 + tpitg.x];
|
||||
}
|
||||
|
||||
float s = simd_prefix_inclusive_sum(v);
|
||||
|
||||
if (tiisg == N_SIMDWIDTH - 1) {
|
||||
shmem_f32[sgitg] = s;
|
||||
}
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
if (sgitg == 0) {
|
||||
shmem_f32[tiisg] = simd_prefix_exclusive_sum(shmem_f32[tiisg]);
|
||||
}
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
s += shmem_f32[sgitg];
|
||||
|
||||
device float * dst_row = (device float *) dst +
|
||||
args.ne00*i01 +
|
||||
args.ne00*args.ne01*i02 +
|
||||
args.ne00*args.ne01*args.ne02*i03;
|
||||
|
||||
if (i00 + tpitg.x < args.ne00) {
|
||||
dst_row[i00 + tpitg.x] = s;
|
||||
}
|
||||
|
||||
if (args.outb && tpitg.x == ntg.x - 1) {
|
||||
device float * tmp_row = (device float *) tmp +
|
||||
args.net0*i01 +
|
||||
args.net0*args.net1*i02 +
|
||||
args.net0*args.net1*args.net2*i03;
|
||||
|
||||
tmp_row[ib] = s;
|
||||
}
|
||||
}
|
||||
|
||||
typedef decltype(kernel_cumsum_blk<float>) kernel_cumsum_blk_t;
|
||||
|
||||
template [[host_name("kernel_cumsum_blk_f32")]] kernel kernel_cumsum_blk_t kernel_cumsum_blk<float>;
|
||||
|
||||
template<typename T>
|
||||
kernel void kernel_cumsum_add(
|
||||
constant ggml_metal_kargs_cumsum_add & args,
|
||||
device const char * tmp,
|
||||
device char * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
ushort3 tpitg[[thread_position_in_threadgroup]],
|
||||
ushort sgitg[[simdgroup_index_in_threadgroup]],
|
||||
ushort tiisg[[thread_index_in_simdgroup]],
|
||||
ushort3 ntg[[threads_per_threadgroup]]) {
|
||||
const int ib = tgpig[0]/args.ne01;
|
||||
|
||||
if (ib == 0) {
|
||||
return;
|
||||
}
|
||||
|
||||
const int i00 = ib*ntg.x;
|
||||
const int i01 = tgpig[0]%args.ne01;
|
||||
const int i02 = tgpig[1];
|
||||
const int i03 = tgpig[2];
|
||||
|
||||
device const float * tmp_row = (device const float *) (tmp +
|
||||
args.nbt1*i01 +
|
||||
args.nbt2*i02 +
|
||||
args.nbt3*i03);
|
||||
|
||||
device float * dst_row = (device float *) dst +
|
||||
args.ne00*i01 +
|
||||
args.ne00*args.ne01*i02 +
|
||||
args.ne00*args.ne01*args.ne02*i03;
|
||||
|
||||
if (i00 + tpitg.x < args.ne00) {
|
||||
dst_row[i00 + tpitg.x] += tmp_row[ib - 1];
|
||||
}
|
||||
}
|
||||
|
||||
typedef decltype(kernel_cumsum_add<float>) kernel_cumsum_add_t;
|
||||
|
||||
template [[host_name("kernel_cumsum_add_f32")]] kernel kernel_cumsum_add_t kernel_cumsum_add<float>;
|
||||
@@ -0,0 +1,318 @@
|
||||
#include "common.h"
|
||||
|
||||
constant bool FC_rope_is_imrope [[function_constant(FC_ROPE + 0)]];
|
||||
constant bool FC_rope_is_back [[function_constant(FC_ROPE + 1)]];
|
||||
|
||||
static float rope_yarn_ramp(const float low, const float high, const int i0) {
|
||||
const float y = (i0 / 2 - low) / max(0.001f, high - low);
|
||||
return 1.0f - min(1.0f, max(0.0f, y));
|
||||
}
|
||||
|
||||
// YaRN algorithm based on LlamaYaRNScaledRotaryEmbedding.py from https://github.com/jquesnelle/yarn
|
||||
// MIT licensed. Copyright (c) 2023 Jeffrey Quesnelle and Bowen Peng.
|
||||
static void rope_yarn(
|
||||
float theta_extrap, float freq_scale, float corr_dims[2], int i0, float ext_factor, float mscale,
|
||||
thread float * cos_theta, thread float * sin_theta) {
|
||||
// Get n-d rotational scaling corrected for extrapolation
|
||||
float theta_interp = freq_scale * theta_extrap;
|
||||
float theta = theta_interp;
|
||||
if (ext_factor != 0.0f) {
|
||||
float ramp_mix = rope_yarn_ramp(corr_dims[0], corr_dims[1], i0) * ext_factor;
|
||||
theta = theta_interp * (1 - ramp_mix) + theta_extrap * ramp_mix;
|
||||
|
||||
// Get n-d magnitude scaling corrected for interpolation
|
||||
mscale *= 1.0f + 0.1f * log(1.0f / freq_scale);
|
||||
}
|
||||
*cos_theta = cos(theta) * mscale;
|
||||
*sin_theta = sin(theta) * mscale;
|
||||
if (FC_rope_is_back) {
|
||||
*sin_theta *= -1.0f;
|
||||
}
|
||||
}
|
||||
|
||||
// Apparently solving `n_rot = 2pi * x * base^((2 * max_pos_emb) / n_dims)` for x, we get
|
||||
// `corr_fac(n_rot) = n_dims * log(max_pos_emb / (n_rot * 2pi)) / (2 * log(base))`
|
||||
static float rope_yarn_corr_factor(int n_dims, int n_ctx_orig, float n_rot, float base) {
|
||||
return n_dims * log(n_ctx_orig / (n_rot * 2 * M_PI_F)) / (2 * log(base));
|
||||
}
|
||||
|
||||
static void rope_yarn_corr_dims(
|
||||
int n_dims, int n_ctx_orig, float freq_base, float beta_fast, float beta_slow, float dims[2]
|
||||
) {
|
||||
// start and end correction dims
|
||||
dims[0] = max(0.0f, floor(rope_yarn_corr_factor(n_dims, n_ctx_orig, beta_fast, freq_base)));
|
||||
dims[1] = min(n_dims - 1.0f, ceil(rope_yarn_corr_factor(n_dims, n_ctx_orig, beta_slow, freq_base)));
|
||||
}
|
||||
|
||||
template<typename T>
|
||||
kernel void kernel_rope_norm(
|
||||
constant ggml_metal_kargs_rope & args,
|
||||
device const char * src0,
|
||||
device const char * src1,
|
||||
device const char * src2,
|
||||
device char * dst,
|
||||
ushort tiitg[[thread_index_in_threadgroup]],
|
||||
ushort3 tptg [[threads_per_threadgroup]],
|
||||
uint3 tgpig[[threadgroup_position_in_grid]]) {
|
||||
const int i3 = tgpig[2];
|
||||
const int i2 = tgpig[1];
|
||||
const int i1 = tgpig[0];
|
||||
|
||||
float corr_dims[2];
|
||||
rope_yarn_corr_dims(args.n_dims, args.n_ctx_orig, args.freq_base, args.beta_fast, args.beta_slow, corr_dims);
|
||||
|
||||
device const int32_t * pos = (device const int32_t *) src1;
|
||||
|
||||
const float theta_base = (float) pos[i2];
|
||||
const float inv_ndims = -1.f/args.n_dims;
|
||||
|
||||
float cos_theta;
|
||||
float sin_theta;
|
||||
|
||||
for (int i0 = 2*tiitg; i0 < args.ne0; i0 += 2*tptg.x) {
|
||||
if (i0 < args.n_dims) {
|
||||
const int ic = i0/2;
|
||||
|
||||
const float theta = theta_base * pow(args.freq_base, inv_ndims*i0);
|
||||
|
||||
const float freq_factor = args.src2 ? ((device const float *) src2)[ic] : 1.0f;
|
||||
|
||||
rope_yarn(theta/freq_factor, args.freq_scale, corr_dims, i0, args.ext_factor, args.attn_factor, &cos_theta, &sin_theta);
|
||||
|
||||
device const T * const src = (device T *)(src0 + i3*args.nb03 + i2*args.nb02 + i1*args.nb01 + i0*args.nb00);
|
||||
device T * dst_data = (device T *)( dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1 + i0*args.nb0);
|
||||
|
||||
const float x0 = src[0];
|
||||
const float x1 = src[1];
|
||||
|
||||
dst_data[0] = x0*cos_theta - x1*sin_theta;
|
||||
dst_data[1] = x0*sin_theta + x1*cos_theta;
|
||||
} else {
|
||||
device const T * const src = (device T *)(src0 + i3*args.nb03 + i2*args.nb02 + i1*args.nb01 + i0*args.nb00);
|
||||
device T * dst_data = (device T *)( dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1 + i0*args.nb0);
|
||||
|
||||
dst_data[0] = src[0];
|
||||
dst_data[1] = src[1];
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
template<typename T>
|
||||
kernel void kernel_rope_neox(
|
||||
constant ggml_metal_kargs_rope & args,
|
||||
device const char * src0,
|
||||
device const char * src1,
|
||||
device const char * src2,
|
||||
device char * dst,
|
||||
ushort tiitg[[thread_index_in_threadgroup]],
|
||||
ushort3 tptg [[threads_per_threadgroup]],
|
||||
uint3 tgpig[[threadgroup_position_in_grid]]) {
|
||||
const int i3 = tgpig[2];
|
||||
const int i2 = tgpig[1];
|
||||
const int i1 = tgpig[0];
|
||||
|
||||
float corr_dims[2];
|
||||
rope_yarn_corr_dims(args.n_dims, args.n_ctx_orig, args.freq_base, args.beta_fast, args.beta_slow, corr_dims);
|
||||
|
||||
device const int32_t * pos = (device const int32_t *) src1;
|
||||
|
||||
const float theta_base = (float) pos[i2];
|
||||
const float inv_ndims = -1.f/args.n_dims;
|
||||
|
||||
float cos_theta;
|
||||
float sin_theta;
|
||||
|
||||
for (int i0 = 2*tiitg; i0 < args.ne0; i0 += 2*tptg.x) {
|
||||
if (i0 < args.n_dims) {
|
||||
const int ic = i0/2;
|
||||
|
||||
const float theta = theta_base * pow(args.freq_base, inv_ndims*i0);
|
||||
|
||||
const float freq_factor = args.src2 ? ((device const float *) src2)[ic] : 1.0f;
|
||||
|
||||
rope_yarn(theta/freq_factor, args.freq_scale, corr_dims, i0, args.ext_factor, args.attn_factor, &cos_theta, &sin_theta);
|
||||
|
||||
device const T * const src = (device T *)(src0 + i3*args.nb03 + i2*args.nb02 + i1*args.nb01 + ic*args.nb00);
|
||||
device T * dst_data = (device T *)( dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1 + ic*args.nb0);
|
||||
|
||||
const float x0 = src[0];
|
||||
const float x1 = src[args.n_dims/2];
|
||||
|
||||
dst_data[0] = x0*cos_theta - x1*sin_theta;
|
||||
dst_data[args.n_dims/2] = x0*sin_theta + x1*cos_theta;
|
||||
} else {
|
||||
device const T * const src = (device T *)(src0 + i3*args.nb03 + i2*args.nb02 + i1*args.nb01 + i0*args.nb00);
|
||||
device T * dst_data = (device T *)( dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1 + i0*args.nb0);
|
||||
|
||||
dst_data[0] = src[0];
|
||||
dst_data[1] = src[1];
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
template<typename T>
|
||||
kernel void kernel_rope_multi(
|
||||
constant ggml_metal_kargs_rope & args,
|
||||
device const char * src0,
|
||||
device const char * src1,
|
||||
device const char * src2,
|
||||
device char * dst,
|
||||
ushort tiitg[[thread_index_in_threadgroup]],
|
||||
ushort3 tptg [[threads_per_threadgroup]],
|
||||
uint3 tgpig[[threadgroup_position_in_grid]]) {
|
||||
const int i3 = tgpig[2];
|
||||
const int i2 = tgpig[1];
|
||||
const int i1 = tgpig[0];
|
||||
|
||||
float corr_dims[2];
|
||||
rope_yarn_corr_dims(args.n_dims, args.n_ctx_orig, args.freq_base, args.beta_fast, args.beta_slow, corr_dims);
|
||||
|
||||
device const int32_t * pos = (device const int32_t *) src1;
|
||||
|
||||
const float inv_ndims = -1.f/args.n_dims;
|
||||
|
||||
float cos_theta;
|
||||
float sin_theta;
|
||||
|
||||
for (int i0 = 2*tiitg; i0 < args.ne0; i0 += 2*tptg.x) {
|
||||
if (i0 < args.n_dims) {
|
||||
const int ic = i0/2;
|
||||
|
||||
// mrope theta calculations
|
||||
// note: the rest is the same as kernel_rope_neox
|
||||
const int sect_dims = args.sect_0 + args.sect_1 + args.sect_2 + args.sect_3;
|
||||
const int sec_w01 = args.sect_0 + args.sect_1; // end of section 1
|
||||
const int sec_w012 = args.sect_0 + args.sect_1 + args.sect_2; // end of section 2
|
||||
const int sector = ic % sect_dims;
|
||||
|
||||
float theta_base;
|
||||
if (FC_rope_is_imrope) {
|
||||
if (sector % 3 == 1 && sector < 3 * args.sect_1) { // h
|
||||
theta_base = (float) pos[i2 + args.ne02 * 1];
|
||||
} else if (sector % 3 == 2 && sector < 3 * args.sect_2) { // w
|
||||
theta_base = (float) pos[i2 + args.ne02 * 2];
|
||||
} else if (sector % 3 == 0 && sector < 3 * args.sect_0) { // t
|
||||
theta_base = (float) pos[i2 + args.ne02 * 0];
|
||||
} else { // e
|
||||
theta_base = (float) pos[i2 + args.ne02 * 3];
|
||||
}
|
||||
} else {
|
||||
if (sector < args.sect_0) {
|
||||
theta_base = (float) pos[i2];
|
||||
} else if (sector < sec_w01) {
|
||||
theta_base = (float) pos[i2 + args.ne02 * 1];
|
||||
} else if (sector < sec_w012) {
|
||||
theta_base = (float) pos[i2 + args.ne02 * 2];
|
||||
} else {
|
||||
theta_base = (float) pos[i2 + args.ne02 * 3];
|
||||
}
|
||||
}
|
||||
// end of mrope
|
||||
|
||||
const float theta = theta_base * pow(args.freq_base, inv_ndims*i0);
|
||||
|
||||
const float freq_factor = args.src2 ? ((device const float *) src2)[ic] : 1.0f;
|
||||
|
||||
rope_yarn(theta/freq_factor, args.freq_scale, corr_dims, i0, args.ext_factor, args.attn_factor, &cos_theta, &sin_theta);
|
||||
|
||||
device const T * const src = (device T *)(src0 + i3*args.nb03 + i2*args.nb02 + i1*args.nb01 + ic*args.nb00);
|
||||
device T * dst_data = (device T *)( dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1 + ic*args.nb0);
|
||||
|
||||
const float x0 = src[0];
|
||||
const float x1 = src[args.n_dims/2];
|
||||
|
||||
dst_data[0] = x0*cos_theta - x1*sin_theta;
|
||||
dst_data[args.n_dims/2] = x0*sin_theta + x1*cos_theta;
|
||||
} else {
|
||||
device const T * const src = (device T *)(src0 + i3*args.nb03 + i2*args.nb02 + i1*args.nb01 + i0*args.nb00);
|
||||
device T * dst_data = (device T *)( dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1 + i0*args.nb0);
|
||||
|
||||
dst_data[0] = src[0];
|
||||
dst_data[1] = src[1];
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
template<typename T>
|
||||
kernel void kernel_rope_vision(
|
||||
constant ggml_metal_kargs_rope & args,
|
||||
device const char * src0,
|
||||
device const char * src1,
|
||||
device const char * src2,
|
||||
device char * dst,
|
||||
ushort tiitg[[thread_index_in_threadgroup]],
|
||||
ushort3 tptg [[threads_per_threadgroup]],
|
||||
uint3 tgpig[[threadgroup_position_in_grid]]) {
|
||||
const int i3 = tgpig[2];
|
||||
const int i2 = tgpig[1];
|
||||
const int i1 = tgpig[0];
|
||||
|
||||
float corr_dims[2];
|
||||
rope_yarn_corr_dims(args.n_dims, args.n_ctx_orig, args.freq_base, args.beta_fast, args.beta_slow, corr_dims);
|
||||
|
||||
device const int32_t * pos = (device const int32_t *) src1;
|
||||
|
||||
const float inv_ndims = -1.f/args.n_dims;
|
||||
|
||||
float cos_theta;
|
||||
float sin_theta;
|
||||
|
||||
for (int i0 = 2*tiitg; i0 < args.ne0; i0 += 2*tptg.x) {
|
||||
if (i0 < 2*args.n_dims) { // different from kernel_rope_multi
|
||||
const int ic = i0/2;
|
||||
|
||||
// mrope theta calculations (only support 2 dimensions)
|
||||
const int sect_dims = args.sect_0 + args.sect_1;
|
||||
const int sector = ic % sect_dims;
|
||||
|
||||
float p;
|
||||
float theta_base;
|
||||
if (sector < args.sect_1) {
|
||||
p = (float) sector;
|
||||
theta_base = (float) pos[i2];
|
||||
} else {
|
||||
p = (float) sector - args.sect_0;
|
||||
theta_base = (float) pos[i2 + args.ne02];
|
||||
}
|
||||
|
||||
const float theta = theta_base * pow(args.freq_base, 2.0f * inv_ndims * p);
|
||||
// end of mrope
|
||||
|
||||
const float freq_factor = args.src2 ? ((device const float *) src2)[ic] : 1.0f;
|
||||
|
||||
rope_yarn(theta/freq_factor, args.freq_scale, corr_dims, i0, args.ext_factor, args.attn_factor, &cos_theta, &sin_theta);
|
||||
|
||||
device const T * const src = (device T *)(src0 + i3*args.nb03 + i2*args.nb02 + i1*args.nb01 + ic*args.nb00);
|
||||
device T * dst_data = (device T *)( dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1 + ic*args.nb0);
|
||||
|
||||
const float x0 = src[0];
|
||||
const float x1 = src[args.n_dims]; // different from kernel_rope_multi
|
||||
|
||||
dst_data[0] = x0*cos_theta - x1*sin_theta;
|
||||
dst_data[args.n_dims] = x0*sin_theta + x1*cos_theta; // different from kernel_rope_multi
|
||||
} else {
|
||||
device const T * const src = (device T *)(src0 + i3*args.nb03 + i2*args.nb02 + i1*args.nb01 + i0*args.nb00);
|
||||
device T * dst_data = (device T *)( dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1 + i0*args.nb0);
|
||||
|
||||
dst_data[0] = src[0];
|
||||
dst_data[1] = src[1];
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
typedef decltype(kernel_rope_norm<float>) kernel_rope_norm_t;
|
||||
typedef decltype(kernel_rope_neox<float>) kernel_rope_neox_t;
|
||||
typedef decltype(kernel_rope_multi<float>) kernel_rope_multi_t;
|
||||
typedef decltype(kernel_rope_vision<float>) kernel_rope_vision_t;
|
||||
|
||||
template [[host_name("kernel_rope_norm_f32")]] kernel kernel_rope_norm_t kernel_rope_norm<float>;
|
||||
template [[host_name("kernel_rope_norm_f16")]] kernel kernel_rope_norm_t kernel_rope_norm<half>;
|
||||
|
||||
template [[host_name("kernel_rope_neox_f32")]] kernel kernel_rope_neox_t kernel_rope_neox<float>;
|
||||
template [[host_name("kernel_rope_neox_f16")]] kernel kernel_rope_neox_t kernel_rope_neox<half>;
|
||||
|
||||
template [[host_name("kernel_rope_multi_f32")]] kernel kernel_rope_multi_t kernel_rope_multi<float>;
|
||||
template [[host_name("kernel_rope_multi_f16")]] kernel kernel_rope_multi_t kernel_rope_multi<half>;
|
||||
|
||||
template [[host_name("kernel_rope_vision_f32")]] kernel kernel_rope_vision_t kernel_rope_vision<float>;
|
||||
template [[host_name("kernel_rope_vision_f16")]] kernel kernel_rope_vision_t kernel_rope_vision<half>;
|
||||
@@ -0,0 +1,223 @@
|
||||
#include "common.h"
|
||||
|
||||
template<typename T>
|
||||
kernel void kernel_soft_max(
|
||||
constant ggml_metal_kargs_soft_max & args,
|
||||
device const char * src0,
|
||||
device const char * src1,
|
||||
device const char * src2,
|
||||
device char * dst,
|
||||
threadgroup float * buf [[threadgroup(0)]],
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
uint3 tpitg[[thread_position_in_threadgroup]],
|
||||
uint sgitg[[simdgroup_index_in_threadgroup]],
|
||||
uint tiisg[[thread_index_in_simdgroup]],
|
||||
uint3 tptg[[threads_per_threadgroup]]) {
|
||||
const int32_t i03 = tgpig.z;
|
||||
const int32_t i02 = tgpig.y;
|
||||
const int32_t i01 = tgpig.x;
|
||||
|
||||
const int32_t i13 = i03%args.ne13;
|
||||
const int32_t i12 = i02%args.ne12;
|
||||
const int32_t i11 = i01;
|
||||
|
||||
device const float * psrc0 = (device const float *) (src0 + i01*args.nb01 + i02*args.nb02 + i03*args.nb03);
|
||||
device const T * pmask = src1 != src0 ? (device const T * ) (src1 + i11*args.nb11 + i12*args.nb12 + i13*args.nb13) : nullptr;
|
||||
device const float * psrc2 = src2 != src0 ? (device const float *) (src2) : nullptr;
|
||||
device float * pdst = (device float *) (dst + i01*args.nb1 + i02*args.nb2 + i03*args.nb3);
|
||||
|
||||
float slope = 1.0f;
|
||||
|
||||
// ALiBi
|
||||
if (args.max_bias > 0.0f) {
|
||||
const int32_t h = i02;
|
||||
|
||||
const float base = h < args.n_head_log2 ? args.m0 : args.m1;
|
||||
const int exp = h < args.n_head_log2 ? h + 1 : 2*(h - args.n_head_log2) + 1;
|
||||
|
||||
slope = pow(base, exp);
|
||||
}
|
||||
|
||||
// parallel max
|
||||
float lmax = psrc2 ? psrc2[i02] : -INFINITY;
|
||||
|
||||
for (int i00 = tpitg.x; i00 < args.ne00; i00 += tptg.x) {
|
||||
lmax = MAX(lmax, psrc0[i00]*args.scale + (pmask ? slope*pmask[i00] : 0.0f));
|
||||
}
|
||||
|
||||
// find the max value in the block
|
||||
float max_val = simd_max(lmax);
|
||||
if (tptg.x > N_SIMDWIDTH) {
|
||||
if (sgitg == 0) {
|
||||
buf[tiisg] = -INFINITY;
|
||||
}
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
if (tiisg == 0) {
|
||||
buf[sgitg] = max_val;
|
||||
}
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
max_val = buf[tiisg];
|
||||
max_val = simd_max(max_val);
|
||||
}
|
||||
|
||||
// parallel sum
|
||||
float lsum = 0.0f;
|
||||
for (int i00 = tpitg.x; i00 < args.ne00; i00 += tptg.x) {
|
||||
const float exp_psrc0 = exp((psrc0[i00]*args.scale + (pmask ? slope*pmask[i00] : 0.0f)) - max_val);
|
||||
lsum += exp_psrc0;
|
||||
pdst[i00] = exp_psrc0;
|
||||
}
|
||||
|
||||
// This barrier fixes a failing test
|
||||
// ref: https://github.com/ggml-org/ggml/pull/621#discussion_r1425156335
|
||||
threadgroup_barrier(mem_flags::mem_none);
|
||||
|
||||
float sum = simd_sum(lsum);
|
||||
|
||||
if (tptg.x > N_SIMDWIDTH) {
|
||||
if (sgitg == 0) {
|
||||
buf[tiisg] = 0.0f;
|
||||
}
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
if (tiisg == 0) {
|
||||
buf[sgitg] = sum;
|
||||
}
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
sum = buf[tiisg];
|
||||
sum = simd_sum(sum);
|
||||
}
|
||||
|
||||
if (psrc2) {
|
||||
sum += exp(psrc2[i02] - max_val);
|
||||
}
|
||||
|
||||
const float inv_sum = 1.0f/sum;
|
||||
|
||||
for (int i00 = tpitg.x; i00 < args.ne00; i00 += tptg.x) {
|
||||
pdst[i00] *= inv_sum;
|
||||
}
|
||||
}
|
||||
|
||||
template<typename T>
|
||||
kernel void kernel_soft_max_4(
|
||||
constant ggml_metal_kargs_soft_max & args,
|
||||
device const char * src0,
|
||||
device const char * src1,
|
||||
device const char * src2,
|
||||
device char * dst,
|
||||
threadgroup float * buf [[threadgroup(0)]],
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
uint3 tpitg[[thread_position_in_threadgroup]],
|
||||
uint sgitg[[simdgroup_index_in_threadgroup]],
|
||||
uint tiisg[[thread_index_in_simdgroup]],
|
||||
uint3 tptg[[threads_per_threadgroup]]) {
|
||||
const int32_t i03 = tgpig.z;
|
||||
const int32_t i02 = tgpig.y;
|
||||
const int32_t i01 = tgpig.x;
|
||||
|
||||
const int32_t i13 = i03%args.ne13;
|
||||
const int32_t i12 = i02%args.ne12;
|
||||
const int32_t i11 = i01;
|
||||
|
||||
device const float4 * psrc4 = (device const float4 *) (src0 + i01*args.nb01 + i02*args.nb02 + i03*args.nb03);
|
||||
device const T * pmask = src1 != src0 ? (device const T * ) (src1 + i11*args.nb11 + i12*args.nb12 + i13*args.nb13) : nullptr;
|
||||
device const float * psrc2 = src2 != src0 ? (device const float * ) (src2) : nullptr;
|
||||
device float4 * pdst4 = (device float4 *) (dst + i01*args.nb1 + i02*args.nb2 + i03*args.nb3);
|
||||
|
||||
float slope = 1.0f;
|
||||
|
||||
if (args.max_bias > 0.0f) {
|
||||
const int32_t h = i02;
|
||||
|
||||
const float base = h < args.n_head_log2 ? args.m0 : args.m1;
|
||||
const int exp = h < args.n_head_log2 ? h + 1 : 2*(h - args.n_head_log2) + 1;
|
||||
|
||||
slope = pow(base, exp);
|
||||
}
|
||||
|
||||
// parallel max
|
||||
float4 lmax4 = psrc2 ? psrc2[i02] : -INFINITY;
|
||||
|
||||
for (int i00 = tpitg.x; i00 < args.ne00/4; i00 += tptg.x) {
|
||||
lmax4 = fmax(lmax4, psrc4[i00]*args.scale + (float4)((pmask ? slope*pmask[i00] : 0.0f)));
|
||||
}
|
||||
|
||||
const float lmax = MAX(MAX(lmax4[0], lmax4[1]), MAX(lmax4[2], lmax4[3]));
|
||||
|
||||
float max_val = simd_max(lmax);
|
||||
if (tptg.x > N_SIMDWIDTH) {
|
||||
if (sgitg == 0) {
|
||||
buf[tiisg] = -INFINITY;
|
||||
}
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
if (tiisg == 0) {
|
||||
buf[sgitg] = max_val;
|
||||
}
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
max_val = buf[tiisg];
|
||||
max_val = simd_max(max_val);
|
||||
}
|
||||
|
||||
// parallel sum
|
||||
float4 lsum4 = 0.0f;
|
||||
for (int i00 = tpitg.x; i00 < args.ne00/4; i00 += tptg.x) {
|
||||
const float4 exp_psrc4 = exp((psrc4[i00]*args.scale + (float4)((pmask ? slope*pmask[i00] : 0.0f))) - max_val);
|
||||
lsum4 += exp_psrc4;
|
||||
pdst4[i00] = exp_psrc4;
|
||||
}
|
||||
|
||||
const float lsum = lsum4[0] + lsum4[1] + lsum4[2] + lsum4[3];
|
||||
|
||||
// This barrier fixes a failing test
|
||||
// ref: https://github.com/ggml-org/ggml/pull/621#discussion_r1425156335
|
||||
threadgroup_barrier(mem_flags::mem_none);
|
||||
|
||||
float sum = simd_sum(lsum);
|
||||
|
||||
if (tptg.x > N_SIMDWIDTH) {
|
||||
if (sgitg == 0) {
|
||||
buf[tiisg] = 0.0f;
|
||||
}
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
if (tiisg == 0) {
|
||||
buf[sgitg] = sum;
|
||||
}
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
sum = buf[tiisg];
|
||||
sum = simd_sum(sum);
|
||||
}
|
||||
|
||||
if (psrc2) {
|
||||
sum += exp(psrc2[i02] - max_val);
|
||||
}
|
||||
|
||||
const float inv_sum = 1.0f/sum;
|
||||
|
||||
for (int i00 = tpitg.x; i00 < args.ne00/4; i00 += tptg.x) {
|
||||
pdst4[i00] *= inv_sum;
|
||||
}
|
||||
}
|
||||
|
||||
typedef decltype(kernel_soft_max<float>) kernel_soft_max_t;
|
||||
typedef decltype(kernel_soft_max_4<float4>) kernel_soft_max_4_t;
|
||||
|
||||
template [[host_name("kernel_soft_max_f16")]] kernel kernel_soft_max_t kernel_soft_max<half>;
|
||||
template [[host_name("kernel_soft_max_f32")]] kernel kernel_soft_max_t kernel_soft_max<float>;
|
||||
template [[host_name("kernel_soft_max_f16_4")]] kernel kernel_soft_max_4_t kernel_soft_max_4<half4>;
|
||||
template [[host_name("kernel_soft_max_f32_4")]] kernel kernel_soft_max_4_t kernel_soft_max_4<float4>;
|
||||
@@ -0,0 +1,75 @@
|
||||
#include "common.h"
|
||||
|
||||
constant short FC_solve_tri_nsg [[function_constant(FC_SOLVE_TRI + 0)]];
|
||||
constant short FC_solve_tri_n [[function_constant(FC_SOLVE_TRI + 1)]];
|
||||
constant short FC_solve_tri_k [[function_constant(FC_SOLVE_TRI + 2)]];
|
||||
|
||||
kernel void kernel_solve_tri_f32(
|
||||
constant ggml_metal_kargs_solve_tri & args,
|
||||
device const char * src0,
|
||||
device const char * src1,
|
||||
device char * dst,
|
||||
threadgroup char * shmem [[threadgroup(0)]],
|
||||
ushort3 tgpig[[threadgroup_position_in_grid]],
|
||||
ushort sgitg[[simdgroup_index_in_threadgroup]],
|
||||
ushort tiisg[[thread_index_in_simdgroup]],
|
||||
ushort3 ntg[[threads_per_threadgroup]]) {
|
||||
constexpr short NW = N_SIMDWIDTH;
|
||||
|
||||
const short NSG = FC_solve_tri_nsg;
|
||||
const short N = FC_solve_tri_n;
|
||||
const short K = FC_solve_tri_k;
|
||||
const short NP = PAD2(N, NW);
|
||||
|
||||
const int32_t i03 = tgpig.z;
|
||||
const int32_t i02 = tgpig.y;
|
||||
const int32_t i01 = tgpig.x*NSG + sgitg;
|
||||
|
||||
threadgroup float * sh0 = (threadgroup float *) shmem;
|
||||
|
||||
device const float * src0_ptr = (device const float *)(src0 + i02 * args.nb02 + i03 * args.nb03) + sgitg*N;
|
||||
device const float * src1_ptr = (device const float *)(src1 + i02 * args.nb12 + i03 * args.nb13) + i01;
|
||||
device float * dst_ptr = (device float *)(dst + i02 * args.nb2 + i03 * args.nb3) + i01;
|
||||
|
||||
for (short rr = 0; rr < N; rr += NSG) {
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
{
|
||||
threadgroup float * sh0_cur = sh0 + sgitg*NP;
|
||||
|
||||
for (short t = 0; t*NW < N; ++t) {
|
||||
const short idx = t*NW + tiisg;
|
||||
sh0_cur[idx] = src0_ptr[idx];
|
||||
}
|
||||
|
||||
src0_ptr += NSG*N;
|
||||
}
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
if (i01 >= args.ne10) {
|
||||
continue;
|
||||
}
|
||||
|
||||
for (short ir = 0; ir < NSG && rr + ir < N; ++ir) {
|
||||
const short r = rr + ir;
|
||||
|
||||
threadgroup float * sh0_cur = sh0 + ir*NP;
|
||||
|
||||
float sum = 0.0f;
|
||||
|
||||
for (short t = 0; t*NW < r; ++t) {
|
||||
const short idx = t*NW + tiisg;
|
||||
sum += sh0_cur[idx] * dst_ptr[idx*K] * (idx < r);
|
||||
}
|
||||
|
||||
sum = simd_sum(sum);
|
||||
|
||||
if (tiisg == 0) {
|
||||
const float diag = sh0_cur[r];
|
||||
|
||||
dst_ptr[r*K] = (src1_ptr[r*K] - sum) / diag;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,279 @@
|
||||
#include "common.h"
|
||||
|
||||
// ref: ggml.c:ggml_compute_forward_ssm_conv_f32
|
||||
kernel void kernel_ssm_conv_f32_f32(
|
||||
constant ggml_metal_kargs_ssm_conv & args,
|
||||
device const void * src0,
|
||||
device const void * src1,
|
||||
device float * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
uint3 tpitg[[thread_position_in_threadgroup]],
|
||||
uint3 ntg[[threads_per_threadgroup]]) {
|
||||
const int64_t ir = tgpig.x;
|
||||
const int64_t i2 = tgpig.y;
|
||||
const int64_t i3 = tgpig.z;
|
||||
|
||||
const int64_t nc = args.ne10;
|
||||
//const int64_t ncs = args.ne00;
|
||||
//const int64_t nr = args.ne01;
|
||||
//const int64_t n_t = args.ne1;
|
||||
//const int64_t n_s = args.ne2;
|
||||
|
||||
device const float * s = (device const float *) ((device const char *) src0 + ir*args.nb01 + i2*args.nb00 + i3*args.nb02);
|
||||
device const float * c = (device const float *) ((device const char *) src1 + ir*args.nb11);
|
||||
device float * x = (device float *) ((device char *) dst + ir*args.nb0 + i2*args.nb1 + i3*args.nb2);
|
||||
|
||||
float sumf = 0.0f;
|
||||
|
||||
for (int64_t i0 = 0; i0 < nc; ++i0) {
|
||||
sumf += s[i0] * c[i0];
|
||||
}
|
||||
|
||||
x[0] = sumf;
|
||||
}
|
||||
|
||||
kernel void kernel_ssm_conv_f32_f32_4(
|
||||
constant ggml_metal_kargs_ssm_conv & args,
|
||||
device const void * src0,
|
||||
device const void * src1,
|
||||
device float * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
uint3 tpitg[[thread_position_in_threadgroup]],
|
||||
uint3 ntg[[threads_per_threadgroup]]) {
|
||||
const int64_t ir = tgpig.x;
|
||||
const int64_t i2 = tgpig.y;
|
||||
const int64_t i3 = tgpig.z;
|
||||
|
||||
const int64_t nc = args.ne10;
|
||||
//const int64_t ncs = args.ne00;
|
||||
//const int64_t nr = args.ne01;
|
||||
//const int64_t n_t = args.ne1;
|
||||
//const int64_t n_s = args.ne2;
|
||||
|
||||
device const float4 * s = (device const float4 *) ((device const char *) src0 + ir*args.nb01 + i2*args.nb00 + i3*args.nb02);
|
||||
device const float4 * c = (device const float4 *) ((device const char *) src1 + ir*args.nb11);
|
||||
device float * x = (device float *) ((device char *) dst + ir*args.nb0 + i2*args.nb1 + i3*args.nb2);
|
||||
|
||||
float sumf = 0.0f;
|
||||
|
||||
for (int64_t i0 = 0; i0 < nc/4; ++i0) {
|
||||
sumf += dot(s[i0], c[i0]);
|
||||
}
|
||||
|
||||
x[0] = sumf;
|
||||
}
|
||||
|
||||
constant short FC_ssm_conv_bs [[function_constant(FC_SSM_CONV + 0)]];
|
||||
|
||||
// Batched version: each threadgroup processes multiple tokens for better efficiency
|
||||
// Thread layout: each thread handles one token, threadgroup covers BATCH_SIZE tokens
|
||||
kernel void kernel_ssm_conv_f32_f32_batched(
|
||||
constant ggml_metal_kargs_ssm_conv & args,
|
||||
device const void * src0,
|
||||
device const void * src1,
|
||||
device float * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
uint3 tpitg[[thread_position_in_threadgroup]],
|
||||
uint3 ntg[[threads_per_threadgroup]]) {
|
||||
// tgpig.x = row index (ir)
|
||||
// tgpig.y = batch of tokens (i2_base / BATCH_SIZE)
|
||||
// tgpig.z = sequence index (i3)
|
||||
// tpitg.x = thread within batch (0..BATCH_SIZE-1)
|
||||
const short BATCH_SIZE = FC_ssm_conv_bs;
|
||||
|
||||
const int64_t ir = tgpig.x;
|
||||
const int64_t i2_base = tgpig.y * BATCH_SIZE;
|
||||
const int64_t i3 = tgpig.z;
|
||||
const int64_t i2_off = tpitg.x;
|
||||
const int64_t i2 = i2_base + i2_off;
|
||||
|
||||
const int64_t nc = args.ne10; // conv kernel size (typically 4)
|
||||
const int64_t n_t = args.ne1; // number of tokens
|
||||
|
||||
// Bounds check for partial batches at the end
|
||||
if (i2 >= n_t) {
|
||||
return;
|
||||
}
|
||||
|
||||
// Load conv weights (shared across all tokens for this row)
|
||||
device const float * c = (device const float *) ((device const char *) src1 + ir*args.nb11);
|
||||
|
||||
// Load source for this specific token
|
||||
device const float * s = (device const float *) ((device const char *) src0 + ir*args.nb01 + i2*args.nb00 + i3*args.nb02);
|
||||
|
||||
// Output location for this token
|
||||
device float * x = (device float *) ((device char *) dst + ir*args.nb0 + i2*args.nb1 + i3*args.nb2);
|
||||
|
||||
float sumf = 0.0f;
|
||||
for (int64_t i0 = 0; i0 < nc; ++i0) {
|
||||
sumf += s[i0] * c[i0];
|
||||
}
|
||||
|
||||
x[0] = sumf;
|
||||
}
|
||||
|
||||
kernel void kernel_ssm_conv_f32_f32_batched_4(
|
||||
constant ggml_metal_kargs_ssm_conv & args,
|
||||
device const void * src0,
|
||||
device const void * src1,
|
||||
device float * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
uint3 tpitg[[thread_position_in_threadgroup]],
|
||||
uint3 ntg[[threads_per_threadgroup]]) {
|
||||
// tgpig.x = row index (ir)
|
||||
// tgpig.y = batch of tokens (i2_base / BATCH_SIZE)
|
||||
// tgpig.z = sequence index (i3)
|
||||
// tpitg.x = thread within batch (0..BATCH_SIZE-1)
|
||||
const short BATCH_SIZE = FC_ssm_conv_bs;
|
||||
|
||||
const int64_t ir = tgpig.x;
|
||||
const int64_t i2_base = tgpig.y * BATCH_SIZE;
|
||||
const int64_t i3 = tgpig.z;
|
||||
const int64_t i2_off = tpitg.x;
|
||||
const int64_t i2 = i2_base + i2_off;
|
||||
|
||||
const int64_t nc = args.ne10; // conv kernel size (typically 4)
|
||||
const int64_t n_t = args.ne1; // number of tokens
|
||||
|
||||
// Bounds check for partial batches at the end
|
||||
if (i2 >= n_t) {
|
||||
return;
|
||||
}
|
||||
|
||||
// Load conv weights (shared across all tokens for this row)
|
||||
device const float4 * c = (device const float4 *) ((device const char *) src1 + ir*args.nb11);
|
||||
|
||||
// Load source for this specific token
|
||||
device const float4 * s = (device const float4 *) ((device const char *) src0 + ir*args.nb01 + i2*args.nb00 + i3*args.nb02);
|
||||
|
||||
// Output location for this token
|
||||
device float * x = (device float *) ((device char *) dst + ir*args.nb0 + i2*args.nb1 + i3*args.nb2);
|
||||
|
||||
float sumf = 0.0f;
|
||||
for (int64_t i0 = 0; i0 < nc/4; ++i0) {
|
||||
sumf += dot(s[i0], c[i0]);
|
||||
}
|
||||
|
||||
x[0] = sumf;
|
||||
}
|
||||
|
||||
// ref: ggml.c:ggml_compute_forward_ssm_scan_f32, Mamba-2 part
|
||||
// Optimized version: reduces redundant memory loads by having one thread load shared values
|
||||
kernel void kernel_ssm_scan_f32(
|
||||
constant ggml_metal_kargs_ssm_scan & args,
|
||||
device const void * src0,
|
||||
device const void * src1,
|
||||
device const void * src2,
|
||||
device const void * src3,
|
||||
device const void * src4,
|
||||
device const void * src5,
|
||||
device const void * src6,
|
||||
device float * dst,
|
||||
threadgroup float * shared [[threadgroup(0)]],
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
ushort3 tpitg[[thread_position_in_threadgroup]],
|
||||
ushort sgitg[[simdgroup_index_in_threadgroup]],
|
||||
ushort tiisg[[thread_index_in_simdgroup]],
|
||||
ushort sgptg[[simdgroups_per_threadgroup]],
|
||||
uint3 tgpg[[threadgroups_per_grid]]) {
|
||||
constexpr short NW = N_SIMDWIDTH;
|
||||
|
||||
// Shared memory layout:
|
||||
// [0..sgptg*NW-1]: partial sums for reduction (existing)
|
||||
// [sgptg*NW..sgptg*NW+sgptg-1]: pre-computed x_dt values for each token in batch
|
||||
// [sgptg*NW+sgptg..sgptg*NW+2*sgptg-1]: pre-computed dA values for each token in batch
|
||||
threadgroup float * shared_sums = shared;
|
||||
threadgroup float * shared_x_dt = shared + sgptg * NW;
|
||||
threadgroup float * shared_dA = shared + sgptg * NW + sgptg;
|
||||
|
||||
shared_sums[tpitg.x] = 0.0f;
|
||||
|
||||
const int32_t i0 = tpitg.x;
|
||||
const int32_t i1 = tgpig.x;
|
||||
const int32_t ir = tgpig.y; // current head
|
||||
const int32_t i3 = tgpig.z; // current seq
|
||||
|
||||
const int32_t nc = args.d_state;
|
||||
const int32_t nr = args.d_inner;
|
||||
const int32_t nh = args.n_head;
|
||||
const int32_t ng = args.n_group;
|
||||
const int32_t n_t = args.n_seq_tokens;
|
||||
|
||||
const int32_t s_off = args.s_off;
|
||||
|
||||
device const int32_t * ids = (device const int32_t *) src6;
|
||||
|
||||
device const float * s0_buff = (device const float *) ((device const char *) src0 + ir*args.nb02 + ids[i3]*args.nb03);
|
||||
device float * s_buff = (device float *) ((device char *) dst + ir*args.nb02 + i3*args.nb03 + s_off);
|
||||
|
||||
const int32_t i = i0 + i1*nc;
|
||||
const int32_t g = ir / (nh / ng); // repeat_interleave
|
||||
|
||||
float s0 = s0_buff[i];
|
||||
float s = 0.0f;
|
||||
|
||||
device const float * A = (device const float *) ((device const char *) src3 + ir*args.nb31); // {ne30, nh}
|
||||
|
||||
const float A0 = A[i0%args.ne30];
|
||||
|
||||
device const float * x = (device const float *)((device const char *) src1 + i1*args.nb10 + ir*args.nb11 + i3*args.nb13); // {dim, nh, nt, ns}
|
||||
device const float * dt = (device const float *)((device const char *) src2 + ir*args.nb20 + i3*args.nb22); // {nh, nt, ns}
|
||||
device const float * B = (device const float *)((device const char *) src4 + g*args.nb41 + i3*args.nb43); // {d_state, ng, nt, ns}
|
||||
device const float * C = (device const float *)((device const char *) src5 + g*args.nb51 + i3*args.nb53); // {d_state, ng, nt, ns}
|
||||
|
||||
device float * y = dst + (i1 + ir*(nr) + i3*(n_t*nh*nr)); // {dim, nh, nt, ns}
|
||||
|
||||
for (int i2 = 0; i2 < n_t; i2 += sgptg) {
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
// Pre-compute x_dt and dA for this batch of tokens
|
||||
// Only first sgptg threads do the loads and expensive math
|
||||
if (i0 < sgptg && i2 + i0 < n_t) {
|
||||
// ns12 and ns21 are element strides (nb12/nb10, nb21/nb20)
|
||||
device const float * x_t = x + i0 * args.ns12;
|
||||
device const float * dt_t = dt + i0 * args.ns21;
|
||||
|
||||
const float dt0 = dt_t[0];
|
||||
const float dtsp = dt0 <= 20.0f ? log(1.0f + exp(dt0)) : dt0;
|
||||
shared_x_dt[i0] = x_t[0] * dtsp;
|
||||
shared_dA[i0] = dtsp; // Store dtsp, compute exp(dtsp * A0) per-thread since A0 varies
|
||||
}
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
for (int t = 0; t < sgptg && i2 + t < n_t; t++) {
|
||||
const float x_dt = shared_x_dt[t];
|
||||
const float dA = exp(shared_dA[t] * A0);
|
||||
|
||||
s = (s0 * dA) + (B[i0] * x_dt);
|
||||
|
||||
const float sumf = simd_sum(s * C[i0]);
|
||||
|
||||
if (tiisg == 0) {
|
||||
shared_sums[t*NW + sgitg] = sumf;
|
||||
}
|
||||
|
||||
// recurse
|
||||
s0 = s;
|
||||
|
||||
B += args.ns42;
|
||||
C += args.ns52;
|
||||
}
|
||||
|
||||
// Advance pointers for next batch
|
||||
x += sgptg * args.ns12;
|
||||
dt += sgptg * args.ns21;
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
const float sumf = simd_sum(shared_sums[sgitg*NW + tiisg]);
|
||||
|
||||
if (tiisg == 0 && i2 + sgitg < n_t) {
|
||||
y[sgitg*nh*nr] = sumf;
|
||||
}
|
||||
|
||||
y += sgptg*nh*nr;
|
||||
}
|
||||
|
||||
s_buff[i] = s;
|
||||
}
|
||||
@@ -0,0 +1,69 @@
|
||||
#include "common.h"
|
||||
|
||||
template<uint32_t ttype>
|
||||
bool _ggml_vec_tri_cmp(const int i, const int r);
|
||||
|
||||
template<>
|
||||
bool _ggml_vec_tri_cmp</* GGML_TRI_TYPE_LOWER */ 3>(const int i, const int r) {
|
||||
return i < r;
|
||||
}
|
||||
|
||||
template<>
|
||||
bool _ggml_vec_tri_cmp</* GGML_TRI_TYPE_LOWER_DIAG */ 2>(const int i, const int r) {
|
||||
return i <= r;
|
||||
}
|
||||
|
||||
template<>
|
||||
bool _ggml_vec_tri_cmp</* GGML_TRI_TYPE_UPPER */ 1>(const int i, const int r) {
|
||||
return i > r;
|
||||
}
|
||||
|
||||
template<>
|
||||
bool _ggml_vec_tri_cmp</* GGML_TRI_TYPE_UPPER_DIAG */ 0>(const int i, const int r) {
|
||||
return i >= r;
|
||||
}
|
||||
|
||||
template<typename T, int ttype>
|
||||
kernel void kernel_tri(
|
||||
constant ggml_metal_kargs_tri & args,
|
||||
device const char * src0,
|
||||
device const char * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
ushort3 tpitg[[thread_position_in_threadgroup]],
|
||||
ushort3 ntg[[threads_per_threadgroup]]) {
|
||||
const int i3 = tgpig.z;
|
||||
const int i2 = tgpig.y;
|
||||
const int i1 = tgpig.x;
|
||||
|
||||
if (i3 >= args.ne03 || i2 >= args.ne02 || i1 >= args.ne01) {
|
||||
return;
|
||||
}
|
||||
|
||||
device const T * src_row = (device const T *) ((device const char *) src0 + i1*args.nb01 + i2*args.nb02 + i3*args.nb03);
|
||||
device T * dst_row = (device T *) ((device char *) dst + i1*args.nb1 + i2*args.nb2 + i3*args.nb3);
|
||||
|
||||
// Each thread is a single element of the row if ne00 < max threads per
|
||||
// threadgroup, so this will loop once for each index that this thread is
|
||||
// responsible for
|
||||
for (int64_t i0 = tpitg.x; i0 < args.ne00; i0 += ntg.x) {
|
||||
// Use the comparison as a mask for branchless
|
||||
dst_row[i0] = static_cast<T>(_ggml_vec_tri_cmp<ttype>(i0, i1)) * src_row[i0];
|
||||
}
|
||||
}
|
||||
|
||||
typedef decltype(kernel_tri<float, 0>) kernel_tri_t;
|
||||
|
||||
template [[host_name("kernel_tri_f32_0")]] kernel kernel_tri_t kernel_tri<float, 0>;
|
||||
template [[host_name("kernel_tri_f32_1")]] kernel kernel_tri_t kernel_tri<float, 1>;
|
||||
template [[host_name("kernel_tri_f32_2")]] kernel kernel_tri_t kernel_tri<float, 2>;
|
||||
template [[host_name("kernel_tri_f32_3")]] kernel kernel_tri_t kernel_tri<float, 3>;
|
||||
template [[host_name("kernel_tri_f16_0")]] kernel kernel_tri_t kernel_tri<half, 0>;
|
||||
template [[host_name("kernel_tri_f16_1")]] kernel kernel_tri_t kernel_tri<half, 1>;
|
||||
template [[host_name("kernel_tri_f16_2")]] kernel kernel_tri_t kernel_tri<half, 2>;
|
||||
template [[host_name("kernel_tri_f16_3")]] kernel kernel_tri_t kernel_tri<half, 3>;
|
||||
#if defined(GGML_METAL_HAS_BF16)
|
||||
template [[host_name("kernel_tri_bf16_0")]] kernel kernel_tri_t kernel_tri<bfloat, 0>;
|
||||
template [[host_name("kernel_tri_bf16_1")]] kernel kernel_tri_t kernel_tri<bfloat, 1>;
|
||||
template [[host_name("kernel_tri_bf16_2")]] kernel kernel_tri_t kernel_tri<bfloat, 2>;
|
||||
template [[host_name("kernel_tri_bf16_3")]] kernel kernel_tri_t kernel_tri<bfloat, 3>;
|
||||
#endif
|
||||
@@ -0,0 +1,360 @@
|
||||
#include "common.h"
|
||||
|
||||
constant short FC_unary_op [[function_constant(FC_UNARY + 0)]];
|
||||
constant bool FC_unary_cnt[[function_constant(FC_UNARY + 1)]];
|
||||
|
||||
template <typename T0, typename T, typename TC>
|
||||
kernel void kernel_unary_impl(
|
||||
constant ggml_metal_kargs_unary & args,
|
||||
device const char * src0,
|
||||
device char * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
ushort3 tpitg[[thread_position_in_threadgroup]],
|
||||
ushort3 ntg[[threads_per_threadgroup]]) {
|
||||
#define FC_OP FC_unary_op
|
||||
#define FC_CNT FC_unary_cnt
|
||||
|
||||
device const T0 * src0_ptr;
|
||||
device T * dst_ptr;
|
||||
|
||||
int i0;
|
||||
|
||||
if (FC_CNT) {
|
||||
i0 = tgpig.x;
|
||||
|
||||
src0_ptr = (device const T0 *) (src0);
|
||||
dst_ptr = (device T *) (dst);
|
||||
} else {
|
||||
const int i03 = tgpig.z;
|
||||
const int i02 = tgpig.y;
|
||||
const int k0 = tgpig.x/args.ne01;
|
||||
const int i01 = tgpig.x - k0*args.ne01;
|
||||
|
||||
i0 = k0*ntg.x + tpitg.x;
|
||||
|
||||
src0_ptr = (device const T0 *) (src0 + i03*args.nb03 + i02*args.nb02 + i01*args.nb01);
|
||||
dst_ptr = (device T *) (dst + i03*args.nb3 + i02*args.nb2 + i01*args.nb1 );
|
||||
}
|
||||
|
||||
{
|
||||
//threadgroup_barrier(mem_flags::mem_none);
|
||||
|
||||
if (!FC_CNT) {
|
||||
if (i0 >= args.ne0) {
|
||||
return;
|
||||
}
|
||||
}
|
||||
|
||||
const TC x = (TC) src0_ptr[i0];
|
||||
|
||||
if (FC_OP == OP_UNARY_NUM_SCALE) {
|
||||
dst_ptr[i0] = (T) (args.scale * x + args.bias);
|
||||
}
|
||||
|
||||
if (FC_OP == OP_UNARY_NUM_FILL) {
|
||||
dst_ptr[i0] = (T) args.val;
|
||||
}
|
||||
|
||||
if (FC_OP == OP_UNARY_NUM_CLAMP) {
|
||||
dst_ptr[i0] = (T) clamp(x, args.min, args.max);
|
||||
}
|
||||
|
||||
if (FC_OP == OP_UNARY_NUM_SQR) {
|
||||
dst_ptr[i0] = (T) (x * x);
|
||||
}
|
||||
|
||||
if (FC_OP == OP_UNARY_NUM_SQRT) {
|
||||
dst_ptr[i0] = (T) sqrt(x);
|
||||
}
|
||||
|
||||
if (FC_OP == OP_UNARY_NUM_SIN) {
|
||||
dst_ptr[i0] = (T) sin(x);
|
||||
}
|
||||
|
||||
if (FC_OP == OP_UNARY_NUM_COS) {
|
||||
dst_ptr[i0] = (T) cos(x);
|
||||
}
|
||||
|
||||
if (FC_OP == OP_UNARY_NUM_LOG) {
|
||||
dst_ptr[i0] = (T) log(x);
|
||||
}
|
||||
|
||||
if (FC_OP == OP_UNARY_NUM_LEAKY_RELU) {
|
||||
dst_ptr[i0] = (T) (TC(x > 0)*x + TC(x <= 0)*(x * args.slope));
|
||||
}
|
||||
|
||||
if (FC_OP == OP_UNARY_NUM_TANH) {
|
||||
dst_ptr[i0] = (T) precise::tanh(x);
|
||||
}
|
||||
|
||||
if (FC_OP == OP_UNARY_NUM_RELU) {
|
||||
dst_ptr[i0] = (T) fmax(0, x);
|
||||
}
|
||||
|
||||
if (FC_OP == OP_UNARY_NUM_SIGMOID) {
|
||||
dst_ptr[i0] = (T) (1 / (1 + exp(-x)));
|
||||
}
|
||||
|
||||
if (FC_OP == OP_UNARY_NUM_GELU) {
|
||||
dst_ptr[i0] = (T) (0.5*x*(1 + precise::tanh(SQRT_2_OVER_PI*x*(1 + GELU_COEF_A*x*x))));
|
||||
}
|
||||
|
||||
if (FC_OP == OP_UNARY_NUM_GELU_ERF) {
|
||||
dst_ptr[i0] = (T) (0.5*x*(1 + erf_approx(SQRT_2_INV*x)));
|
||||
}
|
||||
|
||||
if (FC_OP == OP_UNARY_NUM_GELU_QUICK) {
|
||||
dst_ptr[i0] = (T) (x * (1/(1 + exp(GELU_QUICK_COEF*x))));
|
||||
}
|
||||
|
||||
if (FC_OP == OP_UNARY_NUM_SILU) {
|
||||
dst_ptr[i0] = (T) (x / (1 + exp(-x)));
|
||||
}
|
||||
|
||||
if (FC_OP == OP_UNARY_NUM_ELU) {
|
||||
dst_ptr[i0] = (T) elu_approx(x);
|
||||
}
|
||||
|
||||
if (FC_OP == OP_UNARY_NUM_NEG) {
|
||||
dst_ptr[i0] = (T) -x;
|
||||
}
|
||||
|
||||
if (FC_OP == OP_UNARY_NUM_ABS) {
|
||||
dst_ptr[i0] = (T) fabs(x);
|
||||
}
|
||||
|
||||
if (FC_OP == OP_UNARY_NUM_SGN) {
|
||||
dst_ptr[i0] = T(x > 0) - T(x < 0);
|
||||
}
|
||||
|
||||
if (FC_OP == OP_UNARY_NUM_STEP) {
|
||||
dst_ptr[i0] = T(x > 0);
|
||||
}
|
||||
|
||||
if (FC_OP == OP_UNARY_NUM_HARDSWISH) {
|
||||
dst_ptr[i0] = (T) (x * fmax(0, fmin(1, x/6 + 0.5)));
|
||||
}
|
||||
|
||||
if (FC_OP == OP_UNARY_NUM_HARDSIGMOID) {
|
||||
dst_ptr[i0] = (T) fmax(0, fmin(1, x/6 + 0.5));
|
||||
}
|
||||
|
||||
if (FC_OP == OP_UNARY_NUM_EXP) {
|
||||
dst_ptr[i0] = (T) exp(x);
|
||||
}
|
||||
|
||||
if (FC_OP == OP_UNARY_NUM_SOFTPLUS) {
|
||||
dst_ptr[i0] = (T) select(log(1 + exp(x)), x, x > 20);
|
||||
}
|
||||
|
||||
if (FC_OP == OP_UNARY_NUM_EXPM1) {
|
||||
// TODO: precise implementation
|
||||
dst_ptr[i0] = (T) (exp(x) - 1);
|
||||
}
|
||||
|
||||
if (FC_OP == OP_UNARY_NUM_FLOOR) {
|
||||
dst_ptr[i0] = (T) floor(x);
|
||||
}
|
||||
|
||||
if (FC_OP == OP_UNARY_NUM_CEIL) {
|
||||
dst_ptr[i0] = (T) ceil(x);
|
||||
}
|
||||
|
||||
if (FC_OP == OP_UNARY_NUM_ROUND) {
|
||||
dst_ptr[i0] = (T) round(x);
|
||||
}
|
||||
|
||||
if (FC_OP == OP_UNARY_NUM_TRUNC) {
|
||||
dst_ptr[i0] = (T) trunc(x);
|
||||
}
|
||||
|
||||
if (FC_OP == OP_UNARY_NUM_XIELU) {
|
||||
const TC xi = x;
|
||||
const TC gate = TC(xi > TC(0.0f));
|
||||
const TC clamped = fmin(xi, TC(args.val));
|
||||
const TC y_pos = TC(args.scale) * xi * xi + TC(args.bias) * xi;
|
||||
const TC y_neg = (exp(clamped) - TC(1.0f) - xi) * TC(args.slope) + TC(args.bias) * xi;
|
||||
dst_ptr[i0] = (T) (gate * y_pos + (TC(1.0f) - gate) * y_neg);
|
||||
}
|
||||
}
|
||||
|
||||
#undef FC_OP
|
||||
#undef FC_CNT
|
||||
}
|
||||
|
||||
typedef decltype(kernel_unary_impl<float, float, float>) kernel_unary_t;
|
||||
|
||||
template [[host_name("kernel_unary_f32_f32")]] kernel kernel_unary_t kernel_unary_impl<float, float, float>;
|
||||
template [[host_name("kernel_unary_f32_f32_4")]] kernel kernel_unary_t kernel_unary_impl<float4, float4, float4>;
|
||||
template [[host_name("kernel_unary_f16_f16")]] kernel kernel_unary_t kernel_unary_impl<half, half, float>;
|
||||
template [[host_name("kernel_unary_f16_f16_4")]] kernel kernel_unary_t kernel_unary_impl<half4, half4, float4>;
|
||||
|
||||
template<typename T>
|
||||
kernel void kernel_reglu(
|
||||
constant ggml_metal_kargs_glu & args,
|
||||
device const char * src0,
|
||||
device const char * src1,
|
||||
device char * dst,
|
||||
uint tgpig[[threadgroup_position_in_grid]],
|
||||
uint tpitg[[thread_position_in_threadgroup]],
|
||||
uint ntg[[threads_per_threadgroup]]) {
|
||||
device const T * src0_row = (device const T *) ((device const char *) src0 + tgpig*args.nb01) + args.i00;
|
||||
device const T * src1_row = (device const T *) ((device const char *) src1 + tgpig*args.nb11) + args.i10;
|
||||
device T * dst_row = (device T *) ((device char *) dst + tgpig*args.nb1);
|
||||
|
||||
for (int i0 = tpitg; i0 < args.ne0; i0 += ntg) {
|
||||
const float x0 = src0_row[i0];
|
||||
const float x1 = src1_row[i0];
|
||||
|
||||
dst_row[i0] = (T)(x0*x1*(x0 > 0.0f));
|
||||
}
|
||||
}
|
||||
|
||||
typedef decltype(kernel_reglu<float>) kernel_reglu_t;
|
||||
|
||||
template [[host_name("kernel_reglu_f32")]] kernel kernel_reglu_t kernel_reglu<float>;
|
||||
template [[host_name("kernel_reglu_f16")]] kernel kernel_reglu_t kernel_reglu<half>;
|
||||
|
||||
template<typename T>
|
||||
kernel void kernel_geglu(
|
||||
constant ggml_metal_kargs_glu & args,
|
||||
device const char * src0,
|
||||
device const char * src1,
|
||||
device char * dst,
|
||||
uint tgpig[[threadgroup_position_in_grid]],
|
||||
uint tpitg[[thread_position_in_threadgroup]],
|
||||
uint ntg[[threads_per_threadgroup]]) {
|
||||
device const T * src0_row = (device const T *) ((device const char *) src0 + tgpig*args.nb01) + args.i00;
|
||||
device const T * src1_row = (device const T *) ((device const char *) src1 + tgpig*args.nb11) + args.i10;
|
||||
device T * dst_row = (device T *) ((device char *) dst + tgpig*args.nb1);
|
||||
|
||||
for (int i0 = tpitg; i0 < args.ne0; i0 += ntg) {
|
||||
const float x0 = src0_row[i0];
|
||||
const float x1 = src1_row[i0];
|
||||
|
||||
const float gelu = 0.5f*x0*(1.0f + precise::tanh(SQRT_2_OVER_PI*x0*(1.0f + GELU_COEF_A*x0*x0)));
|
||||
|
||||
dst_row[i0] = (T)(gelu*x1);
|
||||
}
|
||||
}
|
||||
|
||||
typedef decltype(kernel_geglu<float>) kernel_geglu_t;
|
||||
|
||||
template [[host_name("kernel_geglu_f32")]] kernel kernel_geglu_t kernel_geglu<float>;
|
||||
template [[host_name("kernel_geglu_f16")]] kernel kernel_geglu_t kernel_geglu<half>;
|
||||
|
||||
template<typename T>
|
||||
kernel void kernel_swiglu(
|
||||
constant ggml_metal_kargs_glu & args,
|
||||
device const char * src0,
|
||||
device const char * src1,
|
||||
device char * dst,
|
||||
uint tgpig[[threadgroup_position_in_grid]],
|
||||
uint tpitg[[thread_position_in_threadgroup]],
|
||||
uint ntg[[threads_per_threadgroup]]) {
|
||||
device const T * src0_row = (device const T *) ((device const char *) src0 + tgpig*args.nb01) + args.i00;
|
||||
device const T * src1_row = (device const T *) ((device const char *) src1 + tgpig*args.nb11) + args.i10;
|
||||
device T * dst_row = (device T *) ((device char *) dst + tgpig*args.nb1);
|
||||
|
||||
for (int i0 = tpitg; i0 < args.ne0; i0 += ntg) {
|
||||
const float x0 = src0_row[i0];
|
||||
const float x1 = src1_row[i0];
|
||||
|
||||
const float silu = x0 / (1.0f + exp(-x0));
|
||||
|
||||
dst_row[i0] = (T)(silu*x1);
|
||||
}
|
||||
}
|
||||
|
||||
typedef decltype(kernel_swiglu<float>) kernel_swiglu_t;
|
||||
|
||||
template [[host_name("kernel_swiglu_f32")]] kernel kernel_swiglu_t kernel_swiglu<float>;
|
||||
template [[host_name("kernel_swiglu_f16")]] kernel kernel_swiglu_t kernel_swiglu<half>;
|
||||
|
||||
template<typename T>
|
||||
kernel void kernel_swiglu_oai(
|
||||
constant ggml_metal_kargs_glu & args,
|
||||
device const char * src0,
|
||||
device const char * src1,
|
||||
device char * dst,
|
||||
uint tgpig[[threadgroup_position_in_grid]],
|
||||
uint tpitg[[thread_position_in_threadgroup]],
|
||||
uint ntg[[threads_per_threadgroup]]) {
|
||||
device const T * src0_row = (device const T *) ((device const char *) src0 + tgpig*args.nb01) + args.i00;
|
||||
device const T * src1_row = (device const T *) ((device const char *) src1 + tgpig*args.nb11) + args.i10;
|
||||
device T * dst_row = (device T *) ((device char *) dst + tgpig*args.nb1);
|
||||
|
||||
for (int i0 = tpitg; i0 < args.ne0; i0 += ntg) {
|
||||
float x0 = src0_row[i0];
|
||||
float x1 = src1_row[i0];
|
||||
|
||||
x0 = min(x0, args.limit);
|
||||
x1 = max(min(x1, args.limit), -args.limit);
|
||||
|
||||
float out_glu = x0 / (1.0f + exp(-x0 * args.alpha));
|
||||
out_glu = out_glu * (1.0f + x1);
|
||||
|
||||
dst_row[i0] = (T)out_glu;
|
||||
}
|
||||
}
|
||||
|
||||
typedef decltype(kernel_swiglu_oai<float>) kernel_swiglu_oai_t;
|
||||
|
||||
template [[host_name("kernel_swiglu_oai_f32")]] kernel kernel_swiglu_oai_t kernel_swiglu_oai<float>;
|
||||
template [[host_name("kernel_swiglu_oai_f16")]] kernel kernel_swiglu_oai_t kernel_swiglu_oai<half>;
|
||||
|
||||
template<typename T>
|
||||
kernel void kernel_geglu_erf(
|
||||
constant ggml_metal_kargs_glu & args,
|
||||
device const char * src0,
|
||||
device const char * src1,
|
||||
device char * dst,
|
||||
uint tgpig[[threadgroup_position_in_grid]],
|
||||
uint tpitg[[thread_position_in_threadgroup]],
|
||||
uint ntg[[threads_per_threadgroup]]) {
|
||||
device const T * src0_row = (device const T *) ((device const char *) src0 + tgpig*args.nb01) + args.i00;
|
||||
device const T * src1_row = (device const T *) ((device const char *) src1 + tgpig*args.nb11) + args.i10;
|
||||
device T * dst_row = (device T *) ((device char *) dst + tgpig*args.nb1);
|
||||
|
||||
for (int i0 = tpitg; i0 < args.ne0; i0 += ntg) {
|
||||
const float x0 = src0_row[i0];
|
||||
const float x1 = src1_row[i0];
|
||||
|
||||
const float gelu_erf = 0.5f*x0*(1.0f+erf_approx<float>(x0*SQRT_2_INV));
|
||||
|
||||
dst_row[i0] = (T)(gelu_erf*x1);
|
||||
}
|
||||
}
|
||||
|
||||
typedef decltype(kernel_geglu_erf<float>) kernel_geglu_erf_t;
|
||||
|
||||
template [[host_name("kernel_geglu_erf_f32")]] kernel kernel_geglu_erf_t kernel_geglu_erf<float>;
|
||||
template [[host_name("kernel_geglu_erf_f16")]] kernel kernel_geglu_erf_t kernel_geglu_erf<half>;
|
||||
|
||||
template<typename T>
|
||||
kernel void kernel_geglu_quick(
|
||||
constant ggml_metal_kargs_glu & args,
|
||||
device const char * src0,
|
||||
device const char * src1,
|
||||
device char * dst,
|
||||
uint tgpig[[threadgroup_position_in_grid]],
|
||||
uint tpitg[[thread_position_in_threadgroup]],
|
||||
uint ntg[[threads_per_threadgroup]]) {
|
||||
device const T * src0_row = (device const T *) ((device const char *) src0 + tgpig*args.nb01) + args.i00;
|
||||
device const T * src1_row = (device const T *) ((device const char *) src1 + tgpig*args.nb11) + args.i10;
|
||||
device T * dst_row = (device T *) ((device char *) dst + tgpig*args.nb1);
|
||||
|
||||
for (int i0 = tpitg; i0 < args.ne0; i0 += ntg) {
|
||||
const float x0 = src0_row[i0];
|
||||
const float x1 = src1_row[i0];
|
||||
|
||||
const float gelu_quick = x0*(1.0f/(1.0f+exp(GELU_QUICK_COEF*x0)));
|
||||
|
||||
dst_row[i0] = (T)(gelu_quick*x1);
|
||||
}
|
||||
}
|
||||
|
||||
typedef decltype(kernel_geglu_quick<float>) kernel_geglu_quick_t;
|
||||
|
||||
template [[host_name("kernel_geglu_quick_f32")]] kernel kernel_geglu_quick_t kernel_geglu_quick<float>;
|
||||
template [[host_name("kernel_geglu_quick_f16")]] kernel kernel_geglu_quick_t kernel_geglu_quick<half>;
|
||||
@@ -0,0 +1,179 @@
|
||||
#include "common.h"
|
||||
|
||||
constant bool FC_upscale_aa [[function_constant(FC_UPSCALE + 0)]];
|
||||
|
||||
kernel void kernel_upscale_nearest_f32(
|
||||
constant ggml_metal_kargs_upscale & args,
|
||||
device const char * src0,
|
||||
device char * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
uint3 tpitg[[thread_position_in_threadgroup]],
|
||||
uint3 ntg[[threads_per_threadgroup]]) {
|
||||
|
||||
const int64_t i3 = tgpig.z;
|
||||
const int64_t i2 = tgpig.y;
|
||||
const int64_t i1 = tgpig.x;
|
||||
|
||||
const int64_t i03 = i3/args.sf3;
|
||||
const int64_t i02 = i2/args.sf2;
|
||||
const int64_t i01 = i1/args.sf1;
|
||||
|
||||
for (int i0 = tpitg.x; i0 < args.ne0; i0 += ntg.x) {
|
||||
const int64_t i00 = i0/args.sf0;
|
||||
|
||||
device const float * src0_ptr = (device const float *) (src0 + i03*args.nb03 + i02*args.nb02 + i01*args.nb01 + i00*args.nb00);
|
||||
device float * dst_ptr = (device float *) (dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1 + i0*args.nb0);
|
||||
|
||||
dst_ptr[0] = src0_ptr[0];
|
||||
}
|
||||
}
|
||||
|
||||
static inline float bilinear_tri(float x) {
|
||||
return MAX(0.0f, 1.0f - fabs(x));
|
||||
}
|
||||
|
||||
kernel void kernel_upscale_bilinear_f32(
|
||||
constant ggml_metal_kargs_upscale & args,
|
||||
device const char * src0,
|
||||
device char * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
uint3 tpitg[[thread_position_in_threadgroup]],
|
||||
uint3 ntg[[threads_per_threadgroup]]) {
|
||||
|
||||
const int64_t i3 = tgpig.z;
|
||||
const int64_t i2 = tgpig.y;
|
||||
const int64_t i1 = tgpig.x;
|
||||
|
||||
const int64_t i03 = i3 / args.sf3;
|
||||
const int64_t i02 = i2 / args.sf2;
|
||||
|
||||
const float f01 = ((float)i1 + args.poffs) / args.sf1 - args.poffs;
|
||||
const int64_t i01 = MAX(0, MIN(args.ne01 - 1, (int64_t)floor(f01)));
|
||||
const int64_t i01p = MAX(0, MIN(args.ne01 - 1, i01 + 1));
|
||||
const float fd1 = MAX(0.0f, MIN(1.0f, f01 - (float)i01));
|
||||
|
||||
src0 += i03*args.nb03 + i02*args.nb02;
|
||||
|
||||
device float * dst_ptr = (device float *)(dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1);
|
||||
|
||||
if (FC_upscale_aa) {
|
||||
const float support0 = MAX(1.0f, 1.0f / args.sf0);
|
||||
const float invscale0 = 1.0f / support0;
|
||||
const float support1 = MAX(1.0f, 1.0f / args.sf1);
|
||||
const float invscale1 = 1.0f / support1;
|
||||
|
||||
for (int i0 = tpitg.x; i0 < args.ne0; i0 += ntg.x) {
|
||||
const float f00 = ((float)i0 + args.poffs) / args.sf0 - args.poffs;
|
||||
|
||||
int64_t x_min = MAX((int64_t)0, (int64_t)floor(f00 - support0 + args.poffs));
|
||||
int64_t x_max = MIN(args.ne00, (int64_t)ceil (f00 + support0 + args.poffs));
|
||||
|
||||
int64_t y_min = MAX((int64_t)0, (int64_t)floor(f01 - support1 + args.poffs));
|
||||
int64_t y_max = MIN(args.ne01, (int64_t)ceil (f01 + support1 + args.poffs));
|
||||
|
||||
float sum = 0.0f;
|
||||
float wsum = 0.0f;
|
||||
|
||||
for (int64_t sy = y_min; sy < y_max; ++sy) {
|
||||
const float wy = MAX(0.0f, 1.0f - fabs((float)sy - f01) * invscale1);
|
||||
for (int64_t sx = x_min; sx < x_max; ++sx) {
|
||||
const float wx = MAX(0.0f, 1.0f - fabs((float)sx - f00) * invscale0);
|
||||
const float w = wx * wy;
|
||||
device const float * src_ptr = (device const float *)(src0 + sy*args.nb01 + sx*args.nb00);
|
||||
sum += (*src_ptr) * w;
|
||||
wsum += w;
|
||||
}
|
||||
}
|
||||
|
||||
const float v = (wsum > 0.0f) ? (sum / wsum) : 0.0f;
|
||||
dst_ptr[i0] = v;
|
||||
}
|
||||
} else {
|
||||
for (int i0 = tpitg.x; i0 < args.ne0; i0 += ntg.x) {
|
||||
const float f00 = ((float)i0 + args.poffs) / args.sf0 - args.poffs;
|
||||
const int64_t i00 = MAX(0, MIN(args.ne00 - 1, (int64_t)floor(f00)));
|
||||
const int64_t i00p = MAX(0, MIN(args.ne00 - 1, i00 + 1));
|
||||
const float fd0 = MAX(0.0f, MIN(1.0f, f00 - (float)i00));
|
||||
|
||||
device const float * src00 = (device const float *)(src0 + i01*args.nb01 + i00*args.nb00);
|
||||
device const float * src10 = (device const float *)(src0 + i01*args.nb01 + i00p*args.nb00);
|
||||
device const float * src01 = (device const float *)(src0 + i01p*args.nb01 + i00*args.nb00);
|
||||
device const float * src11 = (device const float *)(src0 + i01p*args.nb01 + i00p*args.nb00);
|
||||
|
||||
const float v =
|
||||
(*src00) * (1.0f - fd0) * (1.0f - fd1) +
|
||||
(*src10) * fd0 * (1.0f - fd1) +
|
||||
(*src01) * (1.0f - fd0) * fd1 +
|
||||
(*src11) * fd0 * fd1;
|
||||
|
||||
dst_ptr[i0] = v;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
static inline float bicubic_weight1(float x) {
|
||||
const float a = -0.75f;
|
||||
return ((a + 2) * x - (a + 3)) * x * x + 1;
|
||||
}
|
||||
|
||||
static inline float bicubic_weight2(float x) {
|
||||
const float a = -0.75f;
|
||||
return ((a * x - 5 * a) * x + 8 * a) * x - 4 * a;
|
||||
}
|
||||
|
||||
kernel void kernel_upscale_bicubic_f32(
|
||||
constant ggml_metal_kargs_upscale & args,
|
||||
device const char * src0,
|
||||
device char * dst,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
uint3 tpitg[[thread_position_in_threadgroup]],
|
||||
uint3 ntg[[threads_per_threadgroup]]) {
|
||||
|
||||
const int64_t i3 = tgpig.z;
|
||||
const int64_t i2 = tgpig.y;
|
||||
const int64_t i1 = tgpig.x;
|
||||
|
||||
const int64_t i03 = i3 / args.sf3;
|
||||
const int64_t i02 = i2 / args.sf2;
|
||||
|
||||
const float f01 = ((float)i1 + args.poffs) / args.sf1 - args.poffs;
|
||||
const int64_t i01 = (int64_t)floor(f01);
|
||||
const float fd1 = f01 - (float)i01;
|
||||
|
||||
const float w_y0 = bicubic_weight2(fd1 + 1.0f);
|
||||
const float w_y1 = bicubic_weight1(fd1);
|
||||
const float w_y2 = bicubic_weight1(1.0f - fd1);
|
||||
const float w_y3 = bicubic_weight2(2.0f - fd1);
|
||||
|
||||
const device const char * src_slice = src0 + i03 * args.nb03 + i02 * args.nb02;
|
||||
|
||||
device float * dst_ptr = (device float *)(dst + i3 * args.nb3 + i2 * args.nb2 + i1 * args.nb1);
|
||||
|
||||
for (int i0 = tpitg.x; i0 < args.ne0; i0 += ntg.x) {
|
||||
const float f00 = ((float)i0 + args.poffs) / args.sf0 - args.poffs;
|
||||
const int64_t i00 = (int64_t)floor(f00);
|
||||
const float fd0 = f00 - (float)i00;
|
||||
|
||||
const float w_x0 = bicubic_weight2(fd0 + 1.0f);
|
||||
const float w_x1 = bicubic_weight1(fd0);
|
||||
const float w_x2 = bicubic_weight1(1.0f - fd0);
|
||||
const float w_x3 = bicubic_weight2(2.0f - fd0);
|
||||
|
||||
float sum = 0.0f;
|
||||
|
||||
for (int dy = -1; dy <= 2; ++dy) {
|
||||
const int64_t iy = MAX(0, MIN(args.ne01 - 1, i01 + dy));
|
||||
const float wy = (dy == -1) ? w_y0 : (dy == 0) ? w_y1 : (dy == 1) ? w_y2 : w_y3;
|
||||
|
||||
for (int dx = -1; dx <= 2; ++dx) {
|
||||
const int64_t ix = MAX(0, MIN(args.ne00 - 1, i00 + dx));
|
||||
const float wx = (dx == -1) ? w_x0 : (dx == 0) ? w_x1 : (dx == 1) ? w_x2 : w_x3;
|
||||
|
||||
device const float * src_ptr = (device const float *)(src_slice + iy * args.nb01 + ix * args.nb00);
|
||||
sum += (*src_ptr) * wx * wy;
|
||||
}
|
||||
}
|
||||
|
||||
dst_ptr[i0] = sum;
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,179 @@
|
||||
#include "common.h"
|
||||
|
||||
kernel void kernel_rwkv_wkv6_f32(
|
||||
device const float * k,
|
||||
device const float * v,
|
||||
device const float * r,
|
||||
device const float * tf,
|
||||
device const float * td,
|
||||
device const float * state_in,
|
||||
device float * dst,
|
||||
constant uint & B,
|
||||
constant uint & T,
|
||||
constant uint & C,
|
||||
constant uint & H,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
uint3 tpitg[[thread_position_in_threadgroup]],
|
||||
uint3 ntg[[threads_per_threadgroup]]) {
|
||||
|
||||
const uint head_size = 64; // TODO: support head_size = 128
|
||||
const uint batch_id = tgpig.x / H;
|
||||
const uint head_id = tgpig.x % H;
|
||||
const uint tid = tpitg.x;
|
||||
|
||||
if (batch_id >= B || head_id >= H) {
|
||||
return;
|
||||
}
|
||||
|
||||
const uint state_size = C * head_size;
|
||||
const uint n_seq_tokens = T / B;
|
||||
|
||||
threadgroup float _k[head_size];
|
||||
threadgroup float _r[head_size];
|
||||
threadgroup float _tf[head_size];
|
||||
threadgroup float _td[head_size];
|
||||
|
||||
float state[head_size];
|
||||
|
||||
for (uint i = 0; i < head_size; i++) {
|
||||
state[i] = state_in[batch_id * state_size + head_id * head_size * head_size
|
||||
+ i * head_size + tid];
|
||||
}
|
||||
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
_tf[tid] = tf[head_id * head_size + tid];
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
const uint start_t = batch_id * n_seq_tokens * C + head_id * head_size + tid;
|
||||
const uint end_t = (batch_id + 1) * n_seq_tokens * C + head_id * head_size + tid;
|
||||
|
||||
for (uint t = start_t; t < end_t; t += C) {
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
_k[tid] = k[t];
|
||||
_r[tid] = r[t];
|
||||
_td[tid] = td[t];
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
const float v_val = v[t];
|
||||
float y = 0.0;
|
||||
|
||||
for (uint j = 0; j < head_size; j += 4) {
|
||||
float4 k_vec = float4(_k[j], _k[j+1], _k[j+2], _k[j+3]);
|
||||
float4 r_vec = float4(_r[j], _r[j+1], _r[j+2], _r[j+3]);
|
||||
float4 tf_vec = float4(_tf[j], _tf[j+1], _tf[j+2], _tf[j+3]);
|
||||
float4 td_vec = float4(_td[j], _td[j+1], _td[j+2], _td[j+3]);
|
||||
float4 s_vec = float4(state[j], state[j+1], state[j+2], state[j+3]);
|
||||
|
||||
float4 kv = k_vec * v_val;
|
||||
|
||||
float4 temp = tf_vec * kv + s_vec;
|
||||
y += dot(r_vec, temp);
|
||||
|
||||
s_vec = s_vec * td_vec + kv;
|
||||
state[j] = s_vec[0];
|
||||
state[j+1] = s_vec[1];
|
||||
state[j+2] = s_vec[2];
|
||||
state[j+3] = s_vec[3];
|
||||
}
|
||||
|
||||
dst[t] = y;
|
||||
}
|
||||
|
||||
for (uint i = 0; i < head_size; i++) {
|
||||
dst[T * C + batch_id * state_size + head_id * head_size * head_size
|
||||
+ i * head_size + tid] = state[i];
|
||||
}
|
||||
}
|
||||
|
||||
kernel void kernel_rwkv_wkv7_f32(
|
||||
device const float * r,
|
||||
device const float * w,
|
||||
device const float * k,
|
||||
device const float * v,
|
||||
device const float * a,
|
||||
device const float * b,
|
||||
device const float * state_in,
|
||||
device float * dst,
|
||||
constant uint & B,
|
||||
constant uint & T,
|
||||
constant uint & C,
|
||||
constant uint & H,
|
||||
uint3 tgpig[[threadgroup_position_in_grid]],
|
||||
uint3 tpitg[[thread_position_in_threadgroup]],
|
||||
uint3 ntg[[threads_per_threadgroup]]) {
|
||||
|
||||
const uint head_size = 64; // TODO: support head_size = 128
|
||||
const uint batch_id = tgpig.x / H;
|
||||
const uint head_id = tgpig.x % H;
|
||||
const uint tid = tpitg.x;
|
||||
|
||||
if (batch_id >= B || head_id >= H) {
|
||||
return;
|
||||
}
|
||||
|
||||
const uint state_size = C * head_size;
|
||||
const uint n_seq_tokens = T / B;
|
||||
|
||||
threadgroup float _r[head_size];
|
||||
threadgroup float _w[head_size];
|
||||
threadgroup float _k[head_size];
|
||||
threadgroup float _a[head_size];
|
||||
threadgroup float _b[head_size];
|
||||
|
||||
float state[head_size];
|
||||
|
||||
for (uint i = 0; i < head_size; i++) {
|
||||
state[i] = state_in[batch_id * state_size + head_id * head_size * head_size
|
||||
+ tid * head_size + i];
|
||||
}
|
||||
|
||||
const uint start_t = batch_id * n_seq_tokens * C + head_id * head_size + tid;
|
||||
const uint end_t = (batch_id + 1) * n_seq_tokens * C + head_id * head_size + tid;
|
||||
|
||||
for (uint t = start_t; t < end_t; t += C) {
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
_r[tid] = r[t];
|
||||
_w[tid] = w[t];
|
||||
_k[tid] = k[t];
|
||||
_a[tid] = a[t];
|
||||
_b[tid] = b[t];
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
const float v_val = v[t];
|
||||
float y = 0.0, sa = 0.0;
|
||||
|
||||
float4 sa_vec(0.0);
|
||||
|
||||
for (uint j = 0; j < head_size; j += 4) {
|
||||
float4 a_vec = float4(_a[j], _a[j+1], _a[j+2], _a[j+3]);
|
||||
float4 s_vec = float4(state[j], state[j+1], state[j+2], state[j+3]);
|
||||
sa_vec += a_vec * s_vec;
|
||||
}
|
||||
sa = sa_vec[0] + sa_vec[1] + sa_vec[2] + sa_vec[3];
|
||||
|
||||
for (uint j = 0; j < head_size; j += 4) {
|
||||
float4 r_vec = float4(_r[j], _r[j+1], _r[j+2], _r[j+3]);
|
||||
float4 w_vec = float4(_w[j], _w[j+1], _w[j+2], _w[j+3]);
|
||||
float4 k_vec = float4(_k[j], _k[j+1], _k[j+2], _k[j+3]);
|
||||
float4 b_vec = float4(_b[j], _b[j+1], _b[j+2], _b[j+3]);
|
||||
float4 s_vec = float4(state[j], state[j+1], state[j+2], state[j+3]);
|
||||
|
||||
float4 kv = k_vec * v_val;
|
||||
|
||||
s_vec = s_vec * w_vec + kv + sa * b_vec;
|
||||
y += dot(s_vec, r_vec);
|
||||
|
||||
state[j] = s_vec[0];
|
||||
state[j+1] = s_vec[1];
|
||||
state[j+2] = s_vec[2];
|
||||
state[j+3] = s_vec[3];
|
||||
}
|
||||
|
||||
dst[t] = y;
|
||||
}
|
||||
|
||||
for (uint i = 0; i < head_size; i++) {
|
||||
dst[T * C + batch_id * state_size + head_id * head_size * head_size
|
||||
+ tid * head_size + i] = state[i];
|
||||
}
|
||||
}
|
||||
+70
-4
@@ -505,7 +505,7 @@ llama_ubatch llama_batch_allocr::split_simple(uint32_t n_ubatch) {
|
||||
return ubatch_add(idxs, idxs.size(), false);
|
||||
}
|
||||
|
||||
llama_ubatch llama_batch_allocr::split_equal(uint32_t n_ubatch, bool sequential) {
|
||||
llama_ubatch llama_batch_allocr::split_equal(uint32_t n_ubatch, bool sequential, uint32_t n_keep_tail) {
|
||||
if (sequential && has_cpl) {
|
||||
LLAMA_LOG_ERROR("%s: sequential split is not supported when there are coupled sequences in the input batch (you may need to use the -kvu flag)\n", __func__);
|
||||
|
||||
@@ -548,7 +548,7 @@ llama_ubatch llama_batch_allocr::split_equal(uint32_t n_ubatch, bool sequential)
|
||||
}
|
||||
}
|
||||
|
||||
const uint32_t n_seqs = cur_seq_set.size();
|
||||
uint32_t n_seqs = cur_seq_set.size();
|
||||
|
||||
// we are done
|
||||
if (n_seqs == 0) {
|
||||
@@ -569,7 +569,7 @@ llama_ubatch llama_batch_allocr::split_equal(uint32_t n_ubatch, bool sequential)
|
||||
std::vector<idx_vec_t> idxs_per_seq(n_seqs);
|
||||
|
||||
while (true) {
|
||||
// we can only add new n_seq_tokens tokens if all the sequence sets have at least one more unused token and
|
||||
// we can only add new n_seq_tokens tokens if all the sequence sets have at least 1 more unused tokens and
|
||||
// if we haven't reached n_ubatch
|
||||
bool can_expand = true;
|
||||
|
||||
@@ -600,6 +600,72 @@ llama_ubatch llama_batch_allocr::split_equal(uint32_t n_ubatch, bool sequential)
|
||||
}
|
||||
}
|
||||
|
||||
// if n_keep_tail > 0, keep only the seqs that either finish in this ubatch or have at least
|
||||
// n_keep_tail tokens remaining for a future ubatch, so that the trailing n_keep_tail tokens
|
||||
// of each seq are never split across ubatches
|
||||
if (n_keep_tail > 0) {
|
||||
GGML_ASSERT(n_ubatch > n_keep_tail);
|
||||
|
||||
auto n_remaining = [&](uint32_t s) {
|
||||
return (uint32_t) (seq_set_map[cur_seq_set[s]].size() - cur_idx[s]);
|
||||
};
|
||||
|
||||
// keep the longest prefix of seqs that satisfy the constraint, to preserve sequential seq ids
|
||||
uint32_t n_keep = 0;
|
||||
while (n_keep < n_seqs) {
|
||||
const uint32_t remaining = n_remaining(n_keep);
|
||||
|
||||
if (remaining != 0 && remaining < n_keep_tail) {
|
||||
break;
|
||||
}
|
||||
|
||||
n_keep++;
|
||||
}
|
||||
|
||||
// all seqs violate the constraint - resolve the first one directly and emit it alone
|
||||
if (n_keep == 0) {
|
||||
auto & idxs = idxs_per_seq[0];
|
||||
|
||||
const auto & seq_idxs = seq_set_map[cur_seq_set[0]];
|
||||
|
||||
if (idxs.size() + n_remaining(0) <= n_ubatch) {
|
||||
// extend the seq to completion
|
||||
while (n_remaining(0) > 0) {
|
||||
const int32_t idx = seq_idxs[cur_idx[0]];
|
||||
|
||||
idxs.push_back(idx);
|
||||
|
||||
used[idx] = true;
|
||||
++n_used;
|
||||
|
||||
++cur_idx[0];
|
||||
}
|
||||
} else {
|
||||
// truncate the seq so that at least n_keep_tail tokens remain
|
||||
while (n_remaining(0) < n_keep_tail) {
|
||||
used[idxs.back()] = false;
|
||||
--n_used;
|
||||
|
||||
idxs.pop_back();
|
||||
|
||||
--cur_idx[0];
|
||||
}
|
||||
}
|
||||
|
||||
n_keep = 1;
|
||||
}
|
||||
|
||||
// return the tokens of the deferred seqs back to the pool
|
||||
for (uint32_t s = n_keep; s < n_seqs; ++s) {
|
||||
for (const int32_t idx : idxs_per_seq[s]) {
|
||||
used[idx] = false;
|
||||
--n_used;
|
||||
}
|
||||
}
|
||||
|
||||
n_seqs = n_keep;
|
||||
}
|
||||
|
||||
// concat the per-sequence-set lists
|
||||
std::vector<int32_t> idxs;
|
||||
|
||||
@@ -814,7 +880,7 @@ void llama_batch_allocr::ubatch_print(const llama_ubatch & ubatch, int debug) {
|
||||
LLAMA_LOG_DEBUG("%s: output = %p\n", __func__, (void *) ubatch.output);
|
||||
LLAMA_LOG_DEBUG("%s: n_outputs = %d\n", __func__, n_outputs);
|
||||
|
||||
if (debug > 1) {
|
||||
if (debug > 0) {
|
||||
int seq_id_max = 0;
|
||||
for (uint32_t i = 0; i < ubatch.n_tokens; ++i) {
|
||||
for (int s = 0; s < ubatch.n_seq_id[i]; ++s) {
|
||||
|
||||
+2
-1
@@ -104,7 +104,8 @@ public:
|
||||
|
||||
// make ubatches of equal-length sequences sets
|
||||
// if sequential == true, the tokens in the ubatch will have increasing sequential sequence ids
|
||||
llama_ubatch split_equal(uint32_t n_ubatch, bool sequential);
|
||||
// n_keep_tail = minimum trailing tokens of a seq that must land in the same ubatch
|
||||
llama_ubatch split_equal(uint32_t n_ubatch, bool sequential, uint32_t n_keep_tail);
|
||||
|
||||
// sequence-set-wise split - each ubatch contains a single sequence-set
|
||||
llama_ubatch split_seq(uint32_t n_ubatch);
|
||||
|
||||
+89
-122
@@ -17,6 +17,7 @@
|
||||
#include <cstring>
|
||||
#include <limits>
|
||||
#include <stdexcept>
|
||||
#include <string>
|
||||
|
||||
//
|
||||
// llama_context
|
||||
@@ -30,6 +31,30 @@ static llm_graph_type ctx_type_to_graph_type(llama_context_type ctx_type) {
|
||||
throw std::runtime_error("Unsupported ctx type");
|
||||
}
|
||||
|
||||
struct llm_fused_op_probe {
|
||||
llm_fused_op op;
|
||||
const char * name;
|
||||
uint32_t n_tokens_per_seq;
|
||||
};
|
||||
|
||||
static const llm_fused_op_probe llm_fused_op_flash_attn_probe = {
|
||||
/*.op =*/ LLM_FUSED_OP_FLASH_ATTN,
|
||||
/*.name =*/ "Flash Attention",
|
||||
/*.n_tokens_per_seq =*/ 1,
|
||||
};
|
||||
|
||||
static const llm_fused_op_probe llm_fused_op_gdn_ar_probe = {
|
||||
/*.op =*/ LLM_FUSED_OP_GDN_AR,
|
||||
/*.name =*/ "fused Gated Delta Net (autoregressive)",
|
||||
/*.n_tokens_per_seq =*/ 1,
|
||||
};
|
||||
|
||||
static const llm_fused_op_probe llm_fused_op_gdn_ch_probe = {
|
||||
/*.op =*/ LLM_FUSED_OP_GDN_CH,
|
||||
/*.name =*/ "fused Gated Delta Net (chunked)",
|
||||
/*.n_tokens_per_seq =*/ 16,
|
||||
};
|
||||
|
||||
llama_context::llama_context(
|
||||
const llama_model & model,
|
||||
llama_context_params params) :
|
||||
@@ -436,6 +461,69 @@ llama_context::~llama_context() {
|
||||
ggml_opt_free(opt_ctx);
|
||||
}
|
||||
|
||||
void llama_context::resolve_fused_ops(const llama_memory_context_i * mctx, uint32_t n_seqs) {
|
||||
const char * func = __func__;
|
||||
auto resolve = [&](const llm_fused_op_probe & probe, bool & enabled) {
|
||||
if (!enabled) {
|
||||
return;
|
||||
}
|
||||
|
||||
const uint32_t n_tokens_probe = probe.n_tokens_per_seq*n_seqs;
|
||||
|
||||
auto * gf = graph_reserve(n_tokens_probe, n_seqs, n_tokens_probe, mctx, true);
|
||||
if (!gf) {
|
||||
throw std::runtime_error(std::string("failed to reserve graph for ") + probe.name + " check");
|
||||
}
|
||||
|
||||
bool device_mismatch = false;
|
||||
for (const auto & node : get_gf_res_reserve()->get_fused_nodes()) {
|
||||
if (node.op != probe.op) {
|
||||
continue;
|
||||
}
|
||||
|
||||
GGML_ASSERT(node.il >= 0);
|
||||
|
||||
ggml_backend_t backend_fused = ggml_backend_sched_get_tensor_backend(sched.get(), node.tensor);
|
||||
ggml_backend_dev_t device_fused = backend_fused ? ggml_backend_get_device(backend_fused) : nullptr;
|
||||
|
||||
// TODO: make this descriptor-specific; model.dev_layer() preserves the current behavior,
|
||||
// but is still wrong for cases like --no-kv-offload.
|
||||
ggml_backend_dev_t device_layer = model.dev_layer(node.il);
|
||||
|
||||
if (device_fused != device_layer) {
|
||||
LLAMA_LOG_WARN("%s: layer %d is assigned to device %s but %s "
|
||||
"is assigned to device %s (usually due to missing support)\n",
|
||||
func, node.il,
|
||||
device_layer ? ggml_backend_dev_name(device_layer) : "none",
|
||||
probe.name,
|
||||
device_fused ? ggml_backend_dev_name(device_fused) : "none");
|
||||
device_mismatch = true;
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
if (device_mismatch) {
|
||||
enabled = false;
|
||||
LLAMA_LOG_WARN("%s: %s not supported, set to disabled\n", func, probe.name);
|
||||
} else {
|
||||
enabled = true;
|
||||
LLAMA_LOG_INFO("%s: %s enabled\n", func, probe.name);
|
||||
}
|
||||
};
|
||||
|
||||
if (cparams.auto_fa) {
|
||||
resolve(llm_fused_op_flash_attn_probe, cparams.flash_attn);
|
||||
cparams.auto_fa = false;
|
||||
}
|
||||
|
||||
if (cparams.auto_fgdn) {
|
||||
LLAMA_LOG_INFO("%s: resolving fused Gated Delta Net support:\n", func);
|
||||
resolve(llm_fused_op_gdn_ar_probe, cparams.fused_gdn_ar);
|
||||
resolve(llm_fused_op_gdn_ch_probe, cparams.fused_gdn_ch);
|
||||
cparams.auto_fgdn = false;
|
||||
}
|
||||
}
|
||||
|
||||
void llama_context::sched_reserve() {
|
||||
if (!sched_need_reserve) {
|
||||
return;
|
||||
@@ -475,128 +563,7 @@ void llama_context::sched_reserve() {
|
||||
|
||||
LLAMA_LOG_DEBUG("%s: worst-case: n_tokens = %d, n_seqs = %d, n_outputs = %d\n", __func__, n_tokens, n_seqs, n_outputs);
|
||||
|
||||
// resolve automatic Flash Attention use
|
||||
if (cparams.auto_fa) {
|
||||
auto * gf = graph_reserve(1, n_seqs, n_outputs, mctx.get(), true);
|
||||
if (!gf) {
|
||||
throw std::runtime_error("failed to reserve graph for Flash Attention check");
|
||||
}
|
||||
|
||||
const size_t prefix_len = strlen(LLAMA_TENSOR_NAME_FATTN) + 1;
|
||||
bool fa_device_mismatch = false;
|
||||
for (int i = 0; i < ggml_graph_n_nodes(gf); i++) {
|
||||
ggml_tensor * n = ggml_graph_node(gf, i);
|
||||
if (n->op != GGML_OP_FLASH_ATTN_EXT) {
|
||||
continue;
|
||||
}
|
||||
ggml_backend_dev_t device_fa = ggml_backend_get_device(ggml_backend_sched_get_tensor_backend(sched.get(), n));
|
||||
|
||||
// TODO: instead of the tensor names, use a map to keep track of which (FA) tensors belong to which layer
|
||||
GGML_ASSERT(strncmp(n->name, LLAMA_TENSOR_NAME_FATTN "-", prefix_len) == 0);
|
||||
const int il = std::stoi(n->name + prefix_len);
|
||||
ggml_backend_dev_t device_kv = model.dev_layer(il);
|
||||
if (device_fa != device_kv) {
|
||||
LLAMA_LOG_WARN("%s: layer %d is assigned to device %s but the Flash Attention tensor "
|
||||
"is assigned to device %s (usually due to missing support)\n",
|
||||
__func__, il, ggml_backend_dev_name(device_kv), ggml_backend_dev_name(device_fa));
|
||||
// FIXME: fa_device_mismatch logic is wrong for --no-kv-offload, but this is broken anyways
|
||||
fa_device_mismatch = true;
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
if (fa_device_mismatch) {
|
||||
cparams.flash_attn = false;
|
||||
LLAMA_LOG_WARN("%s: Flash Attention was auto, set to disabled\n", __func__);
|
||||
} else {
|
||||
cparams.flash_attn = true;
|
||||
LLAMA_LOG_INFO("%s: Flash Attention was auto, set to enabled\n", __func__);
|
||||
}
|
||||
|
||||
cparams.auto_fa = false;
|
||||
}
|
||||
|
||||
if (cparams.auto_fgdn) {
|
||||
LLAMA_LOG_INFO("%s: resolving fused Gated Delta Net support:\n", __func__);
|
||||
|
||||
if (cparams.fused_gdn_ar) {
|
||||
auto * gf = graph_reserve(1, n_seqs, n_outputs, mctx.get(), true);
|
||||
if (!gf) {
|
||||
throw std::runtime_error("failed to reserve graph for fused Gated Delta Net check (autoregressive)");
|
||||
}
|
||||
|
||||
const size_t prefix_len = strlen(LLAMA_TENSOR_NAME_FGDN_AR) + 1;
|
||||
bool gdn_device_mismatch = false;
|
||||
for (int i = 0; i < ggml_graph_n_nodes(gf); i++) {
|
||||
ggml_tensor * n = ggml_graph_node(gf, i);
|
||||
if (n->op != GGML_OP_GATED_DELTA_NET) {
|
||||
continue;
|
||||
}
|
||||
ggml_backend_dev_t device_gdn = ggml_backend_get_device(ggml_backend_sched_get_tensor_backend(sched.get(), n));
|
||||
|
||||
GGML_ASSERT(strncmp(n->name, LLAMA_TENSOR_NAME_FGDN_AR "-", prefix_len) == 0);
|
||||
const int il = std::stoi(n->name + prefix_len);
|
||||
ggml_backend_dev_t device_kv = model.dev_layer(il);
|
||||
if (device_gdn != device_kv) {
|
||||
LLAMA_LOG_WARN("%s: layer %d is assigned to device %s but the fused Gated Delta Net tensor "
|
||||
"is assigned to device %s (usually due to missing support)\n",
|
||||
__func__, il, ggml_backend_dev_name(device_kv), ggml_backend_dev_name(device_gdn));
|
||||
gdn_device_mismatch = true;
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
if (gdn_device_mismatch) {
|
||||
cparams.fused_gdn_ar = false;
|
||||
LLAMA_LOG_WARN("%s: fused Gated Delta Net (autoregressive) not supported, set to disabled\n", __func__);
|
||||
} else {
|
||||
LLAMA_LOG_INFO("%s: fused Gated Delta Net (autoregressive) enabled\n", __func__);
|
||||
}
|
||||
}
|
||||
|
||||
if (cparams.fused_gdn_ch) {
|
||||
// more than one token in the batch per sequence in order to take the chunked path
|
||||
// note: n_outputs must match n_tokens for embedding models with mean/rank pooling,
|
||||
// because build_pooling creates inp_mean with shape [n_tokens, n_seqs] and multiplies
|
||||
// it with t_embd which is reduced to [n_outputs, ...] via out_ids. if n_outputs != n_tokens,
|
||||
// the ggml_mul_mat assertion fails.
|
||||
const uint32_t n_tokens_ch = 16*n_seqs;
|
||||
auto * gf = graph_reserve(n_tokens_ch, n_seqs, n_tokens_ch, mctx.get(), true);
|
||||
if (!gf) {
|
||||
throw std::runtime_error("failed to reserve graph for fused Gated Delta Net check (chunked)");
|
||||
}
|
||||
|
||||
const size_t prefix_len = strlen(LLAMA_TENSOR_NAME_FGDN_CH) + 1;
|
||||
bool gdn_device_mismatch = false;
|
||||
for (int i = 0; i < ggml_graph_n_nodes(gf); i++) {
|
||||
ggml_tensor * n = ggml_graph_node(gf, i);
|
||||
if (n->op != GGML_OP_GATED_DELTA_NET) {
|
||||
continue;
|
||||
}
|
||||
ggml_backend_dev_t device_gdn = ggml_backend_get_device(ggml_backend_sched_get_tensor_backend(sched.get(), n));
|
||||
|
||||
GGML_ASSERT(strncmp(n->name, LLAMA_TENSOR_NAME_FGDN_CH "-", prefix_len) == 0);
|
||||
const int il = std::stoi(n->name + prefix_len);
|
||||
ggml_backend_dev_t device_kv = model.dev_layer(il);
|
||||
if (device_gdn != device_kv) {
|
||||
LLAMA_LOG_WARN("%s: layer %d is assigned to device %s but the fused Gated Delta Net tensor "
|
||||
"is assigned to device %s (usually due to missing support)\n",
|
||||
__func__, il, ggml_backend_dev_name(device_kv), ggml_backend_dev_name(device_gdn));
|
||||
gdn_device_mismatch = true;
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
if (gdn_device_mismatch) {
|
||||
cparams.fused_gdn_ch = false;
|
||||
LLAMA_LOG_WARN("%s: fused Gated Delta Net (chunked) not supported, set to disabled\n", __func__);
|
||||
} else {
|
||||
LLAMA_LOG_INFO("%s: fused Gated Delta Net (chunked) enabled\n", __func__);
|
||||
}
|
||||
}
|
||||
|
||||
cparams.auto_fgdn = false;
|
||||
}
|
||||
resolve_fused_ops(mctx.get(), n_seqs);
|
||||
|
||||
// reserve worst-case graph
|
||||
int n_splits_pp = -1;
|
||||
|
||||
@@ -262,6 +262,10 @@ private:
|
||||
|
||||
llm_graph_cb graph_get_cb() const;
|
||||
|
||||
// disable auto fused ops (Flash Attention, Gated Delta Net) whose op lands on a device
|
||||
// that differs from the layer it belongs to (usually due to missing backend support)
|
||||
void resolve_fused_ops(const llama_memory_context_i * mctx, uint32_t n_seqs);
|
||||
|
||||
// TODO: read/write lora adapters and cvec
|
||||
size_t state_write_data(llama_io_write_i & io);
|
||||
size_t state_read_data (llama_io_read_i & io);
|
||||
|
||||
+8
-1
@@ -1192,6 +1192,7 @@ void llm_graph_result::reset() {
|
||||
params = {};
|
||||
|
||||
inputs.clear();
|
||||
fused_nodes.clear();
|
||||
|
||||
buf_compute_meta.resize(ggml_tensor_overhead()*max_nodes + ggml_graph_overhead_custom(max_nodes, false));
|
||||
|
||||
@@ -1293,6 +1294,10 @@ llm_graph_input_i * llm_graph_result::add_input(llm_graph_input_ptr input) {
|
||||
return inputs.back().get();
|
||||
}
|
||||
|
||||
void llm_graph_result::add_fused_node(llm_graph_fused_node result) {
|
||||
fused_nodes.push_back(result);
|
||||
}
|
||||
|
||||
void llm_graph_result::set_params(const llm_graph_params & params) {
|
||||
this->params = params;
|
||||
}
|
||||
@@ -1352,6 +1357,8 @@ void llm_graph_context::cb(ggml_tensor * cur, const char * name, int il) const {
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
|
||||
ggml_tensor * llm_graph_context::build_cvec(
|
||||
ggml_tensor * cur,
|
||||
int il) const {
|
||||
@@ -2402,7 +2409,7 @@ ggml_tensor * llm_graph_context::build_attn_mha(
|
||||
|
||||
cur = ggml_flash_attn_ext(ctx0, q, k, v, kq_mask, kq_scale, hparams.f_max_alibi_bias,
|
||||
hparams.attn_soft_cap ? hparams.f_attn_logit_softcapping : 0.0f);
|
||||
cb(cur, LLAMA_TENSOR_NAME_FATTN, il);
|
||||
res->add_fused_node({LLM_FUSED_OP_FLASH_ATTN, cur, il});
|
||||
|
||||
ggml_flash_attn_ext_add_sinks(cur, sinks);
|
||||
ggml_flash_attn_ext_set_prec (cur, GGML_PREC_F32);
|
||||
|
||||
@@ -38,6 +38,12 @@ enum llm_graph_type {
|
||||
LLM_GRAPH_TYPE_DECODER_MTP,
|
||||
};
|
||||
|
||||
enum llm_fused_op {
|
||||
LLM_FUSED_OP_FLASH_ATTN,
|
||||
LLM_FUSED_OP_GDN_AR,
|
||||
LLM_FUSED_OP_GDN_CH,
|
||||
};
|
||||
|
||||
enum llm_ffn_op_type : int {
|
||||
LLM_FFN_NONE = 0, // sentinel: unset; archs must assign before use
|
||||
LLM_FFN_SILU,
|
||||
@@ -775,6 +781,12 @@ struct llm_graph_params {
|
||||
}
|
||||
};
|
||||
|
||||
struct llm_graph_fused_node {
|
||||
llm_fused_op op;
|
||||
ggml_tensor * tensor;
|
||||
int il;
|
||||
};
|
||||
|
||||
class llm_graph_result {
|
||||
public:
|
||||
llm_graph_result(int64_t max_nodes);
|
||||
@@ -808,6 +820,10 @@ public:
|
||||
|
||||
llm_graph_input_i * add_input(llm_graph_input_ptr input);
|
||||
|
||||
void add_fused_node(llm_graph_fused_node result);
|
||||
|
||||
const std::vector<llm_graph_fused_node> & get_fused_nodes() const { return fused_nodes; }
|
||||
|
||||
void set_params(const llm_graph_params & params);
|
||||
|
||||
// important graph nodes
|
||||
@@ -826,6 +842,7 @@ public:
|
||||
std::map<llama_seq_id, ggml_tensor *> t_sampled_probs;
|
||||
|
||||
std::vector<llm_graph_input_ptr> inputs;
|
||||
std::vector<llm_graph_fused_node> fused_nodes;
|
||||
|
||||
ggml_context_ptr ctx_compute;
|
||||
|
||||
|
||||
@@ -103,7 +103,3 @@ std::string llama_format_tensor_shape(const std::vector<int64_t> & ne);
|
||||
std::string llama_format_tensor_shape(const struct ggml_tensor * t);
|
||||
|
||||
std::string gguf_kv_to_str(const struct gguf_context * ctx_gguf, int i);
|
||||
|
||||
#define LLAMA_TENSOR_NAME_FATTN "__fattn__"
|
||||
#define LLAMA_TENSOR_NAME_FGDN_AR "__fgdn_ar__"
|
||||
#define LLAMA_TENSOR_NAME_FGDN_CH "__fgdn_ch__"
|
||||
|
||||
@@ -113,7 +113,7 @@ llama_memory_context_ptr llama_kv_cache_dsa::init_batch(
|
||||
|
||||
std::vector<llama_ubatch> ubatches;
|
||||
while (true) {
|
||||
auto ubatch = n_stream == 1 ? balloc.split_simple(n_ubatch) : balloc.split_equal(n_ubatch, true);
|
||||
auto ubatch = n_stream == 1 ? balloc.split_simple(n_ubatch) : balloc.split_equal(n_ubatch, true, 0);
|
||||
|
||||
if (ubatch.n_tokens == 0) {
|
||||
break;
|
||||
|
||||
@@ -1110,7 +1110,7 @@ llama_memory_context_ptr llama_kv_cache_dsv4::init_batch(
|
||||
if (has_coupled) {
|
||||
ubatch = balloc.split_seq(n_ubatch);
|
||||
} else {
|
||||
ubatch = balloc.split_equal(n_ubatch, raw_per_seq || comp_per_seq);
|
||||
ubatch = balloc.split_equal(n_ubatch, raw_per_seq || comp_per_seq, 0);
|
||||
}
|
||||
|
||||
if (ubatch.n_tokens == 0) {
|
||||
|
||||
@@ -206,7 +206,7 @@ llama_memory_context_ptr llama_kv_cache_iswa::init_batch(llama_batch_allocr & ba
|
||||
|
||||
std::vector<llama_ubatch> ubatches;
|
||||
while (true) {
|
||||
auto ubatch = balloc.split_equal(n_ubatch, !unified);
|
||||
auto ubatch = balloc.split_equal(n_ubatch, !unified, 0);
|
||||
|
||||
if (ubatch.n_tokens == 0) {
|
||||
break;
|
||||
|
||||
@@ -706,7 +706,7 @@ llama_memory_context_ptr llama_kv_cache::init_batch(
|
||||
|
||||
std::vector<llama_ubatch> ubatches;
|
||||
while (true) {
|
||||
auto ubatch = n_stream == 1 ? balloc.split_simple(n_ubatch) : balloc.split_equal(n_ubatch, true);
|
||||
auto ubatch = n_stream == 1 ? balloc.split_simple(n_ubatch) : balloc.split_equal(n_ubatch, true, 0);
|
||||
|
||||
if (ubatch.n_tokens == 0) {
|
||||
break;
|
||||
|
||||
@@ -77,15 +77,15 @@ llama_memory_context_ptr llama_memory_hybrid_iswa::init_batch(llama_batch_allocr
|
||||
// if all tokens are output, split by sequence
|
||||
ubatch = balloc.split_seq(n_ubatch);
|
||||
} else {
|
||||
if (mem_recr->n_rs_seq > 0) {
|
||||
// [TAG_RECURRENT_ROLLBACK_SPLITS]
|
||||
// TODO: recurrent state rollback does not support equal splits
|
||||
ubatch = balloc.split_seq(n_ubatch);
|
||||
} else {
|
||||
// Use non-sequential split when KV cache is unified (needed for hellaswag/winogrande/multiple-choice)
|
||||
const bool unified = (mem_attn->get_base()->get_n_stream() == 1);
|
||||
ubatch = balloc.split_equal(n_ubatch, !unified);
|
||||
}
|
||||
// Use non-sequential split when KV cache is unified (needed for hellaswag/winogrande/multiple-choice)
|
||||
const bool unified = (mem_attn->get_base()->get_n_stream() == 1);
|
||||
|
||||
// [TAG_RECURRENT_ROLLBACK_SPLITS]
|
||||
// the trailing (1 + n_rs_seq) tokens of each seq must stay in the same ubatch
|
||||
// so that the rollback snapshots remain valid
|
||||
const uint32_t n_rs_seq = mem_recr->n_rs_seq;
|
||||
|
||||
ubatch = balloc.split_equal(n_ubatch, !unified, n_rs_seq > 0 ? n_rs_seq + 1 : 0);
|
||||
}
|
||||
|
||||
if (ubatch.n_tokens == 0) {
|
||||
|
||||
@@ -78,15 +78,15 @@ llama_memory_context_ptr llama_memory_hybrid::init_batch(llama_batch_allocr & ba
|
||||
// if all tokens are output, split by sequence
|
||||
ubatch = balloc.split_seq(n_ubatch);
|
||||
} else {
|
||||
if (mem_recr->n_rs_seq > 0) {
|
||||
// [TAG_RECURRENT_ROLLBACK_SPLITS]
|
||||
// TODO: recurrent state rollback does not support equal splits
|
||||
ubatch = balloc.split_seq(n_ubatch);
|
||||
} else {
|
||||
// Use non-sequential split when KV cache is unified (needed for hellaswag/winogrande/multiple-choice)
|
||||
const bool unified = (mem_attn->get_n_stream() == 1);
|
||||
ubatch = balloc.split_equal(n_ubatch, !unified);
|
||||
}
|
||||
// Use non-sequential split when KV cache is unified (needed for hellaswag/winogrande/multiple-choice)
|
||||
const bool unified = (mem_attn->get_n_stream() == 1);
|
||||
|
||||
// [TAG_RECURRENT_ROLLBACK_SPLITS]
|
||||
// the trailing (1 + n_rs_seq) tokens of each seq must stay in the same ubatch
|
||||
// so that the rollback snapshots remain valid
|
||||
const uint32_t n_rs_seq = mem_recr->n_rs_seq;
|
||||
|
||||
ubatch = balloc.split_equal(n_ubatch, !unified, n_rs_seq > 0 ? n_rs_seq + 1 : 0);
|
||||
}
|
||||
|
||||
if (ubatch.n_tokens == 0) {
|
||||
|
||||
@@ -416,15 +416,12 @@ llama_memory_context_ptr llama_memory_recurrent::init_batch(llama_batch_allocr &
|
||||
// if all tokens are output, split by sequence
|
||||
ubatch = balloc.split_seq(n_ubatch);
|
||||
} else {
|
||||
if (n_rs_seq > 0) {
|
||||
// [TAG_RECURRENT_ROLLBACK_SPLITS]
|
||||
// TODO: recurrent state rollback does not support equal splits
|
||||
ubatch = balloc.split_seq(n_ubatch);
|
||||
} else {
|
||||
// TODO: non-sequential equal split can be done if using unified KV cache
|
||||
// for simplicity, we always use sequential equal split for now
|
||||
ubatch = balloc.split_equal(n_ubatch, true);
|
||||
}
|
||||
// TODO: non-sequential equal split can be done if using unified KV cache
|
||||
// for simplicity, we always use sequential equal split for now
|
||||
// [TAG_RECURRENT_ROLLBACK_SPLITS]
|
||||
// the trailing (1 + n_rs_seq) tokens of each seq must stay in the same ubatch
|
||||
// so that the rollback snapshots remain valid
|
||||
ubatch = balloc.split_equal(n_ubatch, true, n_rs_seq > 0 ? n_rs_seq + 1 : 0);
|
||||
}
|
||||
|
||||
if (ubatch.n_tokens == 0) {
|
||||
|
||||
+19
-7
@@ -887,9 +887,6 @@ struct llm_tokenizer_ugm : llm_tokenizer {
|
||||
// blob containing XOR-compressed compact double array (XCDA) entries
|
||||
uint32_t xcda_blob_size = *(const uint32_t *) &precompiled_charsmap[0];
|
||||
charsmap_offset += sizeof(xcda_blob_size);
|
||||
if (xcda_blob_size + charsmap_offset >= precompiled_charsmap.size()) {
|
||||
throw std::runtime_error("Index out of array bounds in precompiled charsmap!");
|
||||
}
|
||||
|
||||
// Next xcda_blob_size bytes contain entries of XOR-compressed compact
|
||||
// double array (XCDA). Each entry is bit-packed into a 32-bit integer.
|
||||
@@ -1205,7 +1202,15 @@ private:
|
||||
throw std::runtime_error("Index out of array bounds in precompiled charsmap!");
|
||||
}
|
||||
const char * prefix_replacement = &(tokenizer.prefix_replacements)[longest_prefix_offset];
|
||||
return { prefix_replacement, strlen(prefix_replacement), longest_prefix_length };
|
||||
size_t max_len = tokenizer.prefix_replacements_size - longest_prefix_offset;
|
||||
size_t repl_len = 0;
|
||||
while (repl_len < max_len && prefix_replacement[repl_len] != '\0') {
|
||||
repl_len++;
|
||||
}
|
||||
if (repl_len == max_len) {
|
||||
throw std::runtime_error("Unterminated string in precompiled charsmap!");
|
||||
}
|
||||
return { prefix_replacement, repl_len, longest_prefix_length };
|
||||
}
|
||||
|
||||
// check if the input prefix contains a valid sequence of UTF-8 code units
|
||||
@@ -2018,11 +2023,18 @@ void llama_vocab::impl::load(llama_model_loader & ml, const LLM_KV & kv) {
|
||||
const size_t n_precompiled_charsmap = gguf_get_arr_n(ctx, precompiled_charsmap_keyidx);
|
||||
const char * pc = (const char *) gguf_get_arr_data(ctx, precompiled_charsmap_keyidx);
|
||||
precompiled_charsmap.assign(pc, pc + n_precompiled_charsmap);
|
||||
if (precompiled_charsmap.size() < sizeof(uint32_t)) {
|
||||
throw std::runtime_error("precompiled_charsmap too small for xcda_blob_size header!");
|
||||
}
|
||||
uint32_t * xcda_blob_size = (uint32_t *) &precompiled_charsmap[0];
|
||||
#if defined(__BYTE_ORDER__) && defined(__ORDER_BIG_ENDIAN__) && __BYTE_ORDER__ == __ORDER_BIG_ENDIAN__
|
||||
*xcda_blob_size = __builtin_bswap32(*xcda_blob_size);
|
||||
#endif
|
||||
if (*xcda_blob_size + sizeof(uint32_t) >= precompiled_charsmap.size()) {
|
||||
throw std::runtime_error("Index out of array bounds in precompiled charsmap!");
|
||||
}
|
||||
#if defined(__BYTE_ORDER__) && defined(__ORDER_BIG_ENDIAN__) && __BYTE_ORDER__ == __ORDER_BIG_ENDIAN__
|
||||
// correct endianness of data in precompiled_charsmap binary blob
|
||||
uint32_t * xcda_blob_size = (uint32_t *) &precompiled_charsmap[0];
|
||||
*xcda_blob_size = __builtin_bswap32(*xcda_blob_size);
|
||||
assert(*xcda_blob_size + sizeof(uint32_t) < n_precompiled_charsmap);
|
||||
size_t xcda_array_size = *xcda_blob_size / sizeof(uint32_t);
|
||||
uint32_t * xcda_array = (uint32_t *) &precompiled_charsmap[sizeof(uint32_t)];
|
||||
for (size_t i = 0; i < xcda_array_size; ++i) {
|
||||
|
||||
@@ -401,9 +401,9 @@ std::pair<ggml_tensor *, ggml_tensor *> llm_build_delta_net_base::build_delta_ne
|
||||
// K=1: output carries the final state only. state s is 4D [S_v, S_v, H_v, n_seqs].
|
||||
ggml_tensor * result = ggml_gated_delta_net(ctx0, q, k, v, g, b, s, /*K=*/1);
|
||||
if (n_tokens == 1) {
|
||||
cb(result, LLAMA_TENSOR_NAME_FGDN_AR, il);
|
||||
res->add_fused_node({LLM_FUSED_OP_GDN_AR, result, il});
|
||||
} else {
|
||||
cb(result, LLAMA_TENSOR_NAME_FGDN_CH, il);
|
||||
res->add_fused_node({LLM_FUSED_OP_GDN_CH, result, il});
|
||||
}
|
||||
|
||||
ggml_tensor * output = ggml_view_4d(ctx0, result,
|
||||
@@ -496,8 +496,8 @@ ggml_tensor * llm_build_delta_net_base::build_conv_state(
|
||||
ggml_build_forward_expand(gf, ggml_cpy(ctx0, conv_state_last, conv_state_update));
|
||||
} else {
|
||||
// [TAG_RECURRENT_ROLLBACK_SPLITS]
|
||||
// TODO: this logic incorrectly assumes that the last (n_rs_seq + 1) tokens of a sequence in a batch are
|
||||
// inside the same ubatch. currently with `split_equal()` this is not correct
|
||||
// this logic assumes that the last (n_rs_seq + 1) tokens of a sequence in a batch are inside
|
||||
// the same ubatch, which `split_equal()` guarantees via its n_keep_tail argument
|
||||
|
||||
const int64_t K = (int64_t) cparams.n_rs_seq + 1;
|
||||
|
||||
@@ -566,9 +566,9 @@ ggml_tensor * llm_build_delta_net_base::build_recurrent_attn(
|
||||
// state s is 4D [S_v, S_v, H_v, n_seqs]; K snapshot slots are written into the output.
|
||||
ggml_tensor * gdn_out = ggml_gated_delta_net(ctx0, q, k, v, g, b, s, K);
|
||||
if (n_seq_tokens > 1) {
|
||||
cb(gdn_out, LLAMA_TENSOR_NAME_FGDN_CH, il);
|
||||
res->add_fused_node({LLM_FUSED_OP_GDN_CH, gdn_out, il});
|
||||
} else {
|
||||
cb(gdn_out, LLAMA_TENSOR_NAME_FGDN_AR, il);
|
||||
res->add_fused_node({LLM_FUSED_OP_GDN_AR, gdn_out, il});
|
||||
}
|
||||
|
||||
const int64_t attn_score_elems = S_v * H_v * n_seq_tokens * n_seqs;
|
||||
|
||||
@@ -2,11 +2,13 @@
|
||||
|
||||
set(TARGET llama-cli-impl)
|
||||
|
||||
add_library(${TARGET} cli.cpp)
|
||||
add_library(${TARGET} cli.cpp
|
||||
cli-client.cpp
|
||||
cli-context.cpp)
|
||||
set_target_properties(${TARGET} PROPERTIES WINDOWS_EXPORT_ALL_SYMBOLS ON)
|
||||
|
||||
target_include_directories(${TARGET} PUBLIC ${CMAKE_CURRENT_SOURCE_DIR} ../server)
|
||||
target_link_libraries(${TARGET} PUBLIC server-context llama-common ${CMAKE_THREAD_LIBS_INIT})
|
||||
target_link_libraries(${TARGET} PUBLIC llama-server-impl llama-common ${CMAKE_THREAD_LIBS_INIT})
|
||||
|
||||
if(LLAMA_TOOLS_INSTALL)
|
||||
install(TARGETS ${TARGET} LIBRARY)
|
||||
|
||||
@@ -0,0 +1,130 @@
|
||||
#include "cli-client.h"
|
||||
|
||||
#include "http.h"
|
||||
|
||||
#include <algorithm>
|
||||
#include <chrono>
|
||||
#include <thread>
|
||||
|
||||
// generation can stall for a long time during prompt processing, so the
|
||||
// read timeout must be generous
|
||||
static constexpr time_t CLI_HTTP_READ_TIMEOUT_SEC = 3600;
|
||||
|
||||
// upper bound for the accumulated response body kept for error reporting
|
||||
static constexpr size_t CLI_HTTP_MAX_ERROR_BODY = 1024 * 1024;
|
||||
|
||||
// returns the path with the base url's path prefix prepended (if any)
|
||||
static std::string join_path(const common_http_url & parts, const std::string & path) {
|
||||
if (parts.path.empty() || parts.path == "/") {
|
||||
return path;
|
||||
}
|
||||
std::string prefix = parts.path;
|
||||
if (prefix.back() == '/') {
|
||||
prefix.pop_back();
|
||||
}
|
||||
return prefix + path;
|
||||
}
|
||||
|
||||
std::string cli_client::get(const std::string & path) {
|
||||
auto [cli, parts] = common_http_client(server_base);
|
||||
cli.set_read_timeout(CLI_HTTP_READ_TIMEOUT_SEC, 0);
|
||||
auto path_with_model = path + (model.empty() ? "" : ("?model=" + model));
|
||||
auto res = cli.Get(join_path(parts, path_with_model));
|
||||
if (!res) {
|
||||
throw std::runtime_error("failed to connect to " + server_base + ": " + httplib::to_string(res.error()));
|
||||
}
|
||||
if (res->status < 200 || res->status >= 300) {
|
||||
throw std::runtime_error("GET " + path + " failed with status " + std::to_string(res->status) + ": " + res->body);
|
||||
}
|
||||
return res->body;
|
||||
}
|
||||
|
||||
std::string cli_client::post(const std::string & path, const std::string & body) {
|
||||
auto [cli, parts] = common_http_client(server_base);
|
||||
cli.set_read_timeout(CLI_HTTP_READ_TIMEOUT_SEC, 0);
|
||||
auto res = cli.Post(join_path(parts, path), body, "application/json");
|
||||
if (!res) {
|
||||
throw std::runtime_error("failed to connect to " + server_base + ": " + httplib::to_string(res.error()));
|
||||
}
|
||||
if (res->status < 200 || res->status >= 300) {
|
||||
throw std::runtime_error("POST " + path + " failed with status " + std::to_string(res->status) + ": " + res->body);
|
||||
}
|
||||
return res->body;
|
||||
}
|
||||
|
||||
std::string cli_client::post_sse(const std::string & path,
|
||||
const std::string & body,
|
||||
const std::function<bool()> & should_stop,
|
||||
const std::function<void(const std::string &)> & on_data) {
|
||||
auto [cli, parts] = common_http_client(server_base);
|
||||
cli.set_read_timeout(CLI_HTTP_READ_TIMEOUT_SEC, 0);
|
||||
|
||||
std::string pending; // buffer for incomplete SSE lines
|
||||
std::string raw_body; // accumulated body, used only for error reporting
|
||||
|
||||
auto receiver = [&](const char * data, size_t len) -> bool {
|
||||
if (should_stop()) {
|
||||
return false; // aborts the request
|
||||
}
|
||||
if (raw_body.size() < CLI_HTTP_MAX_ERROR_BODY) {
|
||||
raw_body.append(data, std::min(len, CLI_HTTP_MAX_ERROR_BODY - raw_body.size()));
|
||||
}
|
||||
pending.append(data, len);
|
||||
size_t pos;
|
||||
while ((pos = pending.find('\n')) != std::string::npos) {
|
||||
std::string line = pending.substr(0, pos);
|
||||
pending.erase(0, pos + 1);
|
||||
if (!line.empty() && line.back() == '\r') {
|
||||
line.pop_back();
|
||||
}
|
||||
if (line.rfind("data: ", 0) != 0) {
|
||||
continue;
|
||||
}
|
||||
std::string payload = line.substr(6);
|
||||
if (payload == "[DONE]") {
|
||||
continue;
|
||||
}
|
||||
on_data(payload);
|
||||
}
|
||||
return true;
|
||||
};
|
||||
|
||||
httplib::Headers headers = {{"Accept", "text/event-stream"}};
|
||||
auto res = cli.Post(join_path(parts, path), headers, body, "application/json", receiver);
|
||||
|
||||
if (!res) {
|
||||
if (res.error() == httplib::Error::Canceled && should_stop()) {
|
||||
return ""; // cancelled by the user
|
||||
}
|
||||
return "failed to connect to " + server_base + ": " + httplib::to_string(res.error());
|
||||
}
|
||||
if (res->status < 200 || res->status >= 300) {
|
||||
if (!raw_body.empty()) {
|
||||
return raw_body;
|
||||
}
|
||||
return "request failed with status " + std::to_string(res->status);
|
||||
}
|
||||
return "";
|
||||
}
|
||||
|
||||
bool cli_client::wait_health(const std::function<bool()> & is_aborted) {
|
||||
int connect_attempts = 0;
|
||||
while (!is_aborted()) {
|
||||
auto [cli, parts] = common_http_client(server_base);
|
||||
cli.set_connection_timeout(1, 0);
|
||||
auto res = cli.Get(join_path(parts, "/health"));
|
||||
if (res) {
|
||||
if (res->status == 200) {
|
||||
return true;
|
||||
}
|
||||
// any other status means the server is up but not ready yet
|
||||
// (e.g. 503 while the model is still loading)
|
||||
} else if (++connect_attempts >= 10) {
|
||||
last_error = "failed to connect to " + server_base + ": " + httplib::to_string(res.error());
|
||||
return false;
|
||||
}
|
||||
std::this_thread::sleep_for(std::chrono::milliseconds(300));
|
||||
}
|
||||
last_error = "aborted while waiting for the server to become ready";
|
||||
return false;
|
||||
}
|
||||
@@ -0,0 +1,33 @@
|
||||
#pragma once
|
||||
|
||||
#include <functional>
|
||||
#include <string>
|
||||
|
||||
// openai-like client for CLI
|
||||
struct cli_client {
|
||||
std::string server_base; // base url, for example "http://127.0.0.1:8080"
|
||||
std::string last_error; // set when wait_health() fails
|
||||
|
||||
std::string model; // optional, set when the server has multiple models (router mode)
|
||||
|
||||
// simple GET request, returns the raw response body
|
||||
// throws std::runtime_error on transport error or non-2xx status
|
||||
std::string get(const std::string & path);
|
||||
|
||||
// simple POST request, returns the raw response body
|
||||
// throws std::runtime_error on transport error or non-2xx status
|
||||
std::string post(const std::string & path, const std::string & body);
|
||||
|
||||
// POST request with an SSE streaming response
|
||||
// on_data is invoked per "data:" event with the raw event payload
|
||||
// returns after the stream is finished (empty string on graceful exit)
|
||||
// otherwise, the raw error response body
|
||||
std::string post_sse(const std::string & path,
|
||||
const std::string & body,
|
||||
const std::function<bool()> & should_stop,
|
||||
const std::function<void(const std::string &)> & on_data);
|
||||
|
||||
// poll /health until the server is ready to accept requests
|
||||
// returns false if is_aborted returned true or the server is unreachable
|
||||
bool wait_health(const std::function<bool()> & is_aborted);
|
||||
};
|
||||
@@ -0,0 +1,622 @@
|
||||
#include "cli-context.h"
|
||||
#include "cli-ui.h"
|
||||
|
||||
#include "arg.h"
|
||||
#include "base64.hpp"
|
||||
#include "log.h"
|
||||
#include "console.h"
|
||||
|
||||
#define JSON_ASSERT GGML_ASSERT
|
||||
#include <nlohmann/json.hpp>
|
||||
|
||||
#include <algorithm>
|
||||
#include <cctype>
|
||||
#include <filesystem>
|
||||
#include <fstream>
|
||||
#include <map>
|
||||
#include <set>
|
||||
|
||||
using json = nlohmann::ordered_json;
|
||||
|
||||
struct cli_context_impl {
|
||||
json messages = json::array();
|
||||
json pending_media = json::array(); // staged multimodal content parts
|
||||
};
|
||||
|
||||
cli_context::cli_context(const common_params & params) : params(params), impl(new cli_context_impl()) {}
|
||||
|
||||
cli_context::~cli_context() {
|
||||
shutdown();
|
||||
}
|
||||
|
||||
std::atomic<bool> & cli_context::interrupted() {
|
||||
static std::atomic<bool> flag = false;
|
||||
return flag;
|
||||
}
|
||||
|
||||
static bool should_stop() {
|
||||
return cli_context::interrupted().load();
|
||||
}
|
||||
|
||||
static constexpr size_t FILE_GLOB_MAX_RESULTS = 100;
|
||||
|
||||
const char * LLAMA_ASCII_LOGO = R"(
|
||||
▄▄ ▄▄
|
||||
██ ██
|
||||
██ ██ ▀▀█▄ ███▄███▄ ▀▀█▄ ▄████ ████▄ ████▄
|
||||
██ ██ ▄█▀██ ██ ██ ██ ▄█▀██ ██ ██ ██ ██ ██
|
||||
██ ██ ▀█▄██ ██ ██ ██ ▀█▄██ ██ ▀████ ████▀ ████▀
|
||||
██ ██
|
||||
▀▀ ▀▀
|
||||
)";
|
||||
|
||||
// number of values an arg consumes on the command line
|
||||
static int arg_num_values(const common_arg & opt) {
|
||||
if (opt.value_hint_2 != nullptr) {
|
||||
return 2;
|
||||
}
|
||||
if (opt.value_hint != nullptr) {
|
||||
return 1;
|
||||
}
|
||||
return 0;
|
||||
}
|
||||
|
||||
static std::string format_error_message(const json & err) {
|
||||
if (err.contains("error") && err.at("error").is_object()) {
|
||||
const auto & e = err.at("error");
|
||||
if (e.contains("message") && e.at("message").is_string()) {
|
||||
return e.at("message").get<std::string>();
|
||||
}
|
||||
}
|
||||
return err.dump();
|
||||
}
|
||||
|
||||
// err is the raw response body of a failed request; it may or may not be JSON
|
||||
static std::string format_error_message(const std::string & err) {
|
||||
json parsed = json::parse(err, nullptr, false);
|
||||
if (!parsed.is_discarded()) {
|
||||
return format_error_message(parsed);
|
||||
}
|
||||
return err;
|
||||
}
|
||||
|
||||
static std::string media_type_from_ext(const std::string & fname) {
|
||||
std::string ext = std::filesystem::path(fname).extension().string();
|
||||
std::transform(ext.begin(), ext.end(), ext.begin(), [](unsigned char c) { return std::tolower(c); });
|
||||
if (ext == ".wav" || ext == ".mp3") {
|
||||
return "audio";
|
||||
}
|
||||
if (ext == ".mp4" || ext == ".avi" || ext == ".mkv" || ext == ".mov" || ext == ".webm") {
|
||||
return "video";
|
||||
}
|
||||
return "image";
|
||||
}
|
||||
|
||||
bool cli_context::init() {
|
||||
ui::init(params);
|
||||
|
||||
std::optional<ui::spinner> spinner;
|
||||
|
||||
bool use_external_server = !params.server_base.empty();
|
||||
if (use_external_server) {
|
||||
std::string base = params.server_base;
|
||||
while (!base.empty() && base.back() == '/') {
|
||||
base.pop_back();
|
||||
}
|
||||
client.server_base = base;
|
||||
|
||||
spinner.emplace("Connecting to server at " + base);
|
||||
} else {
|
||||
if (params.model.path.empty() && params.model.url.empty() &&
|
||||
params.model.hf_repo.empty() && params.model.docker_repo.empty()) {
|
||||
ui::show_error(
|
||||
"no model specified",
|
||||
"use -m <file.gguf> or -hf <user/repo> to run a local model,\n"
|
||||
"or --server-base <url> to connect to a running llama-server"
|
||||
);
|
||||
return false;
|
||||
}
|
||||
|
||||
spinner.emplace("\n\nLoading model...");
|
||||
|
||||
server.emplace();
|
||||
if (!server->start(params)) {
|
||||
ui::show_error("server start failed");
|
||||
return false;
|
||||
}
|
||||
if (!server->wait_ready(should_stop)) {
|
||||
if (!should_stop()) {
|
||||
ui::show_error("the server exited before becoming ready");
|
||||
}
|
||||
return false;
|
||||
}
|
||||
client.server_base = server->address();
|
||||
}
|
||||
|
||||
// for --server-base this is the main availability check; for a spawned
|
||||
// server it is a cheap sanity check on top of the ready signal
|
||||
auto is_aborted = [this]() {
|
||||
return should_stop() || (server && !server->alive());
|
||||
};
|
||||
bool healthy = false;
|
||||
try {
|
||||
healthy = client.wait_health(is_aborted);
|
||||
} catch (const std::exception & e) {
|
||||
client.last_error = e.what();
|
||||
}
|
||||
if (!healthy) {
|
||||
if (!should_stop()) {
|
||||
ui::show_error(client.last_error);
|
||||
}
|
||||
return false;
|
||||
}
|
||||
|
||||
if (use_external_server) {
|
||||
spinner.reset();
|
||||
if (!list_and_ask_models()) {
|
||||
return false;
|
||||
}
|
||||
// restore the spinner for the next step
|
||||
spinner.emplace("Waiting for server...");
|
||||
}
|
||||
|
||||
fetch_server_props();
|
||||
|
||||
return true;
|
||||
}
|
||||
|
||||
void cli_context::fetch_server_props() {
|
||||
try {
|
||||
json props = json::parse(client.get("/props"));
|
||||
model_name = props.value("model_alias", "");
|
||||
if (model_name.empty()) {
|
||||
const std::string path = props.value("model_path", "");
|
||||
if (!path.empty()) {
|
||||
model_name = std::filesystem::path(path).filename().string();
|
||||
}
|
||||
}
|
||||
model_ftype = props.value("model_ftype", "");
|
||||
build_info = props.value("build_info", "");
|
||||
if (props.contains("modalities") && props.at("modalities").is_object()) {
|
||||
const auto & modalities = props.at("modalities");
|
||||
has_vision = modalities.value("vision", false);
|
||||
has_audio = modalities.value("audio", false);
|
||||
has_video = modalities.value("video", false);
|
||||
}
|
||||
} catch (const std::exception & e) {
|
||||
// /props can be disabled on remote servers; not fatal
|
||||
LOG_DBG("failed to fetch /props: %s\n", e.what());
|
||||
}
|
||||
}
|
||||
|
||||
bool cli_context::list_and_ask_models() {
|
||||
json resp = json::parse(client.get("/v1/models"));
|
||||
if (!resp.contains("data") || !resp.at("data").is_array()) {
|
||||
throw std::runtime_error("invalid response from /v1/models");
|
||||
}
|
||||
std::vector<std::string> models;
|
||||
std::vector<std::string> models_display;
|
||||
for (const auto & m : resp.at("data")) {
|
||||
if (!m.contains("id") || !m.at("id").is_string()) {
|
||||
continue;
|
||||
}
|
||||
std::string name = m.at("id").get<std::string>();
|
||||
std::string display = name;
|
||||
if (m.contains("aliases") && m.at("aliases").is_array()) {
|
||||
std::vector<std::string> aliases;
|
||||
for (const auto & a : m.at("aliases")) {
|
||||
if (a.is_string()) {
|
||||
aliases.push_back(a.get<std::string>());
|
||||
}
|
||||
}
|
||||
if (!aliases.empty()) {
|
||||
display += " (" + string_join(aliases, ", ") + ")";
|
||||
}
|
||||
}
|
||||
models.push_back(name);
|
||||
models_display.push_back(display);
|
||||
}
|
||||
|
||||
// only one model: use it without asking
|
||||
if (models.size() == 1) {
|
||||
model_name = models[0];
|
||||
client.model = model_name;
|
||||
return true;
|
||||
}
|
||||
|
||||
std::string message = "\nAvailable models:";
|
||||
for (size_t i = 0; i < models_display.size(); ++i) {
|
||||
message += "\n " + std::to_string(i + 1) + ". " + models_display[i];
|
||||
}
|
||||
message += "\n";
|
||||
ui::show_message(message);
|
||||
std::string selection;
|
||||
while (selection.empty()) {
|
||||
if (should_stop()) {
|
||||
return false;
|
||||
}
|
||||
ui::user_turn user_turn;
|
||||
selection = user_turn.read_input(false, "Select model by number: ");
|
||||
if (selection.empty()) {
|
||||
continue;
|
||||
}
|
||||
try {
|
||||
size_t idx = std::stoul(selection);
|
||||
if (idx > 0 && idx <= models.size()) {
|
||||
model_name = models[idx - 1];
|
||||
client.model = model_name;
|
||||
ui::show_message("Selected model: " + model_name);
|
||||
break;
|
||||
}
|
||||
} catch (...) {
|
||||
// ignore
|
||||
}
|
||||
ui::show_error("Invalid selection. Please enter a valid number.");
|
||||
selection.clear();
|
||||
continue;
|
||||
}
|
||||
return true;
|
||||
}
|
||||
|
||||
void cli_context::add_system_prompt() {
|
||||
if (!params.system_prompt.empty()) {
|
||||
impl->messages.push_back({
|
||||
{"role", "system"},
|
||||
{"content", params.system_prompt}
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
void cli_context::push_user_message(const std::string & text) {
|
||||
json content;
|
||||
if (impl->pending_media.empty()) {
|
||||
content = text;
|
||||
} else {
|
||||
// multimodal message: media parts first, then the text
|
||||
content = impl->pending_media;
|
||||
content.push_back({
|
||||
{"type", "text"},
|
||||
{"text", text}
|
||||
});
|
||||
impl->pending_media = json::array();
|
||||
}
|
||||
impl->messages.push_back({
|
||||
{"role", "user"},
|
||||
{"content", content}
|
||||
});
|
||||
}
|
||||
|
||||
bool cli_context::stage_media_file(const std::string & fname, const std::string & type) {
|
||||
std::ifstream file(fname, std::ios::binary);
|
||||
if (!file) {
|
||||
return false;
|
||||
}
|
||||
std::string data((std::istreambuf_iterator<char>(file)), std::istreambuf_iterator<char>());
|
||||
std::string encoded = base64::encode(data);
|
||||
|
||||
if (type == "audio") {
|
||||
std::string ext = std::filesystem::path(fname).extension().string();
|
||||
std::transform(ext.begin(), ext.end(), ext.begin(), [](unsigned char c) { return std::tolower(c); });
|
||||
impl->pending_media.push_back({
|
||||
{"type", "input_audio"},
|
||||
{"input_audio", {
|
||||
{"data", encoded},
|
||||
{"format", ext == ".mp3" ? "mp3" : "wav"}
|
||||
}}
|
||||
});
|
||||
} else if (type == "video") {
|
||||
impl->pending_media.push_back({
|
||||
{"type", "input_video"},
|
||||
{"input_video", {
|
||||
{"data", encoded}
|
||||
}}
|
||||
});
|
||||
} else {
|
||||
// the server detects the actual image type from the data
|
||||
impl->pending_media.push_back({
|
||||
{"type", "image_url"},
|
||||
{"image_url", {
|
||||
{"url", "data:image/unknown;base64," + encoded}
|
||||
}}
|
||||
});
|
||||
}
|
||||
return true;
|
||||
}
|
||||
|
||||
bool cli_context::generate_completion(std::string & assistant_content, cli_timings & timings) {
|
||||
json body = {
|
||||
{"messages", impl->messages},
|
||||
{"stream", true},
|
||||
// in order to get timings even when we cancel mid-way
|
||||
{"timings_per_token", true},
|
||||
};
|
||||
if (!client.model.empty()) {
|
||||
body["model"] = client.model;
|
||||
}
|
||||
|
||||
bool stream_error = false;
|
||||
|
||||
ui::assistant_turn a;
|
||||
|
||||
std::string err = client.post_sse("/v1/chat/completions", body.dump(), should_stop, [&](const std::string & payload) {
|
||||
json chunk = json::parse(payload, nullptr, false);
|
||||
if (chunk.is_discarded()) {
|
||||
return;
|
||||
}
|
||||
if (chunk.contains("error")) {
|
||||
stream_error = true;
|
||||
ui::show_error(format_error_message(chunk));
|
||||
return;
|
||||
}
|
||||
if (chunk.contains("timings")) {
|
||||
const auto & t = chunk.at("timings");
|
||||
timings.prompt_per_second = t.value("prompt_per_second", 0.0);
|
||||
timings.predicted_per_second = t.value("predicted_per_second", 0.0);
|
||||
}
|
||||
if (!chunk.contains("choices") || !chunk.at("choices").is_array() || chunk.at("choices").empty()) {
|
||||
return;
|
||||
}
|
||||
const auto & choice = chunk.at("choices").at(0);
|
||||
if (!choice.contains("delta")) {
|
||||
return;
|
||||
}
|
||||
const auto & delta = choice.at("delta");
|
||||
if (delta.contains("reasoning_content") && delta.at("reasoning_content").is_string()) {
|
||||
const std::string text = delta.at("reasoning_content").get<std::string>();
|
||||
if (!text.empty()) {
|
||||
a.push(ui::ASSISTANT_DISPLAY_MODE_REASONING, text);
|
||||
}
|
||||
}
|
||||
if (delta.contains("content") && delta.at("content").is_string()) {
|
||||
const std::string text = delta.at("content").get<std::string>();
|
||||
if (!text.empty()) {
|
||||
assistant_content += text;
|
||||
a.push(ui::ASSISTANT_DISPLAY_MODE_CONTENT, text);
|
||||
}
|
||||
}
|
||||
});
|
||||
|
||||
cli_context::interrupted().store(false);
|
||||
|
||||
if (!err.empty()) {
|
||||
ui::show_error(format_error_message(err));
|
||||
return false;
|
||||
}
|
||||
return !stream_error;
|
||||
}
|
||||
|
||||
int cli_context::run() {
|
||||
add_system_prompt();
|
||||
|
||||
std::string modalities = "text";
|
||||
if (has_vision) {
|
||||
modalities += ", vision";
|
||||
}
|
||||
if (has_audio) {
|
||||
modalities += ", audio";
|
||||
}
|
||||
if (has_video) {
|
||||
modalities += ", video";
|
||||
}
|
||||
|
||||
std::string banner;
|
||||
banner += "\n";
|
||||
banner += LLAMA_ASCII_LOGO;
|
||||
banner += "\n";
|
||||
banner += "build : " + build_info + "\n";
|
||||
banner += "model : " + model_name + "\n";
|
||||
if (!model_ftype.empty()) {
|
||||
banner += "ftype : " + model_ftype + "\n";
|
||||
}
|
||||
banner += "modalities : " + modalities + "\n";
|
||||
if (!params.system_prompt.empty()) {
|
||||
banner += "using custom system prompt\n";
|
||||
}
|
||||
banner += "\n";
|
||||
banner += "available commands:\n";
|
||||
banner += " /exit or Ctrl+C stop or exit\n";
|
||||
banner += " /regen regenerate the last response\n";
|
||||
banner += " /clear clear the chat history\n";
|
||||
banner += " /read <file> add a text file\n";
|
||||
banner += " /glob <pattern> add text files using globbing pattern\n";
|
||||
if (has_vision) {
|
||||
banner += " /image <file> add an image file\n";
|
||||
}
|
||||
if (has_audio) {
|
||||
banner += " /audio <file> add an audio file\n";
|
||||
}
|
||||
if (has_video) {
|
||||
banner += " /video <file> add a video file\n";
|
||||
}
|
||||
banner += "\n";
|
||||
|
||||
ui::show_message(banner);
|
||||
|
||||
// interactive loop
|
||||
std::string cur_msg;
|
||||
|
||||
auto add_text_file = [&](const std::string & fname) -> bool {
|
||||
std::ifstream file(fname, std::ios::binary);
|
||||
if (!file) {
|
||||
ui::show_error(string_format("file does not exist or cannot be opened: '%s'", fname.c_str()));
|
||||
return false;
|
||||
}
|
||||
std::string content((std::istreambuf_iterator<char>(file)), std::istreambuf_iterator<char>());
|
||||
cur_msg += "--- File: ";
|
||||
cur_msg += fname;
|
||||
cur_msg += " ---\n";
|
||||
cur_msg += content;
|
||||
ui::show_message(string_format("Loaded text from '%s'", fname.c_str()));
|
||||
return true;
|
||||
};
|
||||
|
||||
while (true) {
|
||||
std::string buffer;
|
||||
{
|
||||
ui::user_turn user_turn;
|
||||
|
||||
if (params.prompt.empty()) {
|
||||
buffer = user_turn.read_input(params.multiline_input);
|
||||
} else {
|
||||
// process input prompt from args
|
||||
for (auto & fname : params.image) {
|
||||
if (!stage_media_file(fname, media_type_from_ext(fname))) {
|
||||
ui::show_error(string_format("file does not exist or cannot be opened: '%s'", fname.c_str()));
|
||||
break;
|
||||
}
|
||||
ui::show_message(string_format("Loaded media from '%s'", fname.c_str()));
|
||||
}
|
||||
buffer = params.prompt;
|
||||
user_turn.echo(buffer);
|
||||
params.prompt.clear(); // only use it once
|
||||
}
|
||||
}
|
||||
|
||||
if (should_stop()) {
|
||||
cli_context::interrupted().store(false);
|
||||
break;
|
||||
}
|
||||
|
||||
// remove trailing newline
|
||||
if (!buffer.empty() && buffer.back() == '\n') {
|
||||
buffer.pop_back();
|
||||
}
|
||||
|
||||
// skip empty messages
|
||||
if (buffer.empty()) {
|
||||
continue;
|
||||
}
|
||||
|
||||
bool add_user_msg = true;
|
||||
|
||||
// process commands
|
||||
if (string_starts_with(buffer, "/exit")) {
|
||||
break;
|
||||
} else if (string_starts_with(buffer, "/regen")) {
|
||||
if (impl->messages.size() >= 2) {
|
||||
size_t last_idx = impl->messages.size() - 1;
|
||||
impl->messages.erase(last_idx);
|
||||
add_user_msg = false;
|
||||
} else {
|
||||
ui::show_error("No message to regenerate.");
|
||||
continue;
|
||||
}
|
||||
} else if (string_starts_with(buffer, "/clear")) {
|
||||
impl->messages.clear();
|
||||
add_system_prompt();
|
||||
|
||||
impl->pending_media = json::array();
|
||||
ui::show_message("Chat history cleared.");
|
||||
continue;
|
||||
} else if (
|
||||
(string_starts_with(buffer, "/image ") && has_vision) ||
|
||||
(string_starts_with(buffer, "/audio ") && has_audio) ||
|
||||
(string_starts_with(buffer, "/video ") && has_video)) {
|
||||
std::string type = buffer.substr(1, 5);
|
||||
// just in case (bad copy-paste for example), we strip all trailing/leading spaces
|
||||
std::string fname = string_strip(buffer.substr(7));
|
||||
if (!stage_media_file(fname, type)) {
|
||||
ui::show_error(string_format("file does not exist or cannot be opened: '%s'", fname.c_str()));
|
||||
continue;
|
||||
}
|
||||
ui::show_message(string_format("Loaded media from '%s'", fname.c_str()));
|
||||
continue;
|
||||
} else if (string_starts_with(buffer, "/read ")) {
|
||||
std::string fname = string_strip(buffer.substr(6));
|
||||
add_text_file(fname);
|
||||
continue;
|
||||
} else if (string_starts_with(buffer, "/glob ")) {
|
||||
std::error_code ec;
|
||||
size_t count = 0;
|
||||
auto curdir = std::filesystem::current_path();
|
||||
std::string pattern = string_strip(buffer.substr(6));
|
||||
std::filesystem::path rel_path;
|
||||
|
||||
auto startglob = pattern.find_first_of("![*?");
|
||||
if (startglob != std::string::npos && startglob != 0) {
|
||||
auto endpath = pattern.substr(0, startglob).find_last_of('/');
|
||||
if (endpath != std::string::npos) {
|
||||
std::string rel_pattern = pattern.substr(0, endpath);
|
||||
#if !defined(_WIN32)
|
||||
if (string_starts_with(rel_pattern, '~')) {
|
||||
const char * home = std::getenv("HOME");
|
||||
if (home && home[0]) {
|
||||
rel_pattern = home + rel_pattern.substr(1);
|
||||
}
|
||||
}
|
||||
#endif
|
||||
rel_path = rel_pattern;
|
||||
pattern.erase(0, endpath + 1);
|
||||
curdir /= rel_path;
|
||||
}
|
||||
}
|
||||
|
||||
for (const auto & entry : std::filesystem::recursive_directory_iterator(curdir,
|
||||
std::filesystem::directory_options::skip_permission_denied, ec)) {
|
||||
if (!entry.is_regular_file()) {
|
||||
continue;
|
||||
}
|
||||
|
||||
std::string rel = std::filesystem::relative(entry.path(), curdir, ec).string();
|
||||
if (ec) {
|
||||
ec.clear();
|
||||
continue;
|
||||
}
|
||||
std::replace(rel.begin(), rel.end(), '\\', '/');
|
||||
|
||||
if (!glob_match(pattern, rel)) {
|
||||
continue;
|
||||
}
|
||||
|
||||
if (!add_text_file((rel_path / rel).string())) {
|
||||
continue;
|
||||
}
|
||||
|
||||
if (++count >= FILE_GLOB_MAX_RESULTS) {
|
||||
ui::show_error(string_format("Maximum number of globbed files allowed (%zu) reached.", FILE_GLOB_MAX_RESULTS));
|
||||
break;
|
||||
}
|
||||
}
|
||||
continue;
|
||||
} else {
|
||||
// not a command
|
||||
cur_msg += buffer;
|
||||
}
|
||||
|
||||
// generate response
|
||||
if (add_user_msg) {
|
||||
push_user_message(cur_msg);
|
||||
cur_msg.clear();
|
||||
}
|
||||
cli_timings timings;
|
||||
std::string assistant_content;
|
||||
generate_completion(assistant_content, timings);
|
||||
impl->messages.push_back({
|
||||
{"role", "assistant"},
|
||||
{"content", assistant_content}
|
||||
});
|
||||
|
||||
if (params.show_timings) {
|
||||
ui::show_info(string_format(
|
||||
"\n[ Prompt: %.1f t/s | Generation: %.1f t/s ]",
|
||||
timings.prompt_per_second,
|
||||
timings.predicted_per_second
|
||||
));
|
||||
}
|
||||
|
||||
if (params.single_turn) {
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
ui::show_message("\n\nExiting...");
|
||||
|
||||
return 0;
|
||||
}
|
||||
|
||||
void cli_context::shutdown() {
|
||||
if (server) {
|
||||
server->stop();
|
||||
server.reset();
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,66 @@
|
||||
#pragma once
|
||||
|
||||
#include "common.h"
|
||||
|
||||
#include "cli-client.h"
|
||||
#include "cli-server.h"
|
||||
|
||||
#include <atomic>
|
||||
#include <memory>
|
||||
#include <optional>
|
||||
#include <string>
|
||||
|
||||
struct cli_timings {
|
||||
double prompt_per_second = 0.0;
|
||||
double predicted_per_second = 0.0;
|
||||
};
|
||||
|
||||
struct cli_context_impl;
|
||||
|
||||
struct cli_context {
|
||||
common_params params;
|
||||
|
||||
cli_client client; // always initialized
|
||||
std::optional<cli_server> server; // only set when no --server-base is given
|
||||
|
||||
// properties of the connected server
|
||||
// will be populated by fetch_server_props()
|
||||
std::string model_name;
|
||||
std::string model_ftype;
|
||||
std::string build_info;
|
||||
bool has_vision = false;
|
||||
bool has_audio = false;
|
||||
bool has_video = false;
|
||||
|
||||
cli_context(const common_params & params);
|
||||
~cli_context();
|
||||
|
||||
// connect to --server-base or spawn a local llama-server child;
|
||||
// argc/argv are needed to forward the server-relevant args to the child
|
||||
bool init();
|
||||
|
||||
// run the interactive chat loop, returns the process exit code
|
||||
int run();
|
||||
|
||||
// stop the local server child (if any)
|
||||
void shutdown();
|
||||
|
||||
// set by the SIGINT handler; cleared once the interrupt has been handled
|
||||
static std::atomic<bool> & interrupted();
|
||||
|
||||
private:
|
||||
bool generate_completion(std::string & assistant_content, cli_timings & timings);
|
||||
void fetch_server_props();
|
||||
void add_system_prompt();
|
||||
void push_user_message(const std::string & text);
|
||||
|
||||
// check if server have multiple models (router mode)
|
||||
// if yes, list them then ask; do nothing otherwise
|
||||
bool list_and_ask_models();
|
||||
|
||||
// read a file and stage it as a multimodal content part; type is one of
|
||||
// "image", "audio", "video"; returns false if the file cannot be read
|
||||
bool stage_media_file(const std::string & fname, const std::string & type);
|
||||
|
||||
std::unique_ptr<cli_context_impl> impl;
|
||||
};
|
||||
@@ -0,0 +1,89 @@
|
||||
#pragma once
|
||||
|
||||
#include <thread>
|
||||
|
||||
#include "http.h"
|
||||
|
||||
// llama_server will be available as a dynamic library symbol
|
||||
int llama_server(common_params & params, int argc, char ** argv);
|
||||
void llama_server_terminate();
|
||||
|
||||
struct cli_server {
|
||||
std::thread th;
|
||||
int port = -1;
|
||||
std::atomic<bool> is_alive = false;
|
||||
std::atomic<bool> is_stopping = false;
|
||||
|
||||
~cli_server() {
|
||||
stop();
|
||||
}
|
||||
|
||||
void stop() {
|
||||
if (is_stopping.exchange(true)) {
|
||||
return;
|
||||
}
|
||||
if (alive()) {
|
||||
llama_server_terminate();
|
||||
}
|
||||
if (th.joinable()) {
|
||||
th.join();
|
||||
}
|
||||
}
|
||||
|
||||
// spawn llama-server in a thread and interact with it via a random port
|
||||
bool start(common_params & params) {
|
||||
port = common_http_get_free_port();
|
||||
if (port <= 0) {
|
||||
fprintf(stderr, "failed to get a free port\n");
|
||||
exit(1);
|
||||
}
|
||||
|
||||
is_alive.store(true, std::memory_order_release);
|
||||
|
||||
common_params server_params = params; // copy
|
||||
server_params.port = port;
|
||||
|
||||
th = std::thread([this, server_params]() mutable {
|
||||
// argc / argv are only used in router mode, we can skip them for now
|
||||
int res = llama_server(server_params, 0, nullptr);
|
||||
if (res != 0) {
|
||||
fprintf(stderr, "llama_server exited with code %d\n", res);
|
||||
}
|
||||
is_alive.store(false, std::memory_order_release);
|
||||
});
|
||||
|
||||
return true;
|
||||
}
|
||||
|
||||
std::string address() const {
|
||||
return "http://127.0.0.1:" + std::to_string(port);
|
||||
}
|
||||
|
||||
bool wait_ready(std::function<bool()> should_stop) {
|
||||
if (!alive()) {
|
||||
return false;
|
||||
}
|
||||
while (!should_stop()) {
|
||||
auto [cli, parts] = common_http_client(address());
|
||||
cli.set_connection_timeout(1, 0);
|
||||
auto res = cli.Get("/health");
|
||||
if (res) {
|
||||
if (res->status == 200) {
|
||||
return true;
|
||||
}
|
||||
// any other status means the server is up but not ready yet
|
||||
// (e.g. 503 while the model is still loading)
|
||||
}
|
||||
if (!alive()) {
|
||||
// in case server die permanently
|
||||
return false;
|
||||
}
|
||||
std::this_thread::sleep_for(std::chrono::milliseconds(200));
|
||||
}
|
||||
return true;
|
||||
}
|
||||
|
||||
bool alive() const {
|
||||
return is_alive.load(std::memory_order_acquire);
|
||||
}
|
||||
};
|
||||
@@ -0,0 +1,251 @@
|
||||
#pragma once
|
||||
|
||||
#include "common.h"
|
||||
#include "console.h"
|
||||
|
||||
#include <array>
|
||||
#include <algorithm>
|
||||
#include <cctype>
|
||||
#include <filesystem>
|
||||
#include <string_view>
|
||||
|
||||
// TODO?: Make this reusable, enums, docs
|
||||
static const std::array<std::string_view, 8> cmds = {
|
||||
"/audio ",
|
||||
"/clear",
|
||||
"/exit",
|
||||
"/glob ",
|
||||
"/image ",
|
||||
"/read ",
|
||||
"/regen",
|
||||
"/video ",
|
||||
};
|
||||
|
||||
static std::vector<std::pair<std::string, size_t>> auto_completion_callback(std::string_view line, size_t cursor_byte_pos) {
|
||||
std::vector<std::pair<std::string, size_t>> matches;
|
||||
std::string cmd;
|
||||
|
||||
if (line.length() > 1 && line.front() == '/' && !std::any_of(cmds.begin(), cmds.end(), [line](std::string_view prefix) {
|
||||
return string_starts_with(line, prefix);
|
||||
})) {
|
||||
auto it = cmds.begin();
|
||||
|
||||
while ((it = std::find_if(it, cmds.end(), [line](std::string_view cmd_line) {
|
||||
return string_starts_with(cmd_line, line);
|
||||
})) != cmds.end()) {
|
||||
matches.emplace_back(*it, it->length());
|
||||
++it;
|
||||
}
|
||||
} else {
|
||||
auto it = std::find_if(cmds.begin(), cmds.end(), [line](std::string_view prefix) {
|
||||
return prefix.back() == ' ' && string_starts_with(line, prefix);
|
||||
});
|
||||
|
||||
if (it != cmds.end()) {
|
||||
cmd = *it;
|
||||
}
|
||||
}
|
||||
|
||||
if (!cmd.empty() && cmd != "/glob " && line.length() >= cmd.length() && cursor_byte_pos >= cmd.length()) {
|
||||
const std::string path_prefix = std::string(line.substr(cmd.length(), cursor_byte_pos - cmd.length()));
|
||||
const std::string path_postfix = std::string(line.substr(cursor_byte_pos));
|
||||
auto cur_dir = std::filesystem::current_path();
|
||||
std::string cur_dir_str = cur_dir.string();
|
||||
std::string expanded_prefix = path_prefix;
|
||||
|
||||
#if !defined(_WIN32)
|
||||
if (string_starts_with(path_prefix, '~')) {
|
||||
const char * home = std::getenv("HOME");
|
||||
if (home && home[0]) {
|
||||
expanded_prefix = home + path_prefix.substr(1);
|
||||
}
|
||||
}
|
||||
if (string_starts_with(expanded_prefix, '/')) {
|
||||
#else
|
||||
if (std::isalpha(static_cast<unsigned char>(expanded_prefix[0])) && expanded_prefix.find(':') == 1) {
|
||||
#endif
|
||||
cur_dir = std::filesystem::path(expanded_prefix).parent_path();
|
||||
cur_dir_str.clear();
|
||||
} else if (!path_prefix.empty()) {
|
||||
cur_dir /= std::filesystem::path(path_prefix).parent_path();
|
||||
}
|
||||
|
||||
std::error_code ec;
|
||||
for (const auto & entry : std::filesystem::directory_iterator(cur_dir, ec)) {
|
||||
if (ec) {
|
||||
break;
|
||||
}
|
||||
if (!entry.exists(ec)) {
|
||||
ec.clear();
|
||||
continue;
|
||||
}
|
||||
|
||||
const std::string path_full = entry.path().string();
|
||||
std::string path_entry = !cur_dir_str.empty() && string_starts_with(path_full, cur_dir_str) ? path_full.substr(cur_dir_str.length() + 1) : path_full;
|
||||
|
||||
if (entry.is_directory(ec)) {
|
||||
path_entry.push_back(std::filesystem::path::preferred_separator);
|
||||
}
|
||||
|
||||
if (expanded_prefix.empty() || string_starts_with(path_entry, expanded_prefix)) {
|
||||
const std::string updated_line = cmd + path_entry;
|
||||
matches.emplace_back(updated_line + path_postfix, updated_line.length());
|
||||
}
|
||||
|
||||
if (ec) {
|
||||
ec.clear();
|
||||
}
|
||||
}
|
||||
|
||||
if (matches.empty()) {
|
||||
const std::string updated_line = cmd + path_prefix;
|
||||
matches.emplace_back(updated_line + path_postfix, updated_line.length());
|
||||
}
|
||||
|
||||
// Add the longest common prefix
|
||||
if (!expanded_prefix.empty() && matches.size() > 1) {
|
||||
const std::string_view match0(matches[0].first);
|
||||
const std::string_view match1(matches[1].first);
|
||||
auto it = std::mismatch(match0.begin(), match0.end(), match1.begin(), match1.end());
|
||||
size_t len = it.first - match0.begin();
|
||||
|
||||
for (size_t i = 2; i < matches.size(); ++i) {
|
||||
const std::string_view matchi(matches[i].first);
|
||||
auto cmp = std::mismatch(match0.begin(), match0.end(), matchi.begin(), matchi.end());
|
||||
len = std::min(len, static_cast<size_t>(cmp.first - match0.begin()));
|
||||
}
|
||||
|
||||
const std::string updated_line = std::string(match0.substr(0, len));
|
||||
matches.emplace_back(updated_line + path_postfix, updated_line.length());
|
||||
}
|
||||
|
||||
std::sort(matches.begin(), matches.end(), [](const auto & a, const auto & b) {
|
||||
return a.first.compare(0, a.second, b.first, 0, b.second) < 0;
|
||||
});
|
||||
}
|
||||
|
||||
return matches;
|
||||
}
|
||||
|
||||
// note: make this view implementation generic, so that we can move to TUI in the future if we want to
|
||||
namespace ui {
|
||||
static void init(const common_params & params) {
|
||||
// TODO: avoid using atexit() here by making `console` a singleton
|
||||
console::init(params.simple_io, params.use_color);
|
||||
atexit([]() { console::cleanup(); });
|
||||
|
||||
console::set_completion_callback(auto_completion_callback);
|
||||
}
|
||||
|
||||
struct spinner {
|
||||
spinner(const std::string & message) {
|
||||
if (!message.empty()) {
|
||||
console::log("%s ", message.c_str());
|
||||
}
|
||||
console::spinner::start();
|
||||
}
|
||||
~spinner() {
|
||||
console::spinner::stop();
|
||||
}
|
||||
};
|
||||
|
||||
struct user_turn {
|
||||
user_turn() {
|
||||
console::set_display(DISPLAY_TYPE_USER_INPUT);
|
||||
}
|
||||
~user_turn() {
|
||||
console::set_display(DISPLAY_TYPE_RESET);
|
||||
}
|
||||
void echo(const std::string & buffer) {
|
||||
if (buffer.size() > 500) {
|
||||
console::log("\n> %s ... (truncated)\n", buffer.substr(0, 500).c_str());
|
||||
} else {
|
||||
console::log("\n> %s\n", buffer.c_str());
|
||||
}
|
||||
}
|
||||
std::string read_input(bool multiline_input, const char * prompt = nullptr) {
|
||||
if (prompt) {
|
||||
console::log("%s", prompt);
|
||||
} else {
|
||||
console::log("\n> ");
|
||||
}
|
||||
std::string buffer;
|
||||
std::string line;
|
||||
bool another_line = true;
|
||||
do {
|
||||
another_line = console::readline(line, multiline_input);
|
||||
buffer += line;
|
||||
} while (another_line);
|
||||
return buffer;
|
||||
}
|
||||
};
|
||||
|
||||
enum assistant_display_mode {
|
||||
ASSISTANT_DISPLAY_MODE_REASONING,
|
||||
ASSISTANT_DISPLAY_MODE_CONTENT,
|
||||
};
|
||||
struct assistant_turn {
|
||||
assistant_display_mode mode = ASSISTANT_DISPLAY_MODE_CONTENT;
|
||||
bool trailing_newline = true;
|
||||
bool is_inside_reasoning = false;
|
||||
assistant_turn() {
|
||||
console::set_display(DISPLAY_TYPE_RESET);
|
||||
}
|
||||
~assistant_turn() {
|
||||
console::set_display(DISPLAY_TYPE_RESET);
|
||||
add_newline_if_needed();
|
||||
}
|
||||
void push(assistant_display_mode m, const std::string & buffer) {
|
||||
if (m != mode) {
|
||||
add_newline_if_needed();
|
||||
switch (m) {
|
||||
case ASSISTANT_DISPLAY_MODE_CONTENT:
|
||||
{
|
||||
if (is_inside_reasoning) {
|
||||
console::log("[End thinking]\n\n");
|
||||
is_inside_reasoning = false;
|
||||
}
|
||||
console::set_display(DISPLAY_TYPE_RESET);
|
||||
} break;
|
||||
case ASSISTANT_DISPLAY_MODE_REASONING:
|
||||
{
|
||||
console::set_display(DISPLAY_TYPE_REASONING);
|
||||
is_inside_reasoning = true;
|
||||
console::log("\n[Start thinking]\n\n");
|
||||
} break;
|
||||
}
|
||||
}
|
||||
mode = m;
|
||||
if (buffer.empty()) {
|
||||
return;
|
||||
}
|
||||
trailing_newline = buffer.back() == '\n';
|
||||
console::log("%s", buffer.c_str());
|
||||
console::flush();
|
||||
}
|
||||
void add_newline_if_needed() {
|
||||
if (!trailing_newline) {
|
||||
console::log("\n");
|
||||
console::flush();
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
static void show_error(const std::string & title, const std::string & message = "") {
|
||||
console::spinner::stop();
|
||||
console::error("Error: %s\n", title.c_str());
|
||||
if (!message.empty()) {
|
||||
console::log("%s\n", message.c_str());
|
||||
}
|
||||
}
|
||||
|
||||
static void show_message(const std::string & message) {
|
||||
console::log("%s\n", message.c_str());
|
||||
}
|
||||
|
||||
static void show_info(const std::string & message) {
|
||||
console::set_display(DISPLAY_TYPE_INFO);
|
||||
console::log("%s\n", message.c_str());
|
||||
console::set_display(DISPLAY_TYPE_RESET);
|
||||
}
|
||||
}
|
||||
+9
-627
@@ -1,20 +1,9 @@
|
||||
#include "chat.h"
|
||||
#include "common.h"
|
||||
#include "arg.h"
|
||||
#include "console.h"
|
||||
#include "fit.h"
|
||||
// #include "log.h"
|
||||
#include "common.h"
|
||||
#include "log.h"
|
||||
|
||||
#include "server-common.h"
|
||||
#include "server-context.h"
|
||||
#include "server-task.h"
|
||||
#include "cli-context.h"
|
||||
|
||||
#include <array>
|
||||
#include <atomic>
|
||||
#include <algorithm>
|
||||
#include <filesystem>
|
||||
#include <fstream>
|
||||
#include <thread>
|
||||
#include <signal.h>
|
||||
|
||||
#if defined(_WIN32)
|
||||
@@ -25,342 +14,19 @@
|
||||
#include <windows.h>
|
||||
#endif
|
||||
|
||||
const char * LLAMA_ASCII_LOGO = R"(
|
||||
▄▄ ▄▄
|
||||
██ ██
|
||||
██ ██ ▀▀█▄ ███▄███▄ ▀▀█▄ ▄████ ████▄ ████▄
|
||||
██ ██ ▄█▀██ ██ ██ ██ ▄█▀██ ██ ██ ██ ██ ██
|
||||
██ ██ ▀█▄██ ██ ██ ██ ▀█▄██ ██ ▀████ ████▀ ████▀
|
||||
██ ██
|
||||
▀▀ ▀▀
|
||||
)";
|
||||
|
||||
static std::atomic<bool> g_is_interrupted = false;
|
||||
static bool should_stop() {
|
||||
return g_is_interrupted.load();
|
||||
}
|
||||
|
||||
#if defined (__unix__) || (defined (__APPLE__) && defined (__MACH__)) || defined (_WIN32)
|
||||
static void signal_handler(int) {
|
||||
if (g_is_interrupted.load()) {
|
||||
if (cli_context::interrupted().load()) {
|
||||
// second Ctrl+C - exit immediately
|
||||
// make sure to clear colors before exiting (not using LOG or console.cpp here to avoid deadlock)
|
||||
fprintf(stdout, "\033[0m\n");
|
||||
fflush(stdout);
|
||||
std::exit(130);
|
||||
}
|
||||
g_is_interrupted.store(true);
|
||||
cli_context::interrupted().store(true);
|
||||
}
|
||||
#endif
|
||||
|
||||
struct cli_context {
|
||||
server_context ctx_server;
|
||||
json messages = json::array();
|
||||
std::vector<raw_buffer> input_files;
|
||||
task_params defaults;
|
||||
bool verbose_prompt;
|
||||
|
||||
// thread for showing "loading" animation
|
||||
std::atomic<bool> loading_show;
|
||||
|
||||
cli_context(const common_params & params) {
|
||||
defaults.sampling = params.sampling;
|
||||
defaults.speculative = params.speculative;
|
||||
defaults.n_keep = params.n_keep;
|
||||
defaults.n_predict = params.n_predict;
|
||||
defaults.antiprompt = params.antiprompt;
|
||||
|
||||
defaults.stream = true; // make sure we always use streaming mode
|
||||
defaults.timings_per_token = true; // in order to get timings even when we cancel mid-way
|
||||
// defaults.return_progress = true; // TODO: show progress
|
||||
|
||||
verbose_prompt = params.verbose_prompt;
|
||||
}
|
||||
|
||||
std::string generate_completion(result_timings & out_timings) {
|
||||
server_response_reader rd = ctx_server.get_response_reader();
|
||||
auto chat_params = format_chat();
|
||||
{
|
||||
// TODO: reduce some copies here in the future
|
||||
server_task task = server_task(SERVER_TASK_TYPE_COMPLETION);
|
||||
task.id = rd.get_new_id();
|
||||
task.index = 0;
|
||||
task.params = defaults; // copy
|
||||
task.cli_prompt = chat_params.prompt; // copy
|
||||
task.cli_files = input_files; // copy
|
||||
task.cli = true;
|
||||
|
||||
// chat template settings
|
||||
task.params.chat_parser_params = common_chat_parser_params(chat_params);
|
||||
task.params.chat_parser_params.reasoning_format = COMMON_REASONING_FORMAT_DEEPSEEK;
|
||||
if (!chat_params.parser.empty()) {
|
||||
task.params.chat_parser_params.parser.load(chat_params.parser);
|
||||
}
|
||||
|
||||
// Copy the preserved tokens into the sampling params
|
||||
const llama_vocab * vocab = llama_model_get_vocab(
|
||||
llama_get_model(ctx_server.get_llama_context()));
|
||||
for (const auto & token : chat_params.preserved_tokens) {
|
||||
auto ids = common_tokenize(vocab, token, false, true);
|
||||
if (ids.size() == 1) {
|
||||
task.params.sampling.preserved_tokens.insert(ids[0]);
|
||||
}
|
||||
}
|
||||
|
||||
// reasoning budget sampler
|
||||
if (!chat_params.thinking_end_tag.empty()) {
|
||||
task.params.sampling.reasoning_budget_tokens = defaults.sampling.reasoning_budget_tokens;
|
||||
task.params.sampling.generation_prompt = chat_params.generation_prompt;
|
||||
|
||||
if (!chat_params.thinking_start_tag.empty()) {
|
||||
task.params.sampling.reasoning_budget_start =
|
||||
common_tokenize(vocab, chat_params.thinking_start_tag, false, true);
|
||||
}
|
||||
task.params.sampling.reasoning_budget_end =
|
||||
common_tokenize(vocab, chat_params.thinking_end_tag, false, true);
|
||||
task.params.sampling.reasoning_budget_forced =
|
||||
common_tokenize(vocab, defaults.sampling.reasoning_budget_message + chat_params.thinking_end_tag, false, true);
|
||||
}
|
||||
|
||||
rd.post_task({std::move(task)});
|
||||
}
|
||||
|
||||
if (verbose_prompt) {
|
||||
console::set_display(DISPLAY_TYPE_PROMPT);
|
||||
console::log("%s\n\n", chat_params.prompt.c_str());
|
||||
console::set_display(DISPLAY_TYPE_RESET);
|
||||
}
|
||||
|
||||
// wait for first result
|
||||
console::spinner::start();
|
||||
server_task_result_ptr result = rd.next(should_stop);
|
||||
|
||||
while (true) {
|
||||
auto res_partial = dynamic_cast<server_task_result_cmpl_partial *>(result.get());
|
||||
if (res_partial && res_partial->is_begin) {
|
||||
// this is the "send 200 status to client" signal in streaming mode
|
||||
// skip, do not stop the spinner
|
||||
result = rd.next(should_stop);
|
||||
} else {
|
||||
console::spinner::stop();
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
std::string curr_content;
|
||||
bool is_thinking = false;
|
||||
|
||||
while (result) {
|
||||
if (should_stop()) {
|
||||
break;
|
||||
}
|
||||
if (result->is_error()) {
|
||||
json err_data = result->to_json();
|
||||
if (err_data.contains("message")) {
|
||||
console::error("Error: %s\n", err_data["message"].get<std::string>().c_str());
|
||||
} else {
|
||||
console::error("Error: %s\n", err_data.dump().c_str());
|
||||
}
|
||||
return curr_content;
|
||||
}
|
||||
auto res_partial = dynamic_cast<server_task_result_cmpl_partial *>(result.get());
|
||||
if (res_partial) {
|
||||
out_timings = std::move(res_partial->timings);
|
||||
for (const auto & diff : res_partial->oaicompat_msg_diffs) {
|
||||
if (!diff.content_delta.empty()) {
|
||||
if (is_thinking) {
|
||||
console::log("\n[End thinking]\n\n");
|
||||
console::set_display(DISPLAY_TYPE_RESET);
|
||||
is_thinking = false;
|
||||
}
|
||||
curr_content += diff.content_delta;
|
||||
console::log("%s", diff.content_delta.c_str());
|
||||
console::flush();
|
||||
}
|
||||
if (!diff.reasoning_content_delta.empty()) {
|
||||
console::set_display(DISPLAY_TYPE_REASONING);
|
||||
if (!is_thinking) {
|
||||
console::log("[Start thinking]\n");
|
||||
}
|
||||
is_thinking = true;
|
||||
console::log("%s", diff.reasoning_content_delta.c_str());
|
||||
console::flush();
|
||||
}
|
||||
}
|
||||
}
|
||||
auto res_final = dynamic_cast<server_task_result_cmpl_final *>(result.get());
|
||||
if (res_final) {
|
||||
out_timings = std::move(res_final->timings);
|
||||
break;
|
||||
}
|
||||
result = rd.next(should_stop);
|
||||
}
|
||||
g_is_interrupted.store(false);
|
||||
// server_response_reader automatically cancels pending tasks upon destruction
|
||||
return curr_content;
|
||||
}
|
||||
|
||||
// TODO: support remote files in the future (http, https, etc)
|
||||
std::string load_input_file(const std::string & fname, bool is_media) {
|
||||
std::ifstream file = fs_open_ifstream(fname, std::ios::binary);
|
||||
if (!file) {
|
||||
return "";
|
||||
}
|
||||
if (is_media) {
|
||||
raw_buffer buf;
|
||||
buf.assign((std::istreambuf_iterator<char>(file)), std::istreambuf_iterator<char>());
|
||||
input_files.push_back(std::move(buf));
|
||||
return get_media_marker();
|
||||
} else {
|
||||
std::string content((std::istreambuf_iterator<char>(file)), std::istreambuf_iterator<char>());
|
||||
return content;
|
||||
}
|
||||
}
|
||||
|
||||
common_chat_params format_chat() {
|
||||
auto meta = ctx_server.get_meta();
|
||||
auto & chat_params = meta.chat_params;
|
||||
|
||||
auto caps = common_chat_templates_get_caps(chat_params.tmpls.get());
|
||||
|
||||
common_chat_templates_inputs inputs;
|
||||
inputs.messages = common_chat_msgs_parse_oaicompat(messages);
|
||||
inputs.tools = {}; // TODO
|
||||
inputs.tool_choice = COMMON_CHAT_TOOL_CHOICE_NONE;
|
||||
inputs.json_schema = ""; // TODO
|
||||
inputs.grammar = ""; // TODO
|
||||
inputs.use_jinja = chat_params.use_jinja;
|
||||
inputs.parallel_tool_calls = caps["supports_parallel_tool_calls"];
|
||||
inputs.add_generation_prompt = true;
|
||||
inputs.reasoning_format = COMMON_REASONING_FORMAT_DEEPSEEK;
|
||||
inputs.force_pure_content = chat_params.force_pure_content;
|
||||
inputs.enable_thinking = chat_params.enable_thinking ? common_chat_templates_support_enable_thinking(chat_params.tmpls.get()) : false;
|
||||
|
||||
// Apply chat template to the list of messages
|
||||
return common_chat_templates_apply(chat_params.tmpls.get(), inputs);
|
||||
}
|
||||
};
|
||||
|
||||
// TODO?: Make this reusable, enums, docs
|
||||
static const std::array<std::string_view, 8> cmds = {
|
||||
"/audio ",
|
||||
"/clear",
|
||||
"/exit",
|
||||
"/glob ",
|
||||
"/image ",
|
||||
"/read ",
|
||||
"/regen",
|
||||
"/video ",
|
||||
};
|
||||
|
||||
static std::vector<std::pair<std::string, size_t>> auto_completion_callback(std::string_view line, size_t cursor_byte_pos) {
|
||||
std::vector<std::pair<std::string, size_t>> matches;
|
||||
std::string cmd;
|
||||
|
||||
if (line.length() > 1 && line.front() == '/' && !std::any_of(cmds.begin(), cmds.end(), [line](std::string_view prefix) {
|
||||
return string_starts_with(line, prefix);
|
||||
})) {
|
||||
auto it = cmds.begin();
|
||||
|
||||
while ((it = std::find_if(it, cmds.end(), [line](std::string_view cmd_line) {
|
||||
return string_starts_with(cmd_line, line);
|
||||
})) != cmds.end()) {
|
||||
matches.emplace_back(*it, it->length());
|
||||
++it;
|
||||
}
|
||||
} else {
|
||||
auto it = std::find_if(cmds.begin(), cmds.end(), [line](std::string_view prefix) {
|
||||
return prefix.back() == ' ' && string_starts_with(line, prefix);
|
||||
});
|
||||
|
||||
if (it != cmds.end()) {
|
||||
cmd = *it;
|
||||
}
|
||||
}
|
||||
|
||||
if (!cmd.empty() && cmd != "/glob " && line.length() >= cmd.length() && cursor_byte_pos >= cmd.length()) {
|
||||
const std::string path_prefix = std::string(line.substr(cmd.length(), cursor_byte_pos - cmd.length()));
|
||||
const std::string path_postfix = std::string(line.substr(cursor_byte_pos));
|
||||
auto cur_dir = std::filesystem::current_path();
|
||||
std::string cur_dir_str = cur_dir.string();
|
||||
std::string expanded_prefix = path_prefix;
|
||||
|
||||
#if !defined(_WIN32)
|
||||
if (string_starts_with(path_prefix, '~')) {
|
||||
const char * home = std::getenv("HOME");
|
||||
if (home && home[0]) {
|
||||
expanded_prefix = home + path_prefix.substr(1);
|
||||
}
|
||||
}
|
||||
if (string_starts_with(expanded_prefix, '/')) {
|
||||
#else
|
||||
if (std::isalpha(expanded_prefix[0]) && expanded_prefix.find(':') == 1) {
|
||||
#endif
|
||||
cur_dir = std::filesystem::path(expanded_prefix).parent_path();
|
||||
cur_dir_str.clear();
|
||||
} else if (!path_prefix.empty()) {
|
||||
cur_dir /= std::filesystem::path(path_prefix).parent_path();
|
||||
}
|
||||
|
||||
std::error_code ec;
|
||||
for (const auto & entry : std::filesystem::directory_iterator(cur_dir, ec)) {
|
||||
if (ec) {
|
||||
break;
|
||||
}
|
||||
if (!entry.exists(ec)) {
|
||||
ec.clear();
|
||||
continue;
|
||||
}
|
||||
|
||||
const std::string path_full = entry.path().string();
|
||||
std::string path_entry = !cur_dir_str.empty() && string_starts_with(path_full, cur_dir_str) ? path_full.substr(cur_dir_str.length() + 1) : path_full;
|
||||
|
||||
if (entry.is_directory(ec)) {
|
||||
path_entry.push_back(std::filesystem::path::preferred_separator);
|
||||
}
|
||||
|
||||
if (expanded_prefix.empty() || string_starts_with(path_entry, expanded_prefix)) {
|
||||
const std::string updated_line = cmd + path_entry;
|
||||
matches.emplace_back(updated_line + path_postfix, updated_line.length());
|
||||
}
|
||||
|
||||
if (ec) {
|
||||
ec.clear();
|
||||
}
|
||||
}
|
||||
|
||||
if (matches.empty()) {
|
||||
const std::string updated_line = cmd + path_prefix;
|
||||
matches.emplace_back(updated_line + path_postfix, updated_line.length());
|
||||
}
|
||||
|
||||
// Add the longest common prefix
|
||||
if (!expanded_prefix.empty() && matches.size() > 1) {
|
||||
const std::string_view match0(matches[0].first);
|
||||
const std::string_view match1(matches[1].first);
|
||||
auto it = std::mismatch(match0.begin(), match0.end(), match1.begin(), match1.end());
|
||||
size_t len = it.first - match0.begin();
|
||||
|
||||
for (size_t i = 2; i < matches.size(); ++i) {
|
||||
const std::string_view matchi(matches[i].first);
|
||||
auto cmp = std::mismatch(match0.begin(), match0.end(), matchi.begin(), matchi.end());
|
||||
len = std::min(len, static_cast<size_t>(cmp.first - match0.begin()));
|
||||
}
|
||||
|
||||
const std::string updated_line = std::string(match0.substr(0, len));
|
||||
matches.emplace_back(updated_line + path_postfix, updated_line.length());
|
||||
}
|
||||
|
||||
std::sort(matches.begin(), matches.end(), [](const auto & a, const auto & b) {
|
||||
return a.first.compare(0, a.second, b.first, 0, b.second) < 0;
|
||||
});
|
||||
}
|
||||
|
||||
return matches;
|
||||
}
|
||||
|
||||
static constexpr size_t FILE_GLOB_MAX_RESULTS = 100;
|
||||
|
||||
// satisfies -Wmissing-declarations
|
||||
int llama_cli(int argc, char ** argv);
|
||||
|
||||
@@ -375,25 +41,6 @@ int llama_cli(int argc, char ** argv) {
|
||||
return 1;
|
||||
}
|
||||
|
||||
// TODO: maybe support it later?
|
||||
if (params.conversation_mode == COMMON_CONVERSATION_MODE_DISABLED) {
|
||||
console::error("--no-conversation is not supported by llama-cli\n");
|
||||
console::error("please use llama-completion instead\n");
|
||||
}
|
||||
|
||||
// struct that contains llama context and inference
|
||||
cli_context ctx_cli(params);
|
||||
|
||||
llama_backend_init();
|
||||
llama_numa_init(params.numa);
|
||||
|
||||
// TODO: avoid using atexit() here by making `console` a singleton
|
||||
console::init(params.simple_io, params.use_color);
|
||||
atexit([]() { console::cleanup(); });
|
||||
|
||||
console::set_display(DISPLAY_TYPE_RESET);
|
||||
console::set_completion_callback(auto_completion_callback);
|
||||
|
||||
#if defined (__unix__) || (defined (__APPLE__) && defined (__MACH__))
|
||||
struct sigaction sigint_action;
|
||||
sigint_action.sa_handler = signal_handler;
|
||||
@@ -408,276 +55,11 @@ int llama_cli(int argc, char ** argv) {
|
||||
SetConsoleCtrlHandler(reinterpret_cast<PHANDLER_ROUTINE>(console_ctrl_handler), true);
|
||||
#endif
|
||||
|
||||
console::log("\nLoading model... "); // followed by loading animation
|
||||
console::spinner::start();
|
||||
if (!ctx_cli.ctx_server.load_model(params)) {
|
||||
console::spinner::stop();
|
||||
console::error("\nFailed to load the model\n");
|
||||
cli_context ctx_cli(params);
|
||||
|
||||
if (!ctx_cli.init()) {
|
||||
return 1;
|
||||
}
|
||||
|
||||
ctx_cli.defaults.sampling = params.sampling;
|
||||
|
||||
console::spinner::stop();
|
||||
console::log("\n");
|
||||
|
||||
std::thread inference_thread([&ctx_cli]() {
|
||||
ctx_cli.ctx_server.start_loop();
|
||||
});
|
||||
|
||||
auto inf = ctx_cli.ctx_server.get_meta();
|
||||
std::string modalities = "text";
|
||||
if (inf.has_inp_image) {
|
||||
modalities += ", vision";
|
||||
}
|
||||
if (inf.has_inp_audio) {
|
||||
modalities += ", audio";
|
||||
}
|
||||
|
||||
auto add_system_prompt = [&]() {
|
||||
if (!params.system_prompt.empty()) {
|
||||
ctx_cli.messages.push_back({
|
||||
{"role", "system"},
|
||||
{"content", params.system_prompt}
|
||||
});
|
||||
}
|
||||
};
|
||||
add_system_prompt();
|
||||
|
||||
console::log("\n");
|
||||
console::log("%s\n", LLAMA_ASCII_LOGO);
|
||||
console::log("build : %s\n", inf.build_info.c_str());
|
||||
console::log("model : %s\n", inf.model_name.c_str());
|
||||
if (!inf.model_ftype.empty()) {
|
||||
console::log("ftype : %s\n", inf.model_ftype.c_str());
|
||||
}
|
||||
console::log("modalities : %s\n", modalities.c_str());
|
||||
if (!params.system_prompt.empty()) {
|
||||
console::log("using custom system prompt\n");
|
||||
}
|
||||
console::log("\n");
|
||||
console::log("available commands:\n");
|
||||
console::log(" /exit or Ctrl+C stop or exit\n");
|
||||
console::log(" /regen regenerate the last response\n");
|
||||
console::log(" /clear clear the chat history\n");
|
||||
console::log(" /read <file> add a text file\n");
|
||||
console::log(" /glob <pattern> add text files using globbing pattern\n");
|
||||
if (inf.has_inp_image) {
|
||||
console::log(" /image <file> add an image file\n");
|
||||
}
|
||||
if (inf.has_inp_audio) {
|
||||
console::log(" /audio <file> add an audio file\n");
|
||||
}
|
||||
if (inf.has_inp_video) {
|
||||
console::log(" /video <file> add a video file\n");
|
||||
}
|
||||
console::log("\n");
|
||||
|
||||
// interactive loop
|
||||
std::string cur_msg;
|
||||
|
||||
auto add_text_file = [&](const std::string & fname) -> bool {
|
||||
std::string marker = ctx_cli.load_input_file(fname, false);
|
||||
if (marker.empty()) {
|
||||
console::error("file does not exist or cannot be opened: '%s'\n", fname.c_str());
|
||||
return false;
|
||||
}
|
||||
if (inf.fim_sep_token != LLAMA_TOKEN_NULL) {
|
||||
cur_msg += common_token_to_piece(ctx_cli.ctx_server.get_llama_context(), inf.fim_sep_token, true);
|
||||
cur_msg += fname;
|
||||
cur_msg.push_back('\n');
|
||||
} else {
|
||||
cur_msg += "--- File: ";
|
||||
cur_msg += fname;
|
||||
cur_msg += " ---\n";
|
||||
}
|
||||
cur_msg += marker;
|
||||
console::log("Loaded text from '%s'\n", fname.c_str());
|
||||
return true;
|
||||
};
|
||||
|
||||
while (true) {
|
||||
std::string buffer;
|
||||
console::set_display(DISPLAY_TYPE_USER_INPUT);
|
||||
if (params.prompt.empty()) {
|
||||
console::log("\n> ");
|
||||
std::string line;
|
||||
bool another_line = true;
|
||||
do {
|
||||
another_line = console::readline(line, params.multiline_input);
|
||||
buffer += line;
|
||||
} while (another_line);
|
||||
} else {
|
||||
// process input prompt from args
|
||||
for (auto & fname : params.image) {
|
||||
std::string marker = ctx_cli.load_input_file(fname, true);
|
||||
if (marker.empty()) {
|
||||
console::error("file does not exist or cannot be opened: '%s'\n", fname.c_str());
|
||||
break;
|
||||
}
|
||||
console::log("Loaded media from '%s'\n", fname.c_str());
|
||||
cur_msg += marker;
|
||||
}
|
||||
buffer = params.prompt;
|
||||
if (buffer.size() > 500) {
|
||||
console::log("\n> %s ... (truncated)\n", buffer.substr(0, 500).c_str());
|
||||
} else {
|
||||
console::log("\n> %s\n", buffer.c_str());
|
||||
}
|
||||
params.prompt.clear(); // only use it once
|
||||
}
|
||||
console::set_display(DISPLAY_TYPE_RESET);
|
||||
console::log("\n");
|
||||
|
||||
if (should_stop()) {
|
||||
g_is_interrupted.store(false);
|
||||
break;
|
||||
}
|
||||
|
||||
// remove trailing newline
|
||||
if (!buffer.empty() &&buffer.back() == '\n') {
|
||||
buffer.pop_back();
|
||||
}
|
||||
|
||||
// skip empty messages
|
||||
if (buffer.empty()) {
|
||||
continue;
|
||||
}
|
||||
|
||||
bool add_user_msg = true;
|
||||
|
||||
// process commands
|
||||
if (string_starts_with(buffer, "/exit")) {
|
||||
break;
|
||||
} else if (string_starts_with(buffer, "/regen")) {
|
||||
if (ctx_cli.messages.size() >= 2) {
|
||||
size_t last_idx = ctx_cli.messages.size() - 1;
|
||||
ctx_cli.messages.erase(last_idx);
|
||||
add_user_msg = false;
|
||||
} else {
|
||||
console::error("No message to regenerate.\n");
|
||||
continue;
|
||||
}
|
||||
} else if (string_starts_with(buffer, "/clear")) {
|
||||
ctx_cli.messages.clear();
|
||||
add_system_prompt();
|
||||
|
||||
ctx_cli.input_files.clear();
|
||||
console::log("Chat history cleared.\n");
|
||||
continue;
|
||||
} else if (
|
||||
(string_starts_with(buffer, "/image ") && inf.has_inp_image) ||
|
||||
(string_starts_with(buffer, "/audio ") && inf.has_inp_audio) ||
|
||||
(string_starts_with(buffer, "/video ") && inf.has_inp_video)) {
|
||||
// just in case (bad copy-paste for example), we strip all trailing/leading spaces
|
||||
std::string fname = string_strip(buffer.substr(7));
|
||||
std::string marker = ctx_cli.load_input_file(fname, true);
|
||||
if (marker.empty()) {
|
||||
console::error("file does not exist or cannot be opened: '%s'\n", fname.c_str());
|
||||
continue;
|
||||
}
|
||||
cur_msg += marker;
|
||||
console::log("Loaded media from '%s'\n", fname.c_str());
|
||||
continue;
|
||||
} else if (string_starts_with(buffer, "/read ")) {
|
||||
std::string fname = string_strip(buffer.substr(6));
|
||||
add_text_file(fname);
|
||||
continue;
|
||||
} else if (string_starts_with(buffer, "/glob ")) {
|
||||
std::error_code ec;
|
||||
size_t count = 0;
|
||||
auto curdir = std::filesystem::current_path();
|
||||
std::string pattern = string_strip(buffer.substr(6));
|
||||
std::filesystem::path rel_path;
|
||||
|
||||
auto startglob = pattern.find_first_of("![*?");
|
||||
if (startglob != std::string::npos && startglob != 0) {
|
||||
auto endpath = pattern.substr(0, startglob).find_last_of('/');
|
||||
if (endpath != std::string::npos) {
|
||||
std::string rel_pattern = pattern.substr(0, endpath);
|
||||
#if !defined(_WIN32)
|
||||
if (string_starts_with(rel_pattern, '~')) {
|
||||
const char * home = std::getenv("HOME");
|
||||
if (home && home[0]) {
|
||||
rel_pattern = home + rel_pattern.substr(1);
|
||||
}
|
||||
}
|
||||
#endif
|
||||
rel_path = rel_pattern;
|
||||
pattern.erase(0, endpath + 1);
|
||||
curdir /= rel_path;
|
||||
}
|
||||
}
|
||||
|
||||
for (const auto & entry : std::filesystem::recursive_directory_iterator(curdir,
|
||||
std::filesystem::directory_options::skip_permission_denied, ec)) {
|
||||
if (!entry.is_regular_file()) {
|
||||
continue;
|
||||
}
|
||||
|
||||
std::string rel = std::filesystem::relative(entry.path(), curdir, ec).string();
|
||||
if (ec) {
|
||||
ec.clear();
|
||||
continue;
|
||||
}
|
||||
std::replace(rel.begin(), rel.end(), '\\', '/');
|
||||
|
||||
if (!glob_match(pattern, rel)) {
|
||||
continue;
|
||||
}
|
||||
|
||||
if (!add_text_file((rel_path / rel).string())) {
|
||||
continue;
|
||||
}
|
||||
|
||||
if (++count >= FILE_GLOB_MAX_RESULTS) {
|
||||
console::error("Maximum number of globbed files allowed (%zu) reached.\n", FILE_GLOB_MAX_RESULTS);
|
||||
break;
|
||||
}
|
||||
}
|
||||
continue;
|
||||
} else {
|
||||
// not a command
|
||||
cur_msg += buffer;
|
||||
}
|
||||
|
||||
// generate response
|
||||
if (add_user_msg) {
|
||||
ctx_cli.messages.push_back({
|
||||
{"role", "user"},
|
||||
{"content", cur_msg}
|
||||
});
|
||||
cur_msg.clear();
|
||||
}
|
||||
result_timings timings;
|
||||
std::string assistant_content = ctx_cli.generate_completion(timings);
|
||||
ctx_cli.messages.push_back({
|
||||
{"role", "assistant"},
|
||||
{"content", assistant_content}
|
||||
});
|
||||
console::log("\n");
|
||||
|
||||
if (params.show_timings) {
|
||||
console::set_display(DISPLAY_TYPE_INFO);
|
||||
console::log("\n");
|
||||
console::log("[ Prompt: %.1f t/s | Generation: %.1f t/s ]\n", timings.prompt_per_second, timings.predicted_per_second);
|
||||
console::set_display(DISPLAY_TYPE_RESET);
|
||||
}
|
||||
|
||||
if (params.single_turn) {
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
console::set_display(DISPLAY_TYPE_RESET);
|
||||
|
||||
console::log("\nExiting...\n");
|
||||
ctx_cli.ctx_server.terminate();
|
||||
inference_thread.join();
|
||||
|
||||
// bump the log level to display timings
|
||||
common_log_set_verbosity_thold(LOG_LEVEL_INFO);
|
||||
common_memory_breakdown_print(ctx_cli.ctx_server.get_llama_context());
|
||||
|
||||
return 0;
|
||||
return ctx_cli.run();
|
||||
}
|
||||
|
||||
@@ -57,7 +57,7 @@ The core architecture consists of the following components:
|
||||
- `server_tokens`: Unified representation of token sequences (supports both text and multimodal tokens); used by `server_task` and `server_slot`.
|
||||
- `server_prompt_checkpoint`: For recurrent (e.g., RWKV) and SWA models, stores snapshots of KV cache state. Enables reuse when subsequent requests share the same prompt prefix, saving redundant computation.
|
||||
- `server_models`: Standalone component for managing multiple backend instances (used in router mode). It is completely independent of `server_context`.
|
||||
- `stream_session_manager`: Process wide owner of resumable SSE stream sessions (`g_stream_sessions`), keyed by conversation id. Backs the replay buffer that lets a client reattach to a generation after an HTTP disconnect. See the "Resumable streaming" section below.
|
||||
- `stream_session_manager`: process wide owner of resumable SSE stream sessions, keyed by conversation id. A file-static singleton inside `server-stream.cpp`, driven through `server_stream_session_manager_start/stop`. Backs the replay buffer that lets a client reattach to a generation after an HTTP disconnect. See the "Resumable streaming" section below.
|
||||
|
||||
```mermaid
|
||||
graph TD
|
||||
@@ -127,10 +127,12 @@ It is opt in via the `X-Conversation-Id` header on `POST /v1/chat/completions`.
|
||||
The feature lives entirely in `server-stream.{h,cpp}` and rests on three types:
|
||||
|
||||
- `stream_session`: a bounded ring buffer (4 MiB cap, oldest bytes drop first) plus a condvar. `append` pushes raw SSE bytes, `read_from` drains from any offset and blocks for live bytes or finalize, `finalize` wakes readers, `cancel` stops the producer. One conv maps to at most one live session.
|
||||
- `stream_session_manager` (`g_stream_sessions`): owns all sessions keyed by conv id, enforces the one conv one session invariant via `create_or_replace`, and runs a GC thread that drops completed sessions past their TTL.
|
||||
- `stream_session_manager`: a file-static singleton (`g_stream_sessions`) inside `server-stream.cpp`, owns all sessions keyed by conv id, enforces the one conv one session invariant via `create_or_replace`, and runs a GC thread that drops completed sessions past their TTL. Exposed to main only through `server_stream_session_manager_start/stop`.
|
||||
- `stream_pipe_producer` / `stream_pipe_consumer`: the write and read ends. The producer owns the session lifetime and finalizes it on destruction; the consumer is read only and never finalizes, so a reader detaching cannot kill a running generation.
|
||||
|
||||
Producer side: `server_res_generator` attaches a producer pipe when the header is present. The HTTP content provider mirrors every chunk into the ring before writing it to the socket. While a pipe is attached, `stream_aware_should_stop` ignores peer disconnect, so a dropped socket does not stop generation: only an explicit `DELETE` does. When the peer leaves early, `on_complete` calls `close()`, which drains the rest of the generation into the ring on the http worker.
|
||||
The implementation is hidden in `server-stream.cpp` (pimpl). The header exposes only the route handler factories, `server_stream_session_attach_pipe`, `server_stream_aware_should_stop`, `server_stream_conv_id_from_headers` and the GC lifecycle; the session, manager and consumer types stay in the `.cpp`.
|
||||
|
||||
Producer side: `server_res_generator` attaches a producer pipe when the header is present. The HTTP content provider mirrors every chunk into the ring before writing it to the socket. While a pipe is attached, `server_stream_aware_should_stop` ignores peer disconnect, so a dropped socket does not stop generation: only an explicit `DELETE` does. When the peer leaves early, `on_complete` calls `close()`, which drains the rest of the generation into the ring on the http worker.
|
||||
|
||||
Lifetime safety: the producer pipe holds a shared `alive` flag also captured by the session cancel hook. `~server_res_generator` calls `cleanup()` to clear that hook while the reader is still alive, so a `cancel` arriving during teardown can never call `stop()` on a freed response. This ordering is the most fragile part of the feature: finalizing or destroying the producer before `cleanup()` runs reintroduces a use after free.
|
||||
|
||||
@@ -144,7 +146,7 @@ Routes:
|
||||
|
||||
Router mode binds the same paths to proxy handlers. A `conv_id -> child` map (`conv_models`), populated when a POST is routed, resolves the owning child in one lookup with no polling. The lookup groups ids per child; GET and DELETE proxy straight to the owner. This loopback REST hop is expected to move to a websocket IPC later, swapping only the transport.
|
||||
|
||||
Lifecycle: `g_stream_sessions.start_gc()` runs in main after common init, `stop_gc()` runs first in `clean_up()` and finalizes every live session so no reader hangs. Reader blocking and the post drop drain both run on httplib worker threads, which block on a condvar rather than spin.
|
||||
Lifecycle: `server_stream_session_manager_start()` runs in main after common init, `server_stream_session_manager_stop()` runs first in `clean_up()` and finalizes every live session so no reader hangs. Reader blocking and the post drop drain both run on httplib worker threads, which block on a condvar rather than spin.
|
||||
|
||||
| Constant | Value | Role |
|
||||
| --- | --- | --- |
|
||||
|
||||
@@ -228,7 +228,7 @@ For the full list of features, please refer to [server's changelog](https://gith
|
||||
| `-sps, --slot-prompt-similarity SIMILARITY` | how much the prompt of a request must match the prompt of a slot in order to use that slot (default: 0.10, 0.0 = disabled) |
|
||||
| `--lora-init-without-apply` | load LoRA adapters without applying them (apply later via POST /lora-adapters) (default: disabled) |
|
||||
| `--sleep-idle-seconds SECONDS` | number of seconds of idleness after which the server will sleep (default: -1; -1 = disabled) |
|
||||
| `--log-prompts-dir PATH` | Log prompts to directory (only used for debugging, default: disabled) |
|
||||
| `--log-prompts-dir PATH` | Log prompts to directory (auto-created if not present; only used for debugging, default: disabled) |
|
||||
| `--spec-draft-hf, -hfd, -hfrd, --hf-repo-draft <user>/<model>[:quant]` | Same as --hf-repo, but for the draft model (default: unused)<br/>(env: LLAMA_ARG_SPEC_DRAFT_HF_REPO) |
|
||||
| `--spec-draft-threads, -td, --threads-draft N` | number of threads to use during generation (default: same as --threads) |
|
||||
| `--spec-draft-threads-batch, -tbd, --threads-batch-draft N` | number of threads to use during batch and prompt processing (default: same as --threads-draft) |
|
||||
|
||||
@@ -4188,7 +4188,7 @@ std::unique_ptr<server_res_generator> server_routes::handle_completions_impl(
|
||||
}
|
||||
};
|
||||
|
||||
auto effective_should_stop = stream_aware_should_stop(res_this, req.should_stop);
|
||||
auto effective_should_stop = server_stream_aware_should_stop(res_this, req.should_stop);
|
||||
|
||||
try {
|
||||
if (effective_should_stop()) {
|
||||
@@ -4284,7 +4284,7 @@ std::unique_ptr<server_res_generator> server_routes::handle_completions_impl(
|
||||
|
||||
// attach a producer pipe to the response when X-Conversation-Id is present.
|
||||
// the pipe mirrors SSE chunks into the ring buffer and wires up the cancel hook.
|
||||
stream_session_attach_pipe(*res, req.headers);
|
||||
server_stream_session_attach_pipe(*res, req.headers);
|
||||
|
||||
return res;
|
||||
}
|
||||
@@ -4521,6 +4521,7 @@ void server_routes::init_routes() {
|
||||
{ "default_generation_settings", default_generation_settings_for_props },
|
||||
{ "total_slots", params.n_parallel },
|
||||
{ "model_alias", meta->model_name },
|
||||
{ "model_ftype", meta->model_ftype },
|
||||
{ "model_path", meta->model_path },
|
||||
{ "modalities", json {
|
||||
{"vision", meta->has_inp_image},
|
||||
|
||||
@@ -7,6 +7,7 @@
|
||||
#include "build-info.h"
|
||||
#include "preset.h"
|
||||
#include "download.h"
|
||||
#include "http.h"
|
||||
|
||||
#include <cpp-httplib/httplib.h> // TODO: remove this once we use HTTP client from download.h
|
||||
#include <optional>
|
||||
@@ -28,14 +29,7 @@
|
||||
#include <sstream>
|
||||
#include <cstring>
|
||||
|
||||
#ifdef _WIN32
|
||||
#include <winsock2.h>
|
||||
#include <windows.h>
|
||||
#else
|
||||
#include <sys/socket.h>
|
||||
#include <netinet/in.h>
|
||||
#include <arpa/inet.h>
|
||||
#include <unistd.h>
|
||||
#ifndef _WIN32
|
||||
extern char **environ;
|
||||
#endif
|
||||
|
||||
@@ -716,66 +710,6 @@ std::optional<server_model_meta> server_models::get_meta(const std::string & nam
|
||||
return std::nullopt;
|
||||
}
|
||||
|
||||
static int get_free_port() {
|
||||
#ifdef _WIN32
|
||||
WSADATA wsaData;
|
||||
if (WSAStartup(MAKEWORD(2, 2), &wsaData) != 0) {
|
||||
return -1;
|
||||
}
|
||||
typedef SOCKET native_socket_t;
|
||||
#define INVALID_SOCKET_VAL INVALID_SOCKET
|
||||
#define CLOSE_SOCKET(s) closesocket(s)
|
||||
#else
|
||||
typedef int native_socket_t;
|
||||
#define INVALID_SOCKET_VAL -1
|
||||
#define CLOSE_SOCKET(s) close(s)
|
||||
#endif
|
||||
|
||||
native_socket_t sock = socket(AF_INET, SOCK_STREAM, 0);
|
||||
if (sock == INVALID_SOCKET_VAL) {
|
||||
#ifdef _WIN32
|
||||
WSACleanup();
|
||||
#endif
|
||||
return -1;
|
||||
}
|
||||
|
||||
struct sockaddr_in serv_addr;
|
||||
std::memset(&serv_addr, 0, sizeof(serv_addr));
|
||||
serv_addr.sin_family = AF_INET;
|
||||
serv_addr.sin_addr.s_addr = htonl(INADDR_ANY);
|
||||
serv_addr.sin_port = htons(0);
|
||||
|
||||
if (bind(sock, (struct sockaddr*)&serv_addr, sizeof(serv_addr)) != 0) {
|
||||
CLOSE_SOCKET(sock);
|
||||
#ifdef _WIN32
|
||||
WSACleanup();
|
||||
#endif
|
||||
return -1;
|
||||
}
|
||||
|
||||
#ifdef _WIN32
|
||||
int namelen = sizeof(serv_addr);
|
||||
#else
|
||||
socklen_t namelen = sizeof(serv_addr);
|
||||
#endif
|
||||
if (getsockname(sock, (struct sockaddr*)&serv_addr, &namelen) != 0) {
|
||||
CLOSE_SOCKET(sock);
|
||||
#ifdef _WIN32
|
||||
WSACleanup();
|
||||
#endif
|
||||
return -1;
|
||||
}
|
||||
|
||||
int port = ntohs(serv_addr.sin_port);
|
||||
|
||||
CLOSE_SOCKET(sock);
|
||||
#ifdef _WIN32
|
||||
WSACleanup();
|
||||
#endif
|
||||
|
||||
return port;
|
||||
}
|
||||
|
||||
// helper to convert vector<string> to char **
|
||||
// pointers are only valid as long as the original vector is valid
|
||||
static std::vector<char *> to_char_ptr_array(const std::vector<std::string> & vec) {
|
||||
@@ -879,7 +813,7 @@ void server_models::load(const std::string & name, const load_options & opts) {
|
||||
// prepare new instance info
|
||||
instance_t inst;
|
||||
inst.meta = meta;
|
||||
inst.meta.port = get_free_port();
|
||||
inst.meta.port = common_http_get_free_port();
|
||||
inst.meta.status = SERVER_MODEL_STATUS_LOADING;
|
||||
inst.meta.loaded_info = json{};
|
||||
inst.meta.last_used = ggml_time_ms();
|
||||
@@ -1681,7 +1615,7 @@ void server_models_routes::init_routes() {
|
||||
}
|
||||
// remember which child serves this conversation so the stream routes can route straight
|
||||
// to it without polling, keyed on the exact conv id from the header
|
||||
std::string conv_id = stream_conv_id_from_headers(req.headers);
|
||||
std::string conv_id = server_stream_conv_id_from_headers(req.headers);
|
||||
if (!conv_id.empty()) {
|
||||
models.conv_models.remember(conv_id, name);
|
||||
}
|
||||
@@ -1896,7 +1830,7 @@ void server_models_routes::init_routes() {
|
||||
if (!from.empty()) {
|
||||
child_path += "?from=" + from;
|
||||
}
|
||||
SRV_INF("proxying stream resume to model %s on port %d, path=%s\n",
|
||||
SRV_TRC("proxying stream resume to model %s on port %d, path=%s\n",
|
||||
owner->name.c_str(), owner->port, child_path.c_str());
|
||||
auto proxy = std::make_unique<server_http_proxy>(
|
||||
"GET",
|
||||
|
||||
+147
-41
@@ -6,6 +6,12 @@
|
||||
#include <chrono>
|
||||
#include <memory>
|
||||
#include <utility>
|
||||
#include <shared_mutex>
|
||||
|
||||
enum class stream_read_status {
|
||||
OK,
|
||||
OFFSET_LOST,
|
||||
};
|
||||
|
||||
namespace {
|
||||
constexpr int64_t STREAM_SESSION_TTL_SECONDS = 300;
|
||||
@@ -13,7 +19,6 @@ constexpr size_t STREAM_SESSION_MAX_BYTES = 4 * 1024 * 1024;
|
||||
constexpr int64_t STREAM_SESSION_GC_INTERVAL_SECONDS = 60;
|
||||
constexpr int64_t STREAM_READ_WAKE_INTERVAL_MS = 200;
|
||||
|
||||
// returns unix time in seconds
|
||||
int64_t now_seconds() {
|
||||
return std::chrono::duration_cast<std::chrono::seconds>(
|
||||
std::chrono::system_clock::now().time_since_epoch()
|
||||
@@ -21,6 +26,91 @@ int64_t now_seconds() {
|
||||
}
|
||||
}
|
||||
|
||||
// owns all live sessions keyed by conversation_id, one conv = at most one live session.
|
||||
// a periodic GC evicts expired ones
|
||||
class stream_session_manager {
|
||||
public:
|
||||
stream_session_manager();
|
||||
~stream_session_manager();
|
||||
|
||||
stream_session_manager(const stream_session_manager &) = delete;
|
||||
stream_session_manager & operator=(const stream_session_manager &) = delete;
|
||||
|
||||
// install a new session, evicting and cancelling any previous one. conversation_id must be non empty
|
||||
stream_session_ptr create_or_replace(const std::string & conversation_id);
|
||||
|
||||
stream_session_ptr get(const std::string & conversation_id);
|
||||
|
||||
std::vector<stream_session_ptr> list_all() const;
|
||||
|
||||
void evict(const std::string & conversation_id);
|
||||
|
||||
void evict_and_cancel(const std::string & conversation_id);
|
||||
|
||||
void start_gc();
|
||||
void stop_gc();
|
||||
|
||||
private:
|
||||
void gc_loop();
|
||||
|
||||
mutable std::shared_mutex map_mu;
|
||||
std::unordered_map<std::string, stream_session_ptr> sessions; // key: conversation_id
|
||||
std::thread gc_thread;
|
||||
bool running;
|
||||
std::mutex gc_wake_mu;
|
||||
std::condition_variable gc_wake_cv;
|
||||
};
|
||||
|
||||
// process wide manager, lifecycle controlled by llama-server main() via start_gc/stop_gc
|
||||
static stream_session_manager g_stream_sessions;
|
||||
|
||||
void server_stream_session_manager_start() {
|
||||
g_stream_sessions.start_gc();
|
||||
}
|
||||
|
||||
void server_stream_session_manager_stop() {
|
||||
g_stream_sessions.stop_gc();
|
||||
}
|
||||
|
||||
struct stream_session {
|
||||
std::string conversation_id;
|
||||
int64_t started_ts; // unix seconds at construction
|
||||
|
||||
stream_session(std::string conversation_id_, size_t max_bytes_);
|
||||
stream_session(const stream_session &) = delete;
|
||||
stream_session & operator=(const stream_session &) = delete;
|
||||
|
||||
bool append(const char * data, size_t len);
|
||||
|
||||
void finalize();
|
||||
|
||||
// drain from offset into sink, blocking for more bytes or finalize. OFFSET_LOST if offset
|
||||
// fell below the dropped prefix
|
||||
stream_read_status read_from(size_t offset,
|
||||
const std::function<bool(const char *, size_t)> & sink,
|
||||
const std::function<bool()> & should_stop);
|
||||
|
||||
bool is_done() const;
|
||||
bool is_cancelled() const;
|
||||
size_t total_size() const; // bytes that ever entered the session
|
||||
size_t dropped_prefix() const; // bytes evicted from the front due to cap
|
||||
int64_t completed_at() const; // 0 while alive, unix seconds after finalize
|
||||
|
||||
void set_stop_producer(std::function<void()> fn);
|
||||
|
||||
void cancel();
|
||||
|
||||
private:
|
||||
mutable std::mutex mu;
|
||||
std::condition_variable cv;
|
||||
std::vector<char> buffer;
|
||||
size_t prefix_dropped;
|
||||
size_t cap_bytes;
|
||||
bool done;
|
||||
std::atomic<bool> cancelled; // polled lock-free by the should_stop closure, no mu
|
||||
int64_t completed_ts;
|
||||
std::function<void()> stop_producer;
|
||||
};
|
||||
stream_session::stream_session(std::string conversation_id_, size_t max_bytes_)
|
||||
: conversation_id(std::move(conversation_id_))
|
||||
, started_ts(now_seconds())
|
||||
@@ -38,7 +128,7 @@ bool stream_session::append(const char * data, size_t len) {
|
||||
}
|
||||
{
|
||||
std::lock_guard<std::mutex> lock(mu);
|
||||
if (done.load(std::memory_order_relaxed)) {
|
||||
if (done) {
|
||||
return false;
|
||||
}
|
||||
if (len >= cap_bytes) {
|
||||
@@ -62,11 +152,14 @@ bool stream_session::append(const char * data, size_t len) {
|
||||
}
|
||||
|
||||
void stream_session::finalize() {
|
||||
bool was_done = done.exchange(true, std::memory_order_acq_rel);
|
||||
if (was_done) {
|
||||
return;
|
||||
{
|
||||
std::lock_guard<std::mutex> lock(mu);
|
||||
if (done) {
|
||||
return;
|
||||
}
|
||||
done = true;
|
||||
completed_ts = now_seconds();
|
||||
}
|
||||
completed_ts.store(now_seconds(), std::memory_order_release);
|
||||
cv.notify_all();
|
||||
}
|
||||
|
||||
@@ -96,7 +189,7 @@ stream_read_status stream_session::read_from(size_t offset,
|
||||
lock.lock();
|
||||
continue;
|
||||
}
|
||||
if (done.load(std::memory_order_acquire)) {
|
||||
if (done) {
|
||||
return stream_read_status::OK;
|
||||
}
|
||||
// wait for new bytes, finalize, or a periodic wake to re check should_stop
|
||||
@@ -105,7 +198,8 @@ stream_read_status stream_session::read_from(size_t offset,
|
||||
}
|
||||
|
||||
bool stream_session::is_done() const {
|
||||
return done.load(std::memory_order_acquire);
|
||||
std::lock_guard<std::mutex> lock(mu);
|
||||
return done;
|
||||
}
|
||||
|
||||
size_t stream_session::total_size() const {
|
||||
@@ -119,7 +213,8 @@ size_t stream_session::dropped_prefix() const {
|
||||
}
|
||||
|
||||
int64_t stream_session::completed_at() const {
|
||||
return completed_ts.load(std::memory_order_acquire);
|
||||
std::lock_guard<std::mutex> lock(mu);
|
||||
return completed_ts;
|
||||
}
|
||||
|
||||
void stream_session::set_stop_producer(std::function<void()> fn) {
|
||||
@@ -128,7 +223,7 @@ void stream_session::set_stop_producer(std::function<void()> fn) {
|
||||
}
|
||||
|
||||
void stream_session::cancel() {
|
||||
// flip cancelled first so the producer-side stream_aware_should_stop can break out of the
|
||||
// flip cancelled first so the producer-side server_stream_aware_should_stop can break out of the
|
||||
// recv() wait even if remove_waiting_task_ids does not notify the condvar (the cancel task
|
||||
// posted by rd.stop() will eventually notify, but we do not want to depend on that timing)
|
||||
cancelled.store(true, std::memory_order_release);
|
||||
@@ -237,18 +332,24 @@ void stream_session_manager::evict_and_cancel(const std::string & conversation_i
|
||||
}
|
||||
|
||||
void stream_session_manager::start_gc() {
|
||||
if (running.exchange(true)) {
|
||||
return;
|
||||
{
|
||||
std::lock_guard<std::mutex> lock(gc_wake_mu);
|
||||
if (running) {
|
||||
return;
|
||||
}
|
||||
running = true;
|
||||
}
|
||||
gc_thread = std::thread([this] { gc_loop(); });
|
||||
}
|
||||
|
||||
void stream_session_manager::stop_gc() {
|
||||
bool was_running = running.exchange(false);
|
||||
bool was_running;
|
||||
{
|
||||
std::lock_guard<std::mutex> lock(gc_wake_mu);
|
||||
was_running = running;
|
||||
running = false;
|
||||
}
|
||||
if (was_running) {
|
||||
{
|
||||
std::lock_guard<std::mutex> lock(gc_wake_mu);
|
||||
}
|
||||
gc_wake_cv.notify_all();
|
||||
if (gc_thread.joinable()) {
|
||||
gc_thread.join();
|
||||
@@ -270,15 +371,15 @@ void stream_session_manager::stop_gc() {
|
||||
}
|
||||
|
||||
void stream_session_manager::gc_loop() {
|
||||
while (running.load(std::memory_order_acquire)) {
|
||||
while (true) {
|
||||
{
|
||||
std::unique_lock<std::mutex> lock(gc_wake_mu);
|
||||
gc_wake_cv.wait_for(lock,
|
||||
std::chrono::seconds(STREAM_SESSION_GC_INTERVAL_SECONDS),
|
||||
[this] { return !running.load(std::memory_order_acquire); });
|
||||
}
|
||||
if (!running.load(std::memory_order_acquire)) {
|
||||
return;
|
||||
[this] { return !running; });
|
||||
if (!running) {
|
||||
return;
|
||||
}
|
||||
}
|
||||
int64_t cutoff = now_seconds() - STREAM_SESSION_TTL_SECONDS;
|
||||
std::vector<stream_session_ptr> to_drop;
|
||||
@@ -301,10 +402,19 @@ void stream_session_manager::gc_loop() {
|
||||
}
|
||||
}
|
||||
|
||||
// process wide manager, lifecycle controlled by llama-server main() via start_gc/stop_gc
|
||||
stream_session_manager g_stream_sessions;
|
||||
// stream_pipe
|
||||
|
||||
// stream_pipe ---------------------------------------------------------------------------------
|
||||
// consumer end: read-only replay of the ring buffer, the destructor does not finalize the session
|
||||
struct stream_pipe_consumer : stream_pipe {
|
||||
stream_read_status read(size_t & offset,
|
||||
const std::function<bool(const char *, size_t)> & sink,
|
||||
const std::function<bool()> & should_stop);
|
||||
|
||||
static std::shared_ptr<stream_pipe_consumer> create(stream_session_ptr session);
|
||||
|
||||
private:
|
||||
explicit stream_pipe_consumer(stream_session_ptr session);
|
||||
};
|
||||
|
||||
stream_pipe::stream_pipe(stream_session_ptr session)
|
||||
: session_(std::move(session)) {
|
||||
@@ -408,12 +518,10 @@ static server_http_res_ptr make_error_response(int status, const std::string & m
|
||||
return res;
|
||||
}
|
||||
|
||||
server_http_context::handler_t make_stream_get_handler() {
|
||||
server_http_context::handler_t server_stream_make_get_handler() {
|
||||
return [](const server_http_req & req) -> server_http_res_ptr {
|
||||
// GET /v1/stream/<conv_id>?from=N replays the SSE bytes already buffered for the
|
||||
// session, blocks for more bytes when the session is still running, returns when
|
||||
// the session is finalized. the body is streamed back as text/event-stream so the
|
||||
// browser EventSource can attach to it like a fresh request
|
||||
// GET /v1/stream/<conv_id>?from=N replays buffered SSE bytes then blocks for live
|
||||
// bytes until the session finalizes, streamed as text/event-stream for EventSource
|
||||
std::string conv_id = req.get_param("conv_id");
|
||||
if (conv_id.empty()) {
|
||||
return make_error_response(400, "Missing conversation id in path", ERROR_TYPE_INVALID_REQUEST);
|
||||
@@ -459,11 +567,10 @@ server_http_context::handler_t make_stream_get_handler() {
|
||||
};
|
||||
}
|
||||
|
||||
server_http_context::handler_t make_streams_lookup_handler() {
|
||||
server_http_context::handler_t server_stream_make_lookup_handler() {
|
||||
return [](const server_http_req & req) -> server_http_res_ptr {
|
||||
// POST /v1/streams/lookup with body {"conversation_ids": ["X", "Y", ...]} returns the
|
||||
// matching sessions, only for ids the caller already knows. each id matches the exact key
|
||||
// and any "<id>::<model>" variant, so one lookup covers every per model session for a conv
|
||||
// POST /v1/streams/lookup returns the matching sessions, only for ids the caller already
|
||||
// knows. each id matches the exact key and any "<id>::<model>" per model variant
|
||||
std::vector<std::string> requested;
|
||||
try {
|
||||
json body = json::parse(req.body);
|
||||
@@ -518,11 +625,10 @@ server_http_context::handler_t make_streams_lookup_handler() {
|
||||
};
|
||||
}
|
||||
|
||||
server_http_context::handler_t make_stream_delete_handler() {
|
||||
server_http_context::handler_t server_stream_make_delete_handler() {
|
||||
return [](const server_http_req & req) -> server_http_res_ptr {
|
||||
// DELETE /v1/stream/<conv_id> is the explicit user Stop, cancels the producer hook
|
||||
// wired by handle_completions_impl and evicts the buffer. idempotent, a session that
|
||||
// already finalized or was never created returns 204 either way
|
||||
// DELETE /v1/stream/<conv_id> is the explicit user Stop, cancels the producer and evicts
|
||||
// the buffer. idempotent, returns 204 even if the session was already gone
|
||||
std::string conv_id = req.get_param("conv_id");
|
||||
if (conv_id.empty()) {
|
||||
return make_error_response(400, "Missing conversation id in path", ERROR_TYPE_INVALID_REQUEST);
|
||||
@@ -536,7 +642,7 @@ server_http_context::handler_t make_stream_delete_handler() {
|
||||
};
|
||||
}
|
||||
|
||||
std::string stream_conv_id_from_headers(const std::map<std::string, std::string> & headers) {
|
||||
std::string server_stream_conv_id_from_headers(const std::map<std::string, std::string> & headers) {
|
||||
// case-insensitive scan for x-conversation-id
|
||||
static constexpr char target[] = "x-conversation-id";
|
||||
static constexpr size_t target_len = sizeof(target) - 1;
|
||||
@@ -555,8 +661,8 @@ std::string stream_conv_id_from_headers(const std::map<std::string, std::string>
|
||||
return std::string();
|
||||
}
|
||||
|
||||
void stream_session_attach_pipe(server_http_res & res, const std::map<std::string, std::string> & headers) {
|
||||
std::string conversation_id = stream_conv_id_from_headers(headers);
|
||||
void server_stream_session_attach_pipe(server_http_res & res, const std::map<std::string, std::string> & headers) {
|
||||
std::string conversation_id = server_stream_conv_id_from_headers(headers);
|
||||
SRV_TRC("conv_id=%s (empty=%d)\n", conversation_id.c_str(), conversation_id.empty() ? 1 : 0);
|
||||
if (conversation_id.empty()) {
|
||||
return;
|
||||
@@ -565,7 +671,7 @@ void stream_session_attach_pipe(server_http_res & res, const std::map<std::strin
|
||||
res.spipe = stream_pipe_producer::create(session, res);
|
||||
}
|
||||
|
||||
std::function<bool()> stream_aware_should_stop(server_http_res * res, std::function<bool()> fallback) {
|
||||
std::function<bool()> server_stream_aware_should_stop(server_http_res * res, std::function<bool()> fallback) {
|
||||
return [res, fallback = std::move(fallback)]() -> bool {
|
||||
if (res->spipe) {
|
||||
return res->spipe->is_cancelled();
|
||||
|
||||
+15
-136
@@ -3,81 +3,23 @@
|
||||
#include "server-http.h"
|
||||
|
||||
#include <atomic>
|
||||
#include <condition_variable>
|
||||
#include <cstddef>
|
||||
#include <cstdint>
|
||||
#include <functional>
|
||||
#include <memory>
|
||||
#include <mutex>
|
||||
#include <shared_mutex>
|
||||
#include <string>
|
||||
#include <thread>
|
||||
#include <unordered_map>
|
||||
#include <vector>
|
||||
|
||||
enum class stream_read_status {
|
||||
OK,
|
||||
OFFSET_LOST,
|
||||
};
|
||||
// streaming buffer for one generation, survives HTTP disconnect. the producer appends SSE bytes,
|
||||
// readers drain from any offset via read_from. keyed by conversation_id, one conv = one live session
|
||||
|
||||
// streaming buffer for one generation, survives HTTP disconnect. the producer appends raw SSE
|
||||
// bytes, readers drain from any offset via read_from and block until more bytes or finalize.
|
||||
// keyed by conversation_id: one conv = at most one live session
|
||||
struct stream_session {
|
||||
std::string conversation_id;
|
||||
int64_t started_ts; // unix seconds at construction, used by /v1/streams listing
|
||||
|
||||
stream_session(std::string conversation_id_, size_t max_bytes_);
|
||||
stream_session(const stream_session &) = delete;
|
||||
stream_session & operator=(const stream_session &) = delete;
|
||||
|
||||
// append raw bytes, drops from the front if the cap is reached.
|
||||
// returns false if the session is already finalized
|
||||
bool append(const char * data, size_t len);
|
||||
|
||||
// mark the session as complete, wakes all pending readers
|
||||
void finalize();
|
||||
|
||||
// drain bytes from offset, calling sink for each chunk. blocks until more
|
||||
// bytes arrive or finalize is called. returns OK on clean exit, OFFSET_LOST
|
||||
// if offset falls below the dropped prefix
|
||||
stream_read_status read_from(size_t offset,
|
||||
const std::function<bool(const char *, size_t)> & sink,
|
||||
const std::function<bool()> & should_stop);
|
||||
|
||||
bool is_done() const;
|
||||
bool is_cancelled() const;
|
||||
size_t total_size() const; // bytes that ever entered the session
|
||||
size_t dropped_prefix() const; // bytes evicted from the front due to cap
|
||||
int64_t completed_at() const; // 0 while alive, unix seconds after finalize
|
||||
|
||||
// attach the producer stop hook used to cancel its reader, pass an empty function to detach
|
||||
void set_stop_producer(std::function<void()> fn);
|
||||
|
||||
// signal the producer to abort its inference asap via the stop hook, idempotent
|
||||
void cancel();
|
||||
|
||||
private:
|
||||
mutable std::mutex mu;
|
||||
std::condition_variable cv;
|
||||
std::vector<char> buffer;
|
||||
size_t prefix_dropped;
|
||||
size_t cap_bytes;
|
||||
std::atomic<bool> done;
|
||||
std::atomic<bool> cancelled;
|
||||
std::atomic<int64_t> completed_ts;
|
||||
std::function<void()> stop_producer; // protected by mu
|
||||
};
|
||||
struct stream_session;
|
||||
|
||||
using stream_session_ptr = std::shared_ptr<stream_session>;
|
||||
|
||||
// one end of a stream_session pipe. the base holds the session and the shared query, the
|
||||
// producer and consumer ends derive from it. virtual dtor so each end runs its own teardown:
|
||||
// base of the producer/consumer pipe ends. virtual dtor so each runs its own teardown:
|
||||
// the producer finalizes the session, the consumer leaves it untouched
|
||||
struct stream_pipe {
|
||||
virtual ~stream_pipe() = default;
|
||||
|
||||
// true if the session was cancelled (e.g. via DELETE /v1/stream/<conv_id>)
|
||||
bool is_cancelled() const;
|
||||
|
||||
protected:
|
||||
@@ -95,7 +37,6 @@ protected:
|
||||
struct stream_pipe_producer : stream_pipe {
|
||||
~stream_pipe_producer() override;
|
||||
|
||||
// append raw bytes to the session's ring buffer, returns false if already finalized
|
||||
bool write(const char * data, size_t len);
|
||||
|
||||
// mark the natural end on the wire so a later close() is a no-op
|
||||
@@ -121,83 +62,21 @@ private:
|
||||
server_http_res * res_ = nullptr;
|
||||
};
|
||||
|
||||
// consumer end: read-only replay of the ring buffer, the destructor does not finalize the session
|
||||
struct stream_pipe_consumer : stream_pipe {
|
||||
// drain bytes from offset, calling sink for each available chunk. blocks until more data
|
||||
// arrives or the session finalizes. should_stop is polled, returns OFFSET_LOST if offset
|
||||
// fell below the dropped prefix
|
||||
stream_read_status read(size_t & offset,
|
||||
const std::function<bool(const char *, size_t)> & sink,
|
||||
const std::function<bool()> & should_stop);
|
||||
void server_stream_session_manager_start();
|
||||
void server_stream_session_manager_stop();
|
||||
|
||||
static std::shared_ptr<stream_pipe_consumer> create(stream_session_ptr session);
|
||||
// route handler factories wired under /v1/stream/* by server.cpp
|
||||
server_http_context::handler_t server_stream_make_get_handler();
|
||||
server_http_context::handler_t server_stream_make_lookup_handler();
|
||||
server_http_context::handler_t server_stream_make_delete_handler();
|
||||
|
||||
private:
|
||||
explicit stream_pipe_consumer(stream_session_ptr session);
|
||||
};
|
||||
// extract the X-Conversation-Id header value (case-insensitive), empty when absent
|
||||
std::string server_stream_conv_id_from_headers(const std::map<std::string, std::string> & headers);
|
||||
|
||||
// owns all live sessions, runs a periodic GC to evict expired ones.
|
||||
// the map is keyed by conversation_id, so the invariant "one conv = at most one
|
||||
// live session" is enforced at the type level
|
||||
class stream_session_manager {
|
||||
public:
|
||||
stream_session_manager();
|
||||
~stream_session_manager();
|
||||
|
||||
stream_session_manager(const stream_session_manager &) = delete;
|
||||
stream_session_manager & operator=(const stream_session_manager &) = delete;
|
||||
|
||||
// install a new session for this conversation, evicting and cancelling any previous one.
|
||||
// the conversation_id must be non empty, the caller is responsible for that check.
|
||||
// returns the new session
|
||||
stream_session_ptr create_or_replace(const std::string & conversation_id);
|
||||
|
||||
// lookup, returns null if unknown or already evicted
|
||||
stream_session_ptr get(const std::string & conversation_id);
|
||||
|
||||
// list every live or recently completed session, used by GET /v1/streams without filter
|
||||
std::vector<stream_session_ptr> list_all() const;
|
||||
|
||||
// remove from the map and finalize, wakes any pending readers
|
||||
void evict(const std::string & conversation_id);
|
||||
|
||||
// signal the producer to cancel asap then evict, used by the explicit user Stop path
|
||||
void evict_and_cancel(const std::string & conversation_id);
|
||||
|
||||
void start_gc();
|
||||
void stop_gc();
|
||||
|
||||
private:
|
||||
void gc_loop();
|
||||
|
||||
mutable std::shared_mutex map_mu;
|
||||
std::unordered_map<std::string, stream_session_ptr> sessions; // key: conversation_id
|
||||
std::thread gc_thread;
|
||||
std::atomic<bool> running;
|
||||
std::mutex gc_wake_mu;
|
||||
std::condition_variable gc_wake_cv;
|
||||
};
|
||||
|
||||
// process wide manager, linked by both llama-server and llama-cli. llama-server main() drives
|
||||
// start_gc/stop_gc, llama-cli leaves it idle. the dtor calls stop_gc() unconditionally so exit
|
||||
// is safe whether or not the GC thread ran
|
||||
extern stream_session_manager g_stream_sessions;
|
||||
|
||||
// route handler factories operating on g_stream_sessions, wired under /v1/stream/* by server.cpp.
|
||||
// keeps the resumable stream surface confined to server-stream
|
||||
server_http_context::handler_t make_stream_get_handler();
|
||||
server_http_context::handler_t make_streams_lookup_handler();
|
||||
server_http_context::handler_t make_stream_delete_handler();
|
||||
|
||||
// extract the X-Conversation-Id header value (case-insensitive), empty when absent. exposed so
|
||||
// the router can track which child serves a forwarded POST
|
||||
std::string stream_conv_id_from_headers(const std::map<std::string, std::string> & headers);
|
||||
|
||||
// on an X-Conversation-Id header, create or replace the session and attach a producer pipe to
|
||||
// res. no-op when absent, called from the server_res_generator constructor
|
||||
void stream_session_attach_pipe(server_http_res & res, const std::map<std::string, std::string> & headers);
|
||||
// on an X-Conversation-Id header, create or replace the session and attach a producer pipe to res
|
||||
void server_stream_session_attach_pipe(server_http_res & res, const std::map<std::string, std::string> & headers);
|
||||
|
||||
// should_stop closure that ignores peer disconnect when a pipe is attached, so only an explicit
|
||||
// DELETE stops the producer and generation keeps flowing into the ring buffer. without a pipe it
|
||||
// delegates to fallback, the legacy non-resumable flow
|
||||
std::function<bool()> stream_aware_should_stop(server_http_res * res, std::function<bool()> fallback);
|
||||
std::function<bool()> server_stream_aware_should_stop(server_http_res * res, std::function<bool()> fallback);
|
||||
|
||||
+54
-31
@@ -36,6 +36,19 @@ static inline void signal_handler(int signal) {
|
||||
shutdown_handler(signal);
|
||||
}
|
||||
|
||||
// satisfies -Wmissing-declarations (used by llama command)
|
||||
int llama_server(int argc, char ** argv);
|
||||
|
||||
// to be used via CLI (argc / argv are used by router mode only)
|
||||
int llama_server(common_params & params, int argc, char ** argv);
|
||||
void llama_server_terminate();
|
||||
void llama_server_terminate() {
|
||||
if (shutdown_handler) {
|
||||
shutdown_handler(0);
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
// wrapper function that handles exceptions and logs errors
|
||||
// this is to make sure handler_t never throws exceptions; instead, it returns an error response
|
||||
static server_http_context::handler_t ex_wrapper(server_http_context::handler_t func) {
|
||||
@@ -72,9 +85,6 @@ static server_http_context::handler_t ex_wrapper(server_http_context::handler_t
|
||||
};
|
||||
}
|
||||
|
||||
// satisfies -Wmissing-declarations
|
||||
int llama_server(int argc, char ** argv);
|
||||
|
||||
int llama_server(int argc, char ** argv) {
|
||||
std::setlocale(LC_NUMERIC, "C");
|
||||
|
||||
@@ -85,7 +95,7 @@ int llama_server(int argc, char ** argv) {
|
||||
|
||||
// start the stream session manager GC right after common init, before any HTTP route can
|
||||
// touch it. lifecycle is symmetric, stop_gc() runs in clean_up() before backend free
|
||||
g_stream_sessions.start_gc();
|
||||
server_stream_session_manager_start();
|
||||
|
||||
if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_SERVER)) {
|
||||
return 1;
|
||||
@@ -94,16 +104,26 @@ int llama_server(int argc, char ** argv) {
|
||||
llama_backend_init();
|
||||
llama_numa_init(params.numa);
|
||||
|
||||
return llama_server(params, argc, argv);
|
||||
}
|
||||
|
||||
int llama_server(common_params & params, int argc, char ** argv) {
|
||||
bool is_run_by_cli = (argv == nullptr);
|
||||
|
||||
common_models_handler models_handler;
|
||||
try {
|
||||
models_handler = common_models_handler_init(params, LLAMA_EXAMPLE_SERVER);
|
||||
if (common_models_handler_is_preset_repo(models_handler)) {
|
||||
// apply the preset and start the server in router mode
|
||||
common_models_handler_apply(models_handler, params);
|
||||
|
||||
// note: router mode also accepts -hf remote-preset, so we need to check that first
|
||||
if (!is_run_by_cli && !params.model.hf_repo.empty()) {
|
||||
try {
|
||||
models_handler = common_models_handler_init(params, LLAMA_EXAMPLE_SERVER);
|
||||
if (common_models_handler_is_preset_repo(models_handler)) {
|
||||
// apply the preset and start the server in router mode
|
||||
common_models_handler_apply(models_handler, params);
|
||||
}
|
||||
} catch (const std::exception & e) {
|
||||
SRV_ERR("failed to fetch model metadata: %s\n", e.what());
|
||||
return 1;
|
||||
}
|
||||
} catch (const std::exception & e) {
|
||||
SRV_ERR("failed to fetch model metadata: %s\n", e.what());
|
||||
return 1;
|
||||
}
|
||||
|
||||
// router server never loads a model and must not touch the GPU
|
||||
@@ -245,8 +265,8 @@ int llama_server(int argc, char ** argv) {
|
||||
ctx_http.post("/slots/:id_slot", ex_wrapper(routes.post_slots));
|
||||
|
||||
// resumable streaming, the conversation_id is the session identity end to end. router and
|
||||
// child wire different handlers under the same paths: a child binds the local g_stream_sessions
|
||||
// backed factories, the router binds proxies that resolve the owning child through the
|
||||
// child wire different handlers under the same paths: a child binds the local session
|
||||
// factories, the router binds proxies that resolve the owning child through the
|
||||
// conv_id -> model map
|
||||
server_http_context::handler_t stream_get_h;
|
||||
server_http_context::handler_t streams_lookup_h;
|
||||
@@ -256,9 +276,9 @@ int llama_server(int argc, char ** argv) {
|
||||
streams_lookup_h = models_routes->router_streams_lookup;
|
||||
stream_delete_h = models_routes->router_stream_delete;
|
||||
} else {
|
||||
stream_get_h = make_stream_get_handler();
|
||||
streams_lookup_h = make_streams_lookup_handler();
|
||||
stream_delete_h = make_stream_delete_handler();
|
||||
stream_get_h = server_stream_make_get_handler();
|
||||
streams_lookup_h = server_stream_make_lookup_handler();
|
||||
stream_delete_h = server_stream_make_delete_handler();
|
||||
}
|
||||
ctx_http.get ("/v1/stream/:conv_id", ex_wrapper(stream_get_h));
|
||||
// POST /v1/streams/lookup with body {"conversation_ids": [...]}. you can only ask for ids
|
||||
@@ -321,8 +341,9 @@ int llama_server(int argc, char ** argv) {
|
||||
|
||||
if (child.is_child() && child.get_mode() == SERVER_CHILD_MODE_DOWNLOAD) {
|
||||
return child.run_download(params);
|
||||
} else if (!is_router_server) {
|
||||
} else if (!is_router_server && !is_run_by_cli) {
|
||||
// single-model mode (NOT spawned by router)
|
||||
// if this is invoked by CLI, model downloading should be already handled
|
||||
try {
|
||||
common_models_handler_apply(models_handler, params);
|
||||
} catch (const std::exception & e) {
|
||||
@@ -343,7 +364,7 @@ int llama_server(int argc, char ** argv) {
|
||||
clean_up = [&models_routes]() {
|
||||
SRV_INF("%s: cleaning up before exit...\n", __func__);
|
||||
// stop the session GC first, it finalizes live sessions and wakes pending readers
|
||||
g_stream_sessions.stop_gc();
|
||||
server_stream_session_manager_stop();
|
||||
if (models_routes.has_value()) {
|
||||
models_routes->stopping.store(true); // maybe redundant, but just to be safe
|
||||
models_routes->models.unload_all();
|
||||
@@ -371,7 +392,7 @@ int llama_server(int argc, char ** argv) {
|
||||
clean_up = [&ctx_http, &ctx_server]() {
|
||||
SRV_INF("%s: cleaning up before exit...\n", __func__);
|
||||
// stop the session GC first, it finalizes live sessions and wakes pending readers
|
||||
g_stream_sessions.stop_gc();
|
||||
server_stream_session_manager_stop();
|
||||
ctx_http.stop();
|
||||
ctx_server.terminate();
|
||||
llama_backend_free();
|
||||
@@ -411,20 +432,22 @@ int llama_server(int argc, char ** argv) {
|
||||
};
|
||||
}
|
||||
|
||||
// TODO: refactor in common/console
|
||||
// register signal handler if not running by CLI
|
||||
if (!is_run_by_cli) {
|
||||
#if defined (__unix__) || (defined (__APPLE__) && defined (__MACH__))
|
||||
struct sigaction sigint_action;
|
||||
sigint_action.sa_handler = signal_handler;
|
||||
sigemptyset (&sigint_action.sa_mask);
|
||||
sigint_action.sa_flags = 0;
|
||||
sigaction(SIGINT, &sigint_action, NULL);
|
||||
sigaction(SIGTERM, &sigint_action, NULL);
|
||||
struct sigaction sigint_action;
|
||||
sigint_action.sa_handler = signal_handler;
|
||||
sigemptyset (&sigint_action.sa_mask);
|
||||
sigint_action.sa_flags = 0;
|
||||
sigaction(SIGINT, &sigint_action, NULL);
|
||||
sigaction(SIGTERM, &sigint_action, NULL);
|
||||
#elif defined (_WIN32)
|
||||
auto console_ctrl_handler = +[](DWORD ctrl_type) -> BOOL {
|
||||
return (ctrl_type == CTRL_C_EVENT) ? (signal_handler(SIGINT), true) : false;
|
||||
};
|
||||
SetConsoleCtrlHandler(reinterpret_cast<PHANDLER_ROUTINE>(console_ctrl_handler), true);
|
||||
auto console_ctrl_handler = +[](DWORD ctrl_type) -> BOOL {
|
||||
return (ctrl_type == CTRL_C_EVENT) ? (signal_handler(SIGINT), true) : false;
|
||||
};
|
||||
SetConsoleCtrlHandler(reinterpret_cast<PHANDLER_ROUTINE>(console_ctrl_handler), true);
|
||||
#endif
|
||||
}
|
||||
|
||||
SRV_INF("listening on %s\n", ctx_http.listening_address.c_str());
|
||||
|
||||
|
||||
Generated
+4
-4
@@ -11,7 +11,7 @@
|
||||
"@chromatic-com/storybook": "5.0.0",
|
||||
"@eslint/compat": "1.4.1",
|
||||
"@eslint/js": "9.39.2",
|
||||
"@internationalized/date": "3.10.1",
|
||||
"@internationalized/date": "3.12.2",
|
||||
"@lucide/svelte": "0.515.0",
|
||||
"@modelcontextprotocol/sdk": "1.26.0",
|
||||
"@playwright/test": "1.56.1",
|
||||
@@ -2981,9 +2981,9 @@
|
||||
}
|
||||
},
|
||||
"node_modules/@internationalized/date": {
|
||||
"version": "3.10.1",
|
||||
"resolved": "https://registry.npmjs.org/@internationalized/date/-/date-3.10.1.tgz",
|
||||
"integrity": "sha512-oJrXtQiAXLvT9clCf1K4kxp3eKsQhIaZqxEyowkBcsvZDdZkbWrVmnGknxs5flTD0VGsxrxKgBCZty1EzoiMzA==",
|
||||
"version": "3.12.2",
|
||||
"resolved": "https://registry.npmjs.org/@internationalized/date/-/date-3.12.2.tgz",
|
||||
"integrity": "sha512-FY1Y+H64NDs+HAF6omlnWxm3mEpfgaCSWtL5l551ZZfImA+kGjPFgrnJrGjH6lfmLL0g8Z/mBu1R3kufeCp6Jw==",
|
||||
"dev": true,
|
||||
"license": "Apache-2.0",
|
||||
"dependencies": {
|
||||
|
||||
@@ -30,7 +30,7 @@
|
||||
"@chromatic-com/storybook": "5.0.0",
|
||||
"@eslint/compat": "1.4.1",
|
||||
"@eslint/js": "9.39.2",
|
||||
"@internationalized/date": "3.10.1",
|
||||
"@internationalized/date": "3.12.2",
|
||||
"@lucide/svelte": "0.515.0",
|
||||
"@modelcontextprotocol/sdk": "1.26.0",
|
||||
"@playwright/test": "1.56.1",
|
||||
|
||||
+7
-2
@@ -11,7 +11,8 @@
|
||||
} from '$lib/constants';
|
||||
import {
|
||||
ChatFormActionAddToolsSubmenu,
|
||||
ChatFormActionAddMcpServersSubmenu
|
||||
ChatFormActionAddMcpServersSubmenu,
|
||||
ChatFormActionAddReasoningSubmenu
|
||||
} from '$lib/components/app';
|
||||
import { useAttachmentMenu } from '$lib/hooks/use-attachment-menu.svelte';
|
||||
|
||||
@@ -92,7 +93,11 @@
|
||||
</Tooltip.Content>
|
||||
</Tooltip.Root>
|
||||
|
||||
<DropdownMenu.Content align="start" class="w-48">
|
||||
<DropdownMenu.Content align="start" class="w-52">
|
||||
<ChatFormActionAddReasoningSubmenu />
|
||||
|
||||
<DropdownMenu.Separator />
|
||||
|
||||
<DropdownMenu.Sub>
|
||||
<DropdownMenu.SubTrigger class="flex cursor-pointer items-center gap-2">
|
||||
<File class="h-4 w-4" />
|
||||
|
||||
+29
-46
@@ -2,7 +2,7 @@
|
||||
import { Lightbulb, LightbulbOff, Check, Info } from '@lucide/svelte';
|
||||
import * as DropdownMenu from '$lib/components/ui/dropdown-menu';
|
||||
import * as Tooltip from '$lib/components/ui/tooltip';
|
||||
import { ReasoningEffort, MessageRole } from '$lib/enums';
|
||||
import { ReasoningEffort } from '$lib/enums';
|
||||
import { REASONING_EFFORT_TOKENS } from '$lib/constants/reasoning-effort-tokens';
|
||||
import { REASONING_EFFORT_LEVELS } from '$lib/constants/reasoning-effort';
|
||||
import type { ReasoningEffortLevel } from '$lib/types';
|
||||
@@ -18,31 +18,23 @@
|
||||
import { isRouterMode } from '$lib/stores/server.svelte';
|
||||
import type { DatabaseMessage } from '$lib/types/database';
|
||||
|
||||
let thinkingEnabled = $derived(conversationsStore.getThinkingEnabled());
|
||||
let currentEffort = $derived(conversationsStore.getReasoningEffort());
|
||||
let isOff = $derived(!thinkingEnabled);
|
||||
let tooltipText = $derived(thinkingEnabled ? `${currentEffort} Reasoning` : 'Disabled Reasoning');
|
||||
let subOpen = $state(false);
|
||||
|
||||
// Get conversation model from message history
|
||||
let conversationModel = $derived(
|
||||
chatStore.getConversationModel(activeMessages() as DatabaseMessage[])
|
||||
);
|
||||
|
||||
// Fallback: if model props aren't available, check if any assistant messages
|
||||
// for this model in the active conversation have reasoning content.
|
||||
let modelSupportsThinkingFromMessages = $derived.by(() => {
|
||||
const modelId = isRouterMode() ? modelsStore.selectedModelName || conversationModel : null;
|
||||
if (!modelId) return false;
|
||||
|
||||
const messages = conversationsStore.activeMessages;
|
||||
|
||||
return messages.some(
|
||||
(m: DatabaseMessage) =>
|
||||
m.role === MessageRole.ASSISTANT && m.model === modelId && !!m.reasoningContent
|
||||
(m) => m.role === 'assistant' && m.model === modelId && !!m.reasoningContent
|
||||
);
|
||||
});
|
||||
|
||||
// Check if model supports thinking. Primary: chat template from /props.
|
||||
// Fallback: message history (reasoning content in assistant messages).
|
||||
let modelSupportsThinking = $derived.by(() => {
|
||||
loadedModelIds();
|
||||
propsCacheVersion();
|
||||
@@ -52,15 +44,15 @@
|
||||
return checkModelSupportsThinking(modelId ?? '') || modelSupportsThinkingFromMessages;
|
||||
}
|
||||
|
||||
// In non-router mode, use the built-in supportsThinking
|
||||
return supportsThinking() || modelSupportsThinkingFromMessages;
|
||||
});
|
||||
|
||||
// Check if current item is selected
|
||||
let thinkingEnabled = $derived(conversationsStore.getThinkingEnabled());
|
||||
let currentEffort = $derived(conversationsStore.getReasoningEffort());
|
||||
let isOff = $derived(!thinkingEnabled);
|
||||
|
||||
function isSelected(item: ReasoningEffortLevel): boolean {
|
||||
if (item.isOff) {
|
||||
return isOff;
|
||||
}
|
||||
if (item.isOff) return isOff;
|
||||
return thinkingEnabled && currentEffort === item.value;
|
||||
}
|
||||
|
||||
@@ -76,39 +68,30 @@
|
||||
</script>
|
||||
|
||||
{#if modelSupportsThinking}
|
||||
<DropdownMenu.Root bind:open={subOpen}>
|
||||
<Tooltip.Root>
|
||||
<Tooltip.Trigger>
|
||||
<DropdownMenu.Trigger
|
||||
class={[
|
||||
'flex h-6 w-6 cursor-pointer items-center justify-center rounded-full p-0 transition-colors focus:outline-none focus-visible:ring-2 focus-visible:ring-ring focus-visible:ring-offset-2',
|
||||
thinkingEnabled ? 'bg-amber-400/10 hover:bg-amber-400/20' : 'bg-muted'
|
||||
]}
|
||||
aria-label={`${tooltipText}. Click to configure.`}
|
||||
>
|
||||
{#if thinkingEnabled}
|
||||
<Lightbulb class="h-3 w-3 text-amber-400" />
|
||||
{:else}
|
||||
<LightbulbOff class="h-3 w-3 text-muted-foreground" />
|
||||
{/if}
|
||||
</DropdownMenu.Trigger>
|
||||
</Tooltip.Trigger>
|
||||
<DropdownMenu.Sub bind:open={subOpen}>
|
||||
<DropdownMenu.SubTrigger class="flex cursor-pointer items-center gap-2">
|
||||
{#if thinkingEnabled}
|
||||
<Lightbulb class="h-4 w-4 shrink-0 text-amber-400" />
|
||||
{:else}
|
||||
<LightbulbOff class="h-4 w-4 shrink-0 text-muted-foreground" />
|
||||
{/if}
|
||||
|
||||
<Tooltip.Content>
|
||||
<p class="capitalize">{tooltipText}</p>
|
||||
</Tooltip.Content>
|
||||
</Tooltip.Root>
|
||||
<span class="text-sm inline-flex gap-2 {!thinkingEnabled ? 'text-muted-foreground' : ''}">
|
||||
Reasoning
|
||||
|
||||
<DropdownMenu.Content
|
||||
align="start"
|
||||
class="w-60 rounded-xl bg-popover p-3 text-popover-foreground shadow-md outline-none"
|
||||
<span class="capitalize text-muted-foreground">
|
||||
{thinkingEnabled ? currentEffort : 'off'}
|
||||
</span>
|
||||
</span>
|
||||
</DropdownMenu.SubTrigger>
|
||||
|
||||
<DropdownMenu.SubContent
|
||||
class="w-60 bg-popover p-1.5 text-popover-foreground shadow-md outline-none"
|
||||
>
|
||||
<div class="mb-2 px-2.5 text-sm font-medium">Reasoning effort</div>
|
||||
|
||||
{#each REASONING_EFFORT_LEVELS as level (level.value)}
|
||||
<button
|
||||
type="button"
|
||||
class="flex w-full cursor-pointer items-center gap-2 rounded-lg px-2.5 py-2 text-left text-sm transition-colors hover:bg-accent"
|
||||
class="flex w-full cursor-pointer items-center gap-3 rounded-md px-2 py-1.75 text-left text-sm transition-colors hover:bg-accent"
|
||||
class:bg-accent={isSelected(level)}
|
||||
onclick={() => handleSelection(level)}
|
||||
>
|
||||
@@ -140,6 +123,6 @@
|
||||
{/if}
|
||||
</button>
|
||||
{/each}
|
||||
</DropdownMenu.Content>
|
||||
</DropdownMenu.Root>
|
||||
</DropdownMenu.SubContent>
|
||||
</DropdownMenu.Sub>
|
||||
{/if}
|
||||
+44
-6
@@ -7,14 +7,20 @@
|
||||
ChatFormActionModels,
|
||||
ChatFormActionRecord,
|
||||
ChatFormActionSubmit,
|
||||
ChatFormReasoningToggle
|
||||
ChatFormContextGauge
|
||||
} from '$lib/components/app';
|
||||
import { FileTypeCategory } from '$lib/enums';
|
||||
import { FileTypeCategory, MessageRole } from '$lib/enums';
|
||||
import { mcpStore } from '$lib/stores/mcp.svelte';
|
||||
import { config } from '$lib/stores/settings.svelte';
|
||||
import { conversationsStore } from '$lib/stores/conversations.svelte';
|
||||
import { activeMessages, conversationsStore } from '$lib/stores/conversations.svelte';
|
||||
import {
|
||||
activeProcessingState,
|
||||
isChatStreaming,
|
||||
isLoading as chatIsLoading
|
||||
} from '$lib/stores/chat.svelte';
|
||||
import { getFileTypeCategory } from '$lib/utils';
|
||||
import { goto } from '$app/navigation';
|
||||
import { page } from '$app/state';
|
||||
import { ROUTES } from '$lib/constants/routes';
|
||||
|
||||
interface Props {
|
||||
@@ -93,6 +99,36 @@
|
||||
let activeMessage = $derived(
|
||||
conversationsStore.activeMessages[conversationsStore.activeMessages.length - 1]
|
||||
);
|
||||
|
||||
let hasProcessedTokens = $derived.by(() => {
|
||||
if (!page.params.id) return false;
|
||||
|
||||
const messages = activeMessages() as DatabaseMessage[];
|
||||
let totalHistoricalTokens = 0;
|
||||
for (const m of messages) {
|
||||
if (m.role !== MessageRole.ASSISTANT) continue;
|
||||
const timings = m.timings;
|
||||
if (!timings) continue;
|
||||
const agenticLlm = timings.agentic?.llm;
|
||||
if (agenticLlm?.prompt_n != null || agenticLlm?.predicted_n != null) {
|
||||
totalHistoricalTokens += (agenticLlm?.prompt_n ?? 0) + (agenticLlm?.predicted_n ?? 0);
|
||||
} else {
|
||||
totalHistoricalTokens += (timings.prompt_n ?? 0) + (timings.predicted_n ?? 0);
|
||||
}
|
||||
}
|
||||
if (totalHistoricalTokens > 0) return true;
|
||||
|
||||
if (!chatIsLoading() && !isChatStreaming()) return false;
|
||||
|
||||
const processingState = activeProcessingState();
|
||||
if (!processingState) return false;
|
||||
const livePromptTokens = Math.max(
|
||||
processingState.promptTokens ?? 0,
|
||||
processingState.promptProgress?.processed ?? 0
|
||||
);
|
||||
const liveOutputTokens = processingState.outputTokensUsed ?? 0;
|
||||
return livePromptTokens > 0 || liveOutputTokens > 0;
|
||||
});
|
||||
</script>
|
||||
|
||||
<div
|
||||
@@ -100,7 +136,7 @@
|
||||
style="container-type: inline-size"
|
||||
>
|
||||
{#if showAddButton}
|
||||
<div class="mr-auto flex items-center gap-3">
|
||||
<div class="mr-auto flex items-center gap-2">
|
||||
<ChatFormActionsAdd
|
||||
{disabled}
|
||||
{hasAudioModality}
|
||||
@@ -117,8 +153,10 @@
|
||||
</div>
|
||||
{/if}
|
||||
|
||||
<div class="flex items-center gap-2">
|
||||
<ChatFormReasoningToggle />
|
||||
<div class="flex items-center gap-1.5">
|
||||
{#if hasProcessedTokens}
|
||||
<ChatFormContextGauge />
|
||||
{/if}
|
||||
|
||||
{#if showModelSelector}
|
||||
<ChatFormActionModels
|
||||
|
||||
+9
-14
@@ -6,6 +6,7 @@
|
||||
import { REASONING_EFFORT_TOKENS } from '$lib/constants/reasoning-effort-tokens';
|
||||
import { REASONING_EFFORT_LEVELS } from '$lib/constants/reasoning-effort';
|
||||
import type { ReasoningEffortLevel } from '$lib/types';
|
||||
import { DIALOG_SUBMENU_CONTENT } from '$lib/constants/css-classes';
|
||||
import {
|
||||
modelsStore,
|
||||
checkModelSupportsThinking,
|
||||
@@ -71,9 +72,7 @@
|
||||
|
||||
{#if modelSupportsThinking}
|
||||
<DropdownMenu.Sub bind:open={subOpen}>
|
||||
<DropdownMenu.SubTrigger
|
||||
class="flex cursor-pointer items-center gap-2 rounded-md px-2.5 py-1.5 text-sm transition-colors outline-none hover:bg-accent focus:bg-accent"
|
||||
>
|
||||
<DropdownMenu.SubTrigger class="flex cursor-pointer items-center gap-2">
|
||||
{#if thinkingEnabled}
|
||||
<Lightbulb class="h-4 w-4 shrink-0 text-amber-400" />
|
||||
{:else}
|
||||
@@ -89,23 +88,15 @@
|
||||
{/if}
|
||||
</DropdownMenu.SubTrigger>
|
||||
|
||||
<DropdownMenu.SubContent
|
||||
class="w-60 rounded-xl bg-popover p-3 text-popover-foreground shadow-md outline-none data-[side=bottom]:slide-in-from-top-2 data-[side=left]:slide-in-from-right-2 data-[side=right]:slide-in-from-left-2 data-[side=top]:slide-in-from-bottom-2 data-[state=closed]:animate-out data-[state=closed]:fade-out-0 data-[state=closed]:zoom-out-95 data-[state=open]:animate-in data-[state=open]:fade-in-0 data-[state=open]:zoom-in-95"
|
||||
>
|
||||
<DropdownMenu.SubContent class={DIALOG_SUBMENU_CONTENT}>
|
||||
{#each REASONING_EFFORT_LEVELS as level (level.value)}
|
||||
<button
|
||||
type="button"
|
||||
class="flex w-full cursor-pointer items-center gap-2 rounded-lg px-2.5 py-2 text-left text-sm transition-colors hover:bg-accent"
|
||||
class="flex w-full cursor-pointer items-center gap-2"
|
||||
class:bg-accent={isSelected(level)}
|
||||
onclick={() => handleSelection(level)}
|
||||
>
|
||||
{#if isSelected(level)}
|
||||
<Check class="h-4 w-4 shrink-0 text-foreground" />
|
||||
{:else}
|
||||
<div class="h-4 w-4 shrink-0"></div>
|
||||
{/if}
|
||||
|
||||
<span class="flex-1">{level.label}</span>
|
||||
<span class="flex-1 text-left">{level.label}</span>
|
||||
|
||||
{#if !level.isOff}
|
||||
<span class="text-[11px] text-muted-foreground opacity-60">
|
||||
@@ -125,6 +116,10 @@
|
||||
</Tooltip.Content>
|
||||
</Tooltip.Root>
|
||||
{/if}
|
||||
|
||||
{#if isSelected(level)}
|
||||
<Check class="h-4 w-4 shrink-0 text-foreground" />
|
||||
{/if}
|
||||
</button>
|
||||
{/each}
|
||||
</DropdownMenu.SubContent>
|
||||
|
||||
+108
@@ -0,0 +1,108 @@
|
||||
<script lang="ts">
|
||||
import { untrack } from 'svelte';
|
||||
import * as HoverCard from '$lib/components/ui/hover-card';
|
||||
import { activeConversation, activeMessages } from '$lib/stores/conversations.svelte';
|
||||
import { chatStore, isChatStreaming, isLoading } from '$lib/stores/chat.svelte';
|
||||
import { formatParameters } from '$lib/utils/formatters';
|
||||
import { useContextGauge } from '$lib/hooks/use-context-gauge.svelte';
|
||||
import ContextGaugeDial from './ContextGaugeDial.svelte';
|
||||
import ContextGaugeDetails from './ContextGaugeDetails.svelte';
|
||||
import ContextGaugeLoadModel from './ContextGaugeLoadModel.svelte';
|
||||
import { colorLevelBgClass, colorLevelTextClass } from './context-gauge';
|
||||
|
||||
const gauge = useContextGauge();
|
||||
|
||||
$effect(() => {
|
||||
const conv = activeConversation();
|
||||
untrack(() => chatStore.setActiveProcessingConversation(conv?.id ?? null));
|
||||
});
|
||||
|
||||
$effect(() => {
|
||||
const conv = activeConversation();
|
||||
const messages = activeMessages() as DatabaseMessage[];
|
||||
if (!conv) return;
|
||||
if (isLoading() || isChatStreaming()) return;
|
||||
|
||||
if (messages.length === 0) {
|
||||
untrack(() => chatStore.clearProcessingState(conv.id));
|
||||
return;
|
||||
}
|
||||
|
||||
untrack(() => chatStore.restoreProcessingStateFromMessages(messages, conv.id));
|
||||
});
|
||||
|
||||
$effect(() => {
|
||||
gauge.startMonitoring();
|
||||
});
|
||||
|
||||
const showProgressBar = $derived(
|
||||
gauge.contextTotal !== null &&
|
||||
gauge.contextTotal > 0 &&
|
||||
(gauge.activeModelId !== null || gauge.isActiveModelLoaded)
|
||||
);
|
||||
</script>
|
||||
|
||||
<HoverCard.Root>
|
||||
<HoverCard.Trigger class="flex h-5 w-5 cursor-default items-center justify-center">
|
||||
<ContextGaugeDial percent={gauge.contextPercent} level={gauge.colorLevel} />
|
||||
</HoverCard.Trigger>
|
||||
|
||||
<HoverCard.Content
|
||||
side="bottom"
|
||||
class="z-50 w-64 rounded-lg border border-border/50 bg-popover p-3 text-popover-foreground shadow-lg"
|
||||
>
|
||||
<div class="flex flex-col gap-2">
|
||||
<div class="flex items-center gap-2">
|
||||
<span class="font-medium">Context</span>
|
||||
<span class="text-muted-foreground">·</span>
|
||||
<span class="font-mono text-muted-foreground">
|
||||
{formatParameters(gauge.contextUsed)}
|
||||
/ {gauge.contextTotal !== null ? formatParameters(gauge.contextTotal) : '-'}
|
||||
</span>
|
||||
</div>
|
||||
|
||||
{#if gauge.activeModelId !== null && !gauge.isActiveModelLoaded}
|
||||
<ContextGaugeLoadModel
|
||||
modelId={gauge.activeModelId}
|
||||
isLoading={gauge.isActiveModelLoading}
|
||||
onLoad={gauge.loadModel}
|
||||
/>
|
||||
{:else if showProgressBar}
|
||||
<div class="h-1.5 w-full overflow-hidden rounded-full bg-muted">
|
||||
<div
|
||||
class="h-full rounded-full transition-all duration-300 {colorLevelBgClass(
|
||||
gauge.colorLevel
|
||||
)}"
|
||||
style="width: {gauge.contextPercent}%"
|
||||
></div>
|
||||
</div>
|
||||
|
||||
<div class="flex justify-between text-xs text-muted-foreground">
|
||||
<span>
|
||||
<span class={colorLevelTextClass(gauge.colorLevel)}>{gauge.contextPercent}%</span> used
|
||||
</span>
|
||||
<span>
|
||||
{formatParameters((gauge.contextTotal ?? 0) - gauge.contextUsed)} remaining
|
||||
</span>
|
||||
</div>
|
||||
{:else}
|
||||
<div class="text-xs text-muted-foreground">No context info available</div>
|
||||
{/if}
|
||||
|
||||
{#if gauge.hasAnyUsage}
|
||||
<ContextGaugeDetails
|
||||
currentRead={gauge.currentRead}
|
||||
currentFresh={gauge.currentFresh}
|
||||
currentCache={gauge.currentCache}
|
||||
currentOutput={gauge.currentOutput}
|
||||
kvTotal={gauge.kvTotal}
|
||||
cumulativeRead={gauge.cumulativeRead}
|
||||
cumulativeOutput={gauge.cumulativeOutput}
|
||||
cumulativeCacheTotal={gauge.cumulativeCacheTotal}
|
||||
averageTokensPerSecond={gauge.averageTokensPerSecond}
|
||||
transientDetails={gauge.transientDetails}
|
||||
/>
|
||||
{/if}
|
||||
</div>
|
||||
</HoverCard.Content>
|
||||
</HoverCard.Root>
|
||||
+20
@@ -0,0 +1,20 @@
|
||||
<script lang="ts">
|
||||
interface Props {
|
||||
label: string;
|
||||
value: string;
|
||||
subtitle?: string;
|
||||
}
|
||||
|
||||
let { label, value, subtitle }: Props = $props();
|
||||
</script>
|
||||
|
||||
<div class="grid gap-1.5">
|
||||
<div class="flex items-baseline justify-between">
|
||||
<span class="text-muted-foreground">{label}</span>
|
||||
<span class="font-mono text-muted-foreground">{value}</span>
|
||||
</div>
|
||||
|
||||
{#if subtitle}
|
||||
<div class="text-[10px] leading-tight text-muted-foreground/70">{subtitle}</div>
|
||||
{/if}
|
||||
</div>
|
||||
+122
@@ -0,0 +1,122 @@
|
||||
<script lang="ts">
|
||||
import { ChevronDown } from '@lucide/svelte';
|
||||
import * as Collapsible from '$lib/components/ui/collapsible';
|
||||
import { STATS_UNITS } from '$lib/constants';
|
||||
import ContextGaugeDetailRow from './ContextGaugeDetailRow.svelte';
|
||||
|
||||
interface Props {
|
||||
currentRead: number;
|
||||
currentFresh: number;
|
||||
currentCache: number;
|
||||
currentOutput: number;
|
||||
kvTotal: number;
|
||||
cumulativeRead: number;
|
||||
cumulativeOutput: number;
|
||||
cumulativeCacheTotal: number;
|
||||
averageTokensPerSecond: number | null;
|
||||
transientDetails: string[];
|
||||
}
|
||||
|
||||
let {
|
||||
currentRead,
|
||||
currentFresh,
|
||||
currentCache,
|
||||
currentOutput,
|
||||
kvTotal,
|
||||
cumulativeRead,
|
||||
cumulativeOutput,
|
||||
cumulativeCacheTotal,
|
||||
averageTokensPerSecond,
|
||||
transientDetails
|
||||
}: Props = $props();
|
||||
|
||||
let open = $state(false);
|
||||
|
||||
const hasCumulative = $derived(cumulativeRead > 0 || cumulativeOutput > 0);
|
||||
const hasCurrent = $derived(currentRead > 0 || currentOutput > 0);
|
||||
</script>
|
||||
|
||||
<Collapsible.Root bind:open class="mt-3 border-t border-border/50 pt-4">
|
||||
<Collapsible.Trigger
|
||||
class="flex w-full cursor-pointer items-center gap-1 text-xs text-muted-foreground hover:text-foreground"
|
||||
>
|
||||
<span>Token usage details</span>
|
||||
|
||||
<ChevronDown class={'ml-auto h-3 w-3 transition-transform' + (open ? ' rotate-180' : '')} />
|
||||
</Collapsible.Trigger>
|
||||
|
||||
<Collapsible.Content class="flex flex-col gap-4 text-xs pt-4">
|
||||
{#if hasCumulative}
|
||||
<div>
|
||||
<h3 class="text-[11px] font-medium uppercase tracking-wide text-muted-foreground/70 mb-2">
|
||||
Across all turns
|
||||
</h3>
|
||||
|
||||
<div class="flex flex-col gap-2">
|
||||
{#if cumulativeRead > 0}
|
||||
<ContextGaugeDetailRow
|
||||
label="Prompt tokens evaluated"
|
||||
value={`${cumulativeRead.toLocaleString()} tok`}
|
||||
subtitle={cumulativeCacheTotal > 0
|
||||
? `${cumulativeCacheTotal.toLocaleString()} reused from KV cache`
|
||||
: undefined}
|
||||
/>
|
||||
{/if}
|
||||
{#if cumulativeOutput > 0}
|
||||
<ContextGaugeDetailRow
|
||||
label="Tokens generated"
|
||||
value={`${cumulativeOutput.toLocaleString()} tok`}
|
||||
/>
|
||||
{/if}
|
||||
</div>
|
||||
</div>
|
||||
{/if}
|
||||
|
||||
{#if hasCurrent}
|
||||
<div>
|
||||
<h3 class="text-[11px] font-medium uppercase tracking-wide text-muted-foreground/70 mb-2">
|
||||
This turn · KV cache
|
||||
</h3>
|
||||
|
||||
<div class="flex flex-col gap-2">
|
||||
{#if currentRead > 0}
|
||||
<ContextGaugeDetailRow
|
||||
label="Prompt"
|
||||
value={`${currentRead.toLocaleString()} tok`}
|
||||
subtitle={currentCache > 0
|
||||
? `${currentFresh.toLocaleString()} fresh + ${currentCache.toLocaleString()} cached`
|
||||
: undefined}
|
||||
/>
|
||||
{/if}
|
||||
|
||||
{#if currentOutput > 0}
|
||||
<ContextGaugeDetailRow
|
||||
label="Generated"
|
||||
value={`${currentOutput.toLocaleString()} tok`}
|
||||
/>
|
||||
{/if}
|
||||
|
||||
<div class="pt-1 mt-0.5 border-t border-border/30">
|
||||
<div class="flex justify-between">
|
||||
<span class="text-muted-foreground">KV cache total</span>
|
||||
<span class="font-mono font-medium">{kvTotal.toLocaleString()} tok</span>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
{/if}
|
||||
|
||||
{#if averageTokensPerSecond !== null}
|
||||
<div class="pt-1.5 mt-1 border-t border-border/30">
|
||||
<ContextGaugeDetailRow
|
||||
label="Avg speed"
|
||||
value={`${averageTokensPerSecond.toFixed(1)}${STATS_UNITS.TOKENS_PER_SECOND}`}
|
||||
/>
|
||||
</div>
|
||||
{/if}
|
||||
|
||||
{#each transientDetails as detail (detail)}
|
||||
<div class="font-mono text-muted-foreground">{detail}</div>
|
||||
{/each}
|
||||
</Collapsible.Content>
|
||||
</Collapsible.Root>
|
||||
+43
@@ -0,0 +1,43 @@
|
||||
<script lang="ts">
|
||||
import type { ColorLevel } from './context-gauge';
|
||||
import { colorLevelTextClass } from './context-gauge';
|
||||
|
||||
interface Props {
|
||||
percent: number | null;
|
||||
level: ColorLevel;
|
||||
size?: 'sm' | 'md';
|
||||
}
|
||||
|
||||
let { percent, level, size = 'sm' }: Props = $props();
|
||||
|
||||
const RADIUS = 11;
|
||||
const CIRCUMFERENCE = 2 * Math.PI * RADIUS;
|
||||
|
||||
const strokeLevelClass = $derived(colorLevelTextClass(level));
|
||||
const dimensions = $derived(size === 'md' ? 'h-6 w-6' : 'h-5 w-5');
|
||||
const strokeWidth = $derived(size === 'md' ? 4 : 3);
|
||||
</script>
|
||||
|
||||
<svg viewBox="0 0 32 32" fill="none" class={dimensions}>
|
||||
<circle
|
||||
cx="16"
|
||||
cy="16"
|
||||
r={RADIUS}
|
||||
stroke="currentColor"
|
||||
stroke-opacity="0.1"
|
||||
stroke-width={strokeWidth}
|
||||
/>
|
||||
|
||||
<circle
|
||||
cx="16"
|
||||
cy="16"
|
||||
r={RADIUS}
|
||||
class="transition-colors duration-300 {strokeLevelClass}"
|
||||
stroke="currentColor"
|
||||
stroke-width={strokeWidth}
|
||||
stroke-linecap="round"
|
||||
stroke-dasharray={CIRCUMFERENCE}
|
||||
stroke-dashoffset={percent !== null ? CIRCUMFERENCE * (1 - percent / 100) : CIRCUMFERENCE}
|
||||
transform="rotate(-90 16 16)"
|
||||
/>
|
||||
</svg>
|
||||
+24
@@ -0,0 +1,24 @@
|
||||
<script lang="ts">
|
||||
import { Loader2 } from '@lucide/svelte';
|
||||
import { Button } from '$lib/components/ui/button';
|
||||
|
||||
interface Props {
|
||||
modelId: string | null;
|
||||
isLoading: boolean;
|
||||
onLoad: () => void;
|
||||
}
|
||||
|
||||
let { modelId, isLoading, onLoad }: Props = $props();
|
||||
</script>
|
||||
|
||||
{#if modelId !== null && !isLoading}
|
||||
<div class="flex flex-col gap-2 border-t border-border/50 pt-2 text-xs text-muted-foreground">
|
||||
<span>Available context size is only visible once the model is loaded.</span>
|
||||
<Button size="sm" variant="secondary" class="self-start" onclick={onLoad}>Load model</Button>
|
||||
</div>
|
||||
{:else if isLoading}
|
||||
<div class="flex items-center gap-2 border-t border-border/50 pt-2 text-xs text-muted-foreground">
|
||||
<Loader2 class="h-3.5 w-3.5 animate-spin" />
|
||||
<span>Loading model...</span>
|
||||
</div>
|
||||
{/if}
|
||||
@@ -0,0 +1,37 @@
|
||||
export type ColorLevel = 'ok' | 'warning' | 'critical' | 'neutral';
|
||||
|
||||
const WARNING_THRESHOLD = 80;
|
||||
const CRITICAL_THRESHOLD = 95;
|
||||
|
||||
export function colorLevelFromPercent(percent: number | null): ColorLevel {
|
||||
if (percent === null) return 'neutral';
|
||||
if (percent >= CRITICAL_THRESHOLD) return 'critical';
|
||||
if (percent >= WARNING_THRESHOLD) return 'warning';
|
||||
return 'ok';
|
||||
}
|
||||
|
||||
export function colorLevelTextClass(level: ColorLevel): string {
|
||||
switch (level) {
|
||||
case 'critical':
|
||||
return 'text-red-400';
|
||||
case 'warning':
|
||||
return 'text-amber-400';
|
||||
case 'ok':
|
||||
return 'text-muted-foreground';
|
||||
default:
|
||||
return 'text-muted-foreground';
|
||||
}
|
||||
}
|
||||
|
||||
export function colorLevelBgClass(level: ColorLevel): string {
|
||||
switch (level) {
|
||||
case 'critical':
|
||||
return 'bg-red-500';
|
||||
case 'warning':
|
||||
return 'bg-amber-500';
|
||||
case 'ok':
|
||||
return 'bg-green-500';
|
||||
default:
|
||||
return 'bg-muted';
|
||||
}
|
||||
}
|
||||
@@ -24,6 +24,8 @@
|
||||
message: DatabaseMessage;
|
||||
toolMessages?: DatabaseMessage[];
|
||||
isLastAssistantMessage?: boolean;
|
||||
isLastUserMessage?: boolean;
|
||||
nextAssistantMessage?: DatabaseMessage | null;
|
||||
siblingInfo?: ChatMessageSiblingInfo | null;
|
||||
}
|
||||
|
||||
@@ -32,6 +34,8 @@
|
||||
message,
|
||||
toolMessages = [],
|
||||
isLastAssistantMessage = false,
|
||||
isLastUserMessage = false,
|
||||
nextAssistantMessage = null,
|
||||
siblingInfo = null
|
||||
}: Props = $props();
|
||||
|
||||
@@ -359,7 +363,9 @@
|
||||
<ChatMessageUser
|
||||
class={className}
|
||||
{deletionInfo}
|
||||
{isLastUserMessage}
|
||||
{message}
|
||||
{nextAssistantMessage}
|
||||
onConfirmDelete={handleConfirmDelete}
|
||||
onCopy={handleCopy}
|
||||
onDelete={handleDelete}
|
||||
|
||||
+8
-72
@@ -11,11 +11,10 @@
|
||||
import { useProcessingState } from '$lib/hooks/use-processing-state.svelte';
|
||||
import { isLoading, isChatStreaming } from '$lib/stores/chat.svelte';
|
||||
import { copyToClipboard, deriveAgenticSections, modelLoadProgressText } from '$lib/utils';
|
||||
import { AgenticSectionType } from '$lib/enums';
|
||||
import { AgenticSectionType, ChatMessageStatisticsMode } from '$lib/enums';
|
||||
import { REASONING_TAGS } from '$lib/constants/agentic';
|
||||
import { tick } from 'svelte';
|
||||
import { fade } from 'svelte/transition';
|
||||
import { MessageRole, ChatMessageStatsView } from '$lib/enums';
|
||||
import { MessageRole } from '$lib/enums';
|
||||
import { config } from '$lib/stores/settings.svelte';
|
||||
import { isRouterMode } from '$lib/stores/server.svelte';
|
||||
import { modelsStore } from '$lib/stores/models.svelte';
|
||||
@@ -122,62 +121,6 @@
|
||||
return parts.join('\n\n\n');
|
||||
});
|
||||
|
||||
let activeStatsView = $state<ChatMessageStatsView>(ChatMessageStatsView.GENERATION);
|
||||
let statsContainerEl: HTMLDivElement | undefined = $state();
|
||||
|
||||
function getScrollParent(el: HTMLElement): HTMLElement | null {
|
||||
let parent = el.parentElement;
|
||||
while (parent) {
|
||||
const style = getComputedStyle(parent);
|
||||
if (/(auto|scroll)/.test(style.overflowY)) {
|
||||
return parent;
|
||||
}
|
||||
parent = parent.parentElement;
|
||||
}
|
||||
return null;
|
||||
}
|
||||
|
||||
async function handleStatsViewChange(view: ChatMessageStatsView) {
|
||||
const el = statsContainerEl;
|
||||
if (!el) {
|
||||
activeStatsView = view;
|
||||
|
||||
return;
|
||||
}
|
||||
|
||||
const scrollParent = getScrollParent(el);
|
||||
if (!scrollParent) {
|
||||
activeStatsView = view;
|
||||
|
||||
return;
|
||||
}
|
||||
|
||||
const yBefore = el.getBoundingClientRect().top;
|
||||
|
||||
activeStatsView = view;
|
||||
|
||||
await tick();
|
||||
|
||||
const delta = el.getBoundingClientRect().top - yBefore;
|
||||
if (delta !== 0) {
|
||||
scrollParent.scrollTop += delta;
|
||||
}
|
||||
|
||||
// Correct any drift after browser paint
|
||||
requestAnimationFrame(() => {
|
||||
const drift = el.getBoundingClientRect().top - yBefore;
|
||||
|
||||
if (Math.abs(drift) > 1) {
|
||||
scrollParent.scrollTop += drift;
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
let highlightAgenticTurns = $derived(
|
||||
isAgentic &&
|
||||
(currentConfig.alwaysShowAgenticTurns || activeStatsView === ChatMessageStatsView.SUMMARY)
|
||||
);
|
||||
|
||||
let displayedModel = $derived(message.model ?? null);
|
||||
|
||||
// model being switched to while it loads, so the selector bar tracks it
|
||||
@@ -291,7 +234,6 @@
|
||||
{toolMessages}
|
||||
isStreaming={isChatStreaming()}
|
||||
{isLastAssistantMessage}
|
||||
highlightTurns={highlightAgenticTurns}
|
||||
/>
|
||||
{/if}
|
||||
{:else}
|
||||
@@ -315,10 +257,7 @@
|
||||
|
||||
<div class="info my-6 grid gap-4 tabular-nums">
|
||||
{#if displayedModel}
|
||||
<div
|
||||
bind:this={statsContainerEl}
|
||||
class="inline-flex flex-wrap items-start gap-2 text-xs text-muted-foreground"
|
||||
>
|
||||
<div class="inline-flex flex-wrap items-start gap-2 text-xs text-muted-foreground">
|
||||
{#if isRouter}
|
||||
<ModelsSelectorDropdown
|
||||
currentModel={pendingModel ?? displayedModel}
|
||||
@@ -347,28 +286,25 @@
|
||||
{#if currentConfig.showMessageStats && message.timings && message.timings.predicted_n && message.timings.predicted_ms}
|
||||
{@const agentic = message.timings.agentic}
|
||||
<ChatMessageStatistics
|
||||
mode={ChatMessageStatisticsMode.GENERATION}
|
||||
promptTokens={agentic ? agentic.llm.prompt_n : message.timings.prompt_n}
|
||||
promptMs={agentic ? agentic.llm.prompt_ms : message.timings.prompt_ms}
|
||||
predictedTokens={agentic ? agentic.llm.predicted_n : message.timings.predicted_n}
|
||||
predictedMs={agentic ? agentic.llm.predicted_ms : message.timings.predicted_ms}
|
||||
agenticTimings={agentic}
|
||||
onActiveViewChange={handleStatsViewChange}
|
||||
/>
|
||||
{:else if isLoading() && currentConfig.showMessageStats}
|
||||
{@const liveStats = processingState.getLiveProcessingStats()}
|
||||
{@const genStats = processingState.getLiveGenerationStats()}
|
||||
{@const promptProgress = processingState.processingState?.promptProgress}
|
||||
{@const isStillProcessingPrompt =
|
||||
promptProgress && promptProgress.processed < promptProgress.total}
|
||||
|
||||
{#if liveStats || genStats}
|
||||
{#if genStats}
|
||||
<ChatMessageStatistics
|
||||
mode={ChatMessageStatisticsMode.GENERATION}
|
||||
isLive
|
||||
isProcessingPrompt={!!isStillProcessingPrompt}
|
||||
promptTokens={liveStats?.tokensProcessed}
|
||||
promptMs={liveStats?.timeMs}
|
||||
predictedTokens={genStats?.tokensGenerated}
|
||||
predictedMs={genStats?.timeMs}
|
||||
predictedTokens={genStats.tokensGenerated}
|
||||
predictedMs={genStats.timeMs}
|
||||
/>
|
||||
{/if}
|
||||
{/if}
|
||||
|
||||
+71
-1
@@ -2,10 +2,14 @@
|
||||
import {
|
||||
ChatMessageActionIcons,
|
||||
ChatMessageEditForm,
|
||||
ChatMessageStatistics,
|
||||
ChatMessageUserBubble
|
||||
} from '$lib/components/app/chat';
|
||||
import { getMessageEditContext } from '$lib/contexts';
|
||||
import { MessageRole } from '$lib/enums';
|
||||
import { useProcessingState } from '$lib/hooks/use-processing-state.svelte';
|
||||
import { isLoading } from '$lib/stores/chat.svelte';
|
||||
import { MessageRole, ChatMessageStatisticsMode } from '$lib/enums';
|
||||
import { config } from '$lib/stores/settings.svelte';
|
||||
|
||||
interface Props {
|
||||
class?: string;
|
||||
@@ -17,6 +21,8 @@
|
||||
assistantMessages: number;
|
||||
messageTypes: string[];
|
||||
} | null;
|
||||
isLastUserMessage?: boolean;
|
||||
nextAssistantMessage?: DatabaseMessage | null;
|
||||
showDeleteDialog: boolean;
|
||||
onEdit: () => void;
|
||||
onDelete: () => void;
|
||||
@@ -32,6 +38,8 @@
|
||||
message,
|
||||
siblingInfo = null,
|
||||
deletionInfo,
|
||||
isLastUserMessage = false,
|
||||
nextAssistantMessage = null,
|
||||
showDeleteDialog,
|
||||
onEdit,
|
||||
onDelete,
|
||||
@@ -44,6 +52,37 @@
|
||||
|
||||
// Get contexts
|
||||
const editCtx = getMessageEditContext();
|
||||
const processingState = useProcessingState();
|
||||
|
||||
const currentConfig = $derived(config());
|
||||
const isActivelyProcessing = $derived(isLastUserMessage && isLoading());
|
||||
|
||||
// For agentic turns, prefer the cumulative agentic.llm totals over per-call timings.
|
||||
let storedReadingStats = $derived.by(() => {
|
||||
const timings = nextAssistantMessage?.timings;
|
||||
if (!timings?.prompt_n || !timings?.prompt_ms) return null;
|
||||
|
||||
const agentic = timings.agentic;
|
||||
|
||||
return {
|
||||
promptTokens: agentic ? agentic.llm.prompt_n : timings.prompt_n,
|
||||
promptMs: agentic ? agentic.llm.prompt_ms : timings.prompt_ms
|
||||
};
|
||||
});
|
||||
|
||||
let showStoredReadingStats = $derived(
|
||||
Boolean(currentConfig.showMessageStats) && storedReadingStats !== null
|
||||
);
|
||||
|
||||
let showLiveReadingStats = $derived(
|
||||
Boolean(currentConfig.showMessageStats) && isActivelyProcessing && storedReadingStats === null
|
||||
);
|
||||
|
||||
$effect(() => {
|
||||
if (showLiveReadingStats) {
|
||||
processingState.startMonitoring();
|
||||
}
|
||||
});
|
||||
</script>
|
||||
|
||||
<div
|
||||
@@ -60,6 +99,37 @@
|
||||
renderMarkdown={true}
|
||||
/>
|
||||
|
||||
{#if showStoredReadingStats}
|
||||
<!-- Reading stats sourced from the assistant message that followed this turn -->
|
||||
<div class="info my-2 grid w-full justify-items-end gap-4 tabular-nums">
|
||||
<div
|
||||
class="inline-flex flex-wrap items-start justify-end gap-2 text-xs text-muted-foreground"
|
||||
>
|
||||
<ChatMessageStatistics
|
||||
mode={ChatMessageStatisticsMode.READING}
|
||||
promptTokens={storedReadingStats!.promptTokens}
|
||||
promptMs={storedReadingStats!.promptMs}
|
||||
/>
|
||||
</div>
|
||||
</div>
|
||||
{:else if showLiveReadingStats}
|
||||
{@const liveStats = processingState.getLiveProcessingStats()}
|
||||
{#if liveStats}
|
||||
<div class="info my-2 grid w-full justify-items-end gap-4 tabular-nums">
|
||||
<div
|
||||
class="inline-flex flex-wrap items-start justify-end gap-2 text-xs text-muted-foreground"
|
||||
>
|
||||
<ChatMessageStatistics
|
||||
mode={ChatMessageStatisticsMode.READING}
|
||||
isLive
|
||||
promptTokens={liveStats.tokensProcessed}
|
||||
promptMs={liveStats.timeMs}
|
||||
/>
|
||||
</div>
|
||||
</div>
|
||||
{/if}
|
||||
{/if}
|
||||
|
||||
{#if message.timestamp}
|
||||
<div class="max-w-[80%]">
|
||||
<ChatMessageActionIcons
|
||||
|
||||
+1
-7
@@ -2,7 +2,6 @@
|
||||
import { ActionIcon, ChatMessageEditForm, ChatMessageUserBubble } from '$lib/components/app';
|
||||
import { fadeInView } from '$lib/actions/fade-in-view.svelte';
|
||||
import { ArrowUp, Edit, Trash2 } from '@lucide/svelte';
|
||||
import { getProcessingInfoContext } from '$lib/contexts';
|
||||
import { useMessageEditContext } from '$lib/hooks/use-message-edit-context.svelte';
|
||||
|
||||
interface Props {
|
||||
@@ -23,9 +22,6 @@
|
||||
onDelete
|
||||
}: Props = $props();
|
||||
|
||||
const processingInfoCtx = getProcessingInfoContext();
|
||||
let showProcessingInfo = $derived(processingInfoCtx.showProcessingInfo);
|
||||
|
||||
const editCtx = useMessageEditContext({
|
||||
getContent: () => content,
|
||||
getExtras: () => extras,
|
||||
@@ -36,9 +32,7 @@
|
||||
<div
|
||||
use:fadeInView
|
||||
aria-label="Pending user message"
|
||||
class="group flex flex-col items-end gap-3 transition-opacity hover:opacity-80 md:gap-2 {className} sticky {showProcessingInfo
|
||||
? 'bottom-44'
|
||||
: 'bottom-32'}"
|
||||
class="group flex flex-col items-end gap-3 transition-opacity hover:opacity-80 md:gap-2 {className} sticky bottom-32"
|
||||
role="group"
|
||||
>
|
||||
{#if editCtx.isEditing}
|
||||
|
||||
+14
-32
@@ -41,15 +41,13 @@
|
||||
toolMessages?: DatabaseMessage[];
|
||||
isStreaming?: boolean;
|
||||
isLastAssistantMessage?: boolean;
|
||||
highlightTurns?: boolean;
|
||||
}
|
||||
|
||||
let {
|
||||
message,
|
||||
toolMessages = [],
|
||||
isStreaming = false,
|
||||
isLastAssistantMessage = false,
|
||||
highlightTurns = false
|
||||
isLastAssistantMessage = false
|
||||
}: Props = $props();
|
||||
|
||||
let expandedStates: Record<number, boolean> = $state({});
|
||||
@@ -57,6 +55,7 @@
|
||||
const showToolCallInProgress = $derived(config().showToolCallInProgress as boolean);
|
||||
const showThoughtInProgress = $derived(config().showThoughtInProgress as boolean);
|
||||
const renderThinkingAsMarkdown = $derived(config().renderThinkingAsMarkdown as boolean);
|
||||
const showMessageStats = $derived(config().showMessageStats as boolean);
|
||||
|
||||
const hasReasoningError = $derived(
|
||||
isLastAssistantMessage ? !!agenticLastError(message.convId) : false
|
||||
@@ -354,16 +353,17 @@
|
||||
{/snippet}
|
||||
|
||||
<div class="agentic-content">
|
||||
{#if highlightTurns && turnGroups.length > 1}
|
||||
{#if turnGroups.length > 1}
|
||||
{#each turnGroups as turn, turnIndex (turnIndex)}
|
||||
{@const turnStats = message?.timings?.agentic?.perTurn?.[turnIndex]}
|
||||
<div class="agentic-turn my-2 hover:bg-muted/80 dark:hover:bg-muted/30">
|
||||
<span class="agentic-turn-label">Turn {turnIndex + 1}</span>
|
||||
|
||||
<div class="agentic-turn group/turn grid gap-3 mb-4">
|
||||
{#each turn.sections as section, sIdx (turn.flatIndices[sIdx])}
|
||||
{@render renderSection(section, turn.flatIndices[sIdx])}
|
||||
{/each}
|
||||
{#if turnStats}
|
||||
<div class="turn-stats">
|
||||
|
||||
{#if turnStats && showMessageStats}
|
||||
<div class="turn-stats transition-opacity duration-150">
|
||||
<ChatMessageStatistics
|
||||
promptTokens={turnStats.llm.prompt_n}
|
||||
promptMs={turnStats.llm.prompt_ms}
|
||||
@@ -402,39 +402,21 @@
|
||||
.agentic-content {
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
gap: 0.5rem;
|
||||
width: 100%;
|
||||
max-width: 48rem;
|
||||
gap: 1rem;
|
||||
}
|
||||
|
||||
.agentic-content > :global(*),
|
||||
.agentic-turn > :global(*) {
|
||||
min-width: 0;
|
||||
}
|
||||
|
||||
.agentic-text {
|
||||
width: 100%;
|
||||
}
|
||||
|
||||
.agentic-turn {
|
||||
position: relative;
|
||||
border: 1.5px dashed var(--muted-foreground);
|
||||
border-radius: 0.75rem;
|
||||
padding: 1rem;
|
||||
transition: background 0.1s;
|
||||
}
|
||||
|
||||
.agentic-turn-label {
|
||||
position: absolute;
|
||||
top: -1rem;
|
||||
left: 0.75rem;
|
||||
padding: 0 0.375rem;
|
||||
background: var(--background);
|
||||
font-size: 0.7rem;
|
||||
font-weight: 500;
|
||||
color: var(--muted-foreground);
|
||||
text-transform: uppercase;
|
||||
letter-spacing: 0.05em;
|
||||
}
|
||||
|
||||
.turn-stats {
|
||||
margin-top: 0.75rem;
|
||||
padding-top: 0.5rem;
|
||||
border-top: 1px solid hsl(var(--muted) / 0.5);
|
||||
}
|
||||
</style>
|
||||
|
||||
+54
-43
@@ -2,7 +2,7 @@
|
||||
import { Clock, Gauge, WholeWord, BookOpenText, Sparkles, Wrench, Layers } from '@lucide/svelte';
|
||||
import { ChatMessageStatisticsBadge } from '$lib/components/app';
|
||||
import * as Tooltip from '$lib/components/ui/tooltip';
|
||||
import { ChatMessageStatsView } from '$lib/enums';
|
||||
import { ChatMessageStatsView, ChatMessageStatisticsMode } from '$lib/enums';
|
||||
import type { ChatMessageAgenticTimings } from '$lib/types/chat';
|
||||
import { formatPerformanceTime } from '$lib/utils';
|
||||
import { MS_PER_SECOND, DEFAULT_PERFORMANCE_TIME } from '$lib/constants';
|
||||
@@ -19,6 +19,7 @@
|
||||
agenticTimings?: ChatMessageAgenticTimings;
|
||||
onActiveViewChange?: (view: ChatMessageStatsView) => void;
|
||||
hideSummary?: boolean;
|
||||
mode?: ChatMessageStatisticsMode;
|
||||
}
|
||||
|
||||
let {
|
||||
@@ -31,19 +32,30 @@
|
||||
initialView = ChatMessageStatsView.GENERATION,
|
||||
agenticTimings,
|
||||
onActiveViewChange,
|
||||
hideSummary = false
|
||||
hideSummary = false,
|
||||
mode = ChatMessageStatisticsMode.SWITCHABLE
|
||||
}: Props = $props();
|
||||
|
||||
let activeView: ChatMessageStatsView = $derived(initialView);
|
||||
let isSwitchable = $derived(mode === ChatMessageStatisticsMode.SWITCHABLE);
|
||||
|
||||
let activeView: ChatMessageStatsView = $derived(
|
||||
mode === ChatMessageStatisticsMode.READING
|
||||
? ChatMessageStatsView.READING
|
||||
: mode === ChatMessageStatisticsMode.GENERATION
|
||||
? ChatMessageStatsView.GENERATION
|
||||
: initialView
|
||||
);
|
||||
let hasAutoSwitchedToGeneration = $state(false);
|
||||
|
||||
$effect(() => {
|
||||
onActiveViewChange?.(activeView);
|
||||
if (isSwitchable) {
|
||||
onActiveViewChange?.(activeView);
|
||||
}
|
||||
});
|
||||
|
||||
// In live mode: auto-switch to GENERATION tab when prompt processing completes
|
||||
$effect(() => {
|
||||
if (isLive) {
|
||||
if (isLive && isSwitchable) {
|
||||
// Auto-switch to generation tab only when prompt processing is done (once)
|
||||
if (
|
||||
!hasAutoSwitchedToGeneration &&
|
||||
@@ -91,8 +103,7 @@
|
||||
formattedPromptTime !== undefined
|
||||
);
|
||||
|
||||
// In live mode, generation tab is disabled until we have generation stats
|
||||
let isGenerationDisabled = $derived(isLive && !hasGenerationStats);
|
||||
let isGenerationDisabled = $derived(isLive && isSwitchable && !hasGenerationStats);
|
||||
|
||||
let hasAgenticStats = $derived(agenticTimings !== undefined && agenticTimings.toolCallsCount > 0);
|
||||
|
||||
@@ -153,44 +164,44 @@
|
||||
{/snippet}
|
||||
|
||||
<div class="inline-flex items-center text-xs text-muted-foreground">
|
||||
<div class="inline-flex items-center rounded-sm bg-muted-foreground/15 p-0.5">
|
||||
{#if hasPromptStats || isLive}
|
||||
{@render viewButton({
|
||||
view: ChatMessageStatsView.READING,
|
||||
icon: BookOpenText,
|
||||
label: 'Reading',
|
||||
tooltipText: 'Reading (prompt processing)'
|
||||
})}
|
||||
{/if}
|
||||
|
||||
{@render viewButton({
|
||||
view: ChatMessageStatsView.GENERATION,
|
||||
icon: Sparkles,
|
||||
label: 'Generation',
|
||||
tooltipText: isGenerationDisabled
|
||||
? 'Generation (waiting for tokens...)'
|
||||
: 'Generation (token output)',
|
||||
disabled: isGenerationDisabled
|
||||
})}
|
||||
|
||||
{#if hasAgenticStats}
|
||||
{@render viewButton({
|
||||
view: ChatMessageStatsView.TOOLS,
|
||||
icon: Wrench,
|
||||
label: 'Tools',
|
||||
tooltipText: 'Tool calls'
|
||||
})}
|
||||
|
||||
{#if !hideSummary}
|
||||
{#if isSwitchable}
|
||||
<div class="inline-flex items-center rounded-sm bg-muted-foreground/15 p-0.5">
|
||||
{#if hasPromptStats || isLive}
|
||||
{@render viewButton({
|
||||
view: ChatMessageStatsView.SUMMARY,
|
||||
icon: Layers,
|
||||
label: 'Summary',
|
||||
tooltipText: 'Agentic summary'
|
||||
view: ChatMessageStatsView.READING,
|
||||
icon: BookOpenText,
|
||||
label: 'Reading',
|
||||
tooltipText: 'Processing'
|
||||
})}
|
||||
{/if}
|
||||
{/if}
|
||||
</div>
|
||||
|
||||
{@render viewButton({
|
||||
view: ChatMessageStatsView.GENERATION,
|
||||
icon: Sparkles,
|
||||
label: 'Generation',
|
||||
tooltipText: isGenerationDisabled ? 'Waiting for tokens...' : 'Generation',
|
||||
disabled: isGenerationDisabled
|
||||
})}
|
||||
|
||||
{#if hasAgenticStats}
|
||||
{@render viewButton({
|
||||
view: ChatMessageStatsView.TOOLS,
|
||||
icon: Wrench,
|
||||
label: 'Tools',
|
||||
tooltipText: 'Tool calls'
|
||||
})}
|
||||
|
||||
{#if !hideSummary}
|
||||
{@render viewButton({
|
||||
view: ChatMessageStatsView.SUMMARY,
|
||||
icon: Layers,
|
||||
label: 'Summary',
|
||||
tooltipText: 'Agentic summary'
|
||||
})}
|
||||
{/if}
|
||||
{/if}
|
||||
</div>
|
||||
{/if}
|
||||
|
||||
<div class="flex items-center gap-1 px-2">
|
||||
{#if activeView === ChatMessageStatsView.GENERATION && hasGenerationStats}
|
||||
@@ -256,7 +267,7 @@
|
||||
value={formattedAgenticTotalTime}
|
||||
tooltipLabel="Total time (LLM + tools)"
|
||||
/>
|
||||
{:else if hasPromptStats}
|
||||
{:else if hasPromptStats && (mode === ChatMessageStatisticsMode.READING || isSwitchable)}
|
||||
<ChatMessageStatisticsBadge
|
||||
class="bg-transparent"
|
||||
icon={WholeWord}
|
||||
|
||||
@@ -186,6 +186,8 @@
|
||||
message: DatabaseMessage;
|
||||
toolMessages: DatabaseMessage[];
|
||||
isLastAssistantMessage: boolean;
|
||||
isLastUserMessage: boolean;
|
||||
nextAssistantMessage: DatabaseMessage | null;
|
||||
siblingInfo: ChatMessageSiblingInfo;
|
||||
}> = [];
|
||||
|
||||
@@ -236,18 +238,36 @@
|
||||
message: msg,
|
||||
toolMessages,
|
||||
isLastAssistantMessage: false,
|
||||
isLastUserMessage: false,
|
||||
nextAssistantMessage: null,
|
||||
siblingInfo
|
||||
});
|
||||
}
|
||||
|
||||
// Mark the last assistant message
|
||||
let lastAssistantIdx = -1;
|
||||
for (let i = result.length - 1; i >= 0; i--) {
|
||||
if (result[i].message.role === MessageRole.ASSISTANT) {
|
||||
result[i].isLastAssistantMessage = true;
|
||||
lastAssistantIdx = i;
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
if (lastAssistantIdx > 0 && result[lastAssistantIdx - 1].message.role === MessageRole.USER) {
|
||||
result[lastAssistantIdx - 1].isLastUserMessage = true;
|
||||
}
|
||||
|
||||
for (let i = 0; i < result.length; i++) {
|
||||
if (result[i].message.role !== MessageRole.USER) continue;
|
||||
|
||||
for (let j = i + 1; j < result.length; j++) {
|
||||
if (result[j].message.role === MessageRole.ASSISTANT) {
|
||||
result[i].nextAssistantMessage = result[j].message;
|
||||
break;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
return result;
|
||||
});
|
||||
</script>
|
||||
@@ -257,12 +277,14 @@
|
||||
{isVisible ? 'opacity-100' : 'opacity-0'}
|
||||
{previousRouteId === '/(chat)/chat/[id]' ? '' : 'delay-300'}"
|
||||
>
|
||||
{#each displayMessages as { message, toolMessages, isLastAssistantMessage, siblingInfo } (message.id)}
|
||||
{#each displayMessages as { message, toolMessages, isLastAssistantMessage, isLastUserMessage, nextAssistantMessage, siblingInfo } (message.id)}
|
||||
<ChatMessage
|
||||
class="mx-auto mt-12 w-full max-w-3xl"
|
||||
{message}
|
||||
{toolMessages}
|
||||
{isLastAssistantMessage}
|
||||
{isLastUserMessage}
|
||||
{nextAssistantMessage}
|
||||
{siblingInfo}
|
||||
/>
|
||||
{/each}
|
||||
|
||||
@@ -4,12 +4,10 @@
|
||||
ChatScreenForm,
|
||||
ChatMessages,
|
||||
ChatScreenDragOverlay,
|
||||
ChatScreenProcessingInfo,
|
||||
ChatScreenStreamResumeStatus,
|
||||
ServerLoadingSplash,
|
||||
ChatScreenServerError
|
||||
} from '$lib/components/app';
|
||||
import { setProcessingInfoContext } from '$lib/contexts';
|
||||
import { createAutoScrollController } from '$lib/hooks/use-auto-scroll.svelte';
|
||||
import { useChatScreenActiveModel } from '$lib/hooks/use-chat-screen-active-model.svelte';
|
||||
import { useChatScreenDragAndDrop } from '$lib/hooks/use-chat-screen-drag-and-drop.svelte';
|
||||
@@ -23,8 +21,7 @@
|
||||
errorDialog,
|
||||
isLoading,
|
||||
isChatStreaming,
|
||||
isEditing,
|
||||
activeProcessingState
|
||||
isEditing
|
||||
} from '$lib/stores/chat.svelte';
|
||||
import {
|
||||
conversationsStore,
|
||||
@@ -42,12 +39,6 @@
|
||||
|
||||
let { showCenteredEmpty = false } = $props();
|
||||
|
||||
setProcessingInfoContext({
|
||||
get showProcessingInfo() {
|
||||
return showProcessingInfo;
|
||||
}
|
||||
});
|
||||
|
||||
let disableAutoScroll = $derived(Boolean(config().disableAutoScroll) || isMobile.current);
|
||||
let isMobileUserScrolledUp = $state(false);
|
||||
let mobileScrollDownHint = $state(false);
|
||||
@@ -63,11 +54,6 @@
|
||||
let isServerLoading = $derived(serverLoading());
|
||||
let hasPropsError = $derived(!!serverError());
|
||||
let isCurrentConversationLoading = $derived(isLoading() || isChatStreaming());
|
||||
let showProcessingInfo = $derived(
|
||||
isCurrentConversationLoading ||
|
||||
(config().keepStatsVisible && !!page.params.id) ||
|
||||
activeProcessingState() !== null
|
||||
);
|
||||
let chatFormBottomPosition = $derived.by(() => {
|
||||
if (!isMobile.current) return '1rem';
|
||||
if (device.isStandalone) return '1.5rem';
|
||||
@@ -298,10 +284,6 @@
|
||||
}}
|
||||
/>
|
||||
{/if}
|
||||
|
||||
{#if showProcessingInfo}
|
||||
<ChatScreenProcessingInfo />
|
||||
{/if}
|
||||
</div>
|
||||
|
||||
<ChatScreenForm
|
||||
|
||||
@@ -1,127 +0,0 @@
|
||||
<script lang="ts">
|
||||
import { untrack } from 'svelte';
|
||||
import { PROCESSING_INFO_TIMEOUT } from '$lib/constants';
|
||||
import { useProcessingState } from '$lib/hooks/use-processing-state.svelte';
|
||||
import { chatStore, isLoading, isChatStreaming } from '$lib/stores/chat.svelte';
|
||||
import { activeMessages, activeConversation } from '$lib/stores/conversations.svelte';
|
||||
import { config } from '$lib/stores/settings.svelte';
|
||||
|
||||
const processingState = useProcessingState();
|
||||
|
||||
let isCurrentConversationLoading = $derived(isLoading());
|
||||
let isStreaming = $derived(isChatStreaming());
|
||||
let processingDetails = $derived(processingState.getTechnicalDetails());
|
||||
|
||||
let processingVisible = $derived(processingDetails.length > 0);
|
||||
|
||||
let { onVisibilityChange }: { onVisibilityChange?: (visible: boolean) => void } = $props();
|
||||
|
||||
$effect(() => {
|
||||
onVisibilityChange?.(processingVisible);
|
||||
});
|
||||
|
||||
$effect(() => {
|
||||
const conversation = activeConversation();
|
||||
|
||||
untrack(() => chatStore.setActiveProcessingConversation(conversation?.id ?? null));
|
||||
});
|
||||
|
||||
$effect(() => {
|
||||
const keepStatsVisible = config().keepStatsVisible;
|
||||
const shouldMonitor = keepStatsVisible || isCurrentConversationLoading || isStreaming;
|
||||
|
||||
if (shouldMonitor) {
|
||||
processingState.startMonitoring();
|
||||
}
|
||||
|
||||
if (!isCurrentConversationLoading && !isStreaming && !keepStatsVisible) {
|
||||
const timeout = setTimeout(() => {
|
||||
if (!config().keepStatsVisible && !isChatStreaming()) {
|
||||
processingState.stopMonitoring();
|
||||
}
|
||||
}, PROCESSING_INFO_TIMEOUT);
|
||||
|
||||
return () => clearTimeout(timeout);
|
||||
}
|
||||
});
|
||||
|
||||
$effect(() => {
|
||||
const conversation = activeConversation();
|
||||
const messages = activeMessages() as DatabaseMessage[];
|
||||
const keepStatsVisible = config().keepStatsVisible;
|
||||
|
||||
if (keepStatsVisible && conversation) {
|
||||
if (messages.length === 0) {
|
||||
untrack(() => chatStore.clearProcessingState(conversation.id));
|
||||
return;
|
||||
}
|
||||
|
||||
if (!isCurrentConversationLoading && !isStreaming) {
|
||||
untrack(() => chatStore.restoreProcessingStateFromMessages(messages, conversation.id));
|
||||
}
|
||||
}
|
||||
});
|
||||
</script>
|
||||
|
||||
<div
|
||||
class={[
|
||||
'chat-processing-info-container pointer-events-none relative w-full hidden md:block',
|
||||
processingVisible && 'visible'
|
||||
]}
|
||||
>
|
||||
<div class="chat-processing-info-content absolute bottom-4 left-1/2 -translate-x-1/2">
|
||||
{#each processingDetails as detail (detail)}
|
||||
<span class="chat-processing-info-detail pointer-events-auto backdrop-blur-sm">{detail}</span>
|
||||
{/each}
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<style>
|
||||
.chat-processing-info-container {
|
||||
position: sticky;
|
||||
top: 0;
|
||||
z-index: 10;
|
||||
padding: 0 1rem 0.75rem;
|
||||
opacity: 0;
|
||||
transform: translateY(50%);
|
||||
transition:
|
||||
opacity 300ms ease-out,
|
||||
transform 300ms ease-out;
|
||||
}
|
||||
|
||||
.chat-processing-info-container.visible {
|
||||
opacity: 1;
|
||||
transform: translateY(0);
|
||||
}
|
||||
|
||||
.chat-processing-info-content {
|
||||
display: flex;
|
||||
flex-wrap: wrap;
|
||||
align-items: center;
|
||||
gap: 1rem;
|
||||
justify-content: center;
|
||||
max-width: 48rem;
|
||||
margin: 0 auto;
|
||||
}
|
||||
|
||||
.chat-processing-info-detail {
|
||||
color: var(--muted-foreground);
|
||||
font-size: 0.75rem;
|
||||
padding: 0.25rem 0.75rem;
|
||||
border-radius: 0.375rem;
|
||||
font-family:
|
||||
ui-monospace, SFMono-Regular, 'SF Mono', Consolas, 'Liberation Mono', Menlo, monospace;
|
||||
white-space: nowrap;
|
||||
}
|
||||
|
||||
@media (max-width: 768px) {
|
||||
.chat-processing-info-content {
|
||||
gap: 0.5rem;
|
||||
}
|
||||
|
||||
.chat-processing-info-detail {
|
||||
font-size: 0.7rem;
|
||||
padding: 0.2rem 0.5rem;
|
||||
}
|
||||
}
|
||||
</style>
|
||||
@@ -241,13 +241,18 @@ export { default as ChatFormActionAddToolsSubmenu } from './ChatForm/ChatFormAct
|
||||
export { default as ChatFormActionAddMcpServersSubmenu } from './ChatForm/ChatFormActions/ChatFormActionAdd/ChatFormActionAddMcpServersSubmenu.svelte';
|
||||
|
||||
/**
|
||||
* **ChatFormReasoningToggle** - Thinking toggle button with effort dropdown
|
||||
* Dropdown submenu for selecting reasoning effort level.
|
||||
*
|
||||
* A toggle button with lightbulb icon that indicates thinking status.
|
||||
* Shows the reasoning effort dropdown when clicked.
|
||||
* Shows a "Reasoning" sub-menu item with a lightbulb icon indicating
|
||||
* thinking status, and a nested list of effort levels.
|
||||
* Only visible when the current model supports thinking.
|
||||
*/
|
||||
export { default as ChatFormReasoningToggle } from './ChatForm/ChatFormActions/ChatFormReasoningToggle.svelte';
|
||||
export { default as ChatFormActionAddReasoningSubmenu } from './ChatForm/ChatFormActions/ChatFormActionAdd/ChatFormActionAddReasoningSubmenu.svelte';
|
||||
|
||||
/**
|
||||
* Compact context-usage gauge with per-turn and cumulative breakdown in the tooltip.
|
||||
*/
|
||||
export { default as ChatFormContextGauge } from './ChatForm/ChatFormContextGauge/ChatFormContextGauge.svelte';
|
||||
|
||||
/**
|
||||
* Hidden file input element for programmatic file selection.
|
||||
@@ -669,14 +674,6 @@ export { default as ChatScreenDragOverlay } from './ChatScreen/ChatScreenDragOve
|
||||
*/
|
||||
export { default as ChatScreenForm } from './ChatScreen/ChatScreenForm.svelte';
|
||||
|
||||
/**
|
||||
* Processing info display during generation. Shows real-time statistics:
|
||||
* tokens per second, prompt/completion token counts, and elapsed time.
|
||||
* Data sourced from slotsService polling during active generation.
|
||||
* Only visible when `isCurrentConversationLoading` is true.
|
||||
*/
|
||||
export { default as ChatScreenProcessingInfo } from './ChatScreen/ChatScreenProcessingInfo.svelte';
|
||||
|
||||
/**
|
||||
* Server error alert displayed when the server is unreachable.
|
||||
* Shows the error message with a retry button.
|
||||
|
||||
@@ -76,7 +76,7 @@
|
||||
open = value;
|
||||
onToggle?.();
|
||||
}}
|
||||
class={className}
|
||||
class="{className} my-0!"
|
||||
>
|
||||
<Card class="gap-0 border-muted bg-muted/30 py-0">
|
||||
<Collapsible.Trigger class="flex w-full cursor-pointer items-start justify-between gap-2 p-3">
|
||||
|
||||
@@ -72,8 +72,8 @@
|
||||
</script>
|
||||
|
||||
<div
|
||||
class="code-preview-wrapper rounded-lg border border-border bg-muted {className}"
|
||||
style="max-height: {maxHeight}; max-width: {maxWidth};"
|
||||
class="code-preview-wrapper min-w-0 max-w-full overflow-x-auto rounded-lg border border-border bg-muted {className}"
|
||||
style="max-height: {maxHeight}; {maxWidth ? `max-width: ${maxWidth};` : ''}"
|
||||
>
|
||||
<!-- Needs to be formatted as single line for proper rendering -->
|
||||
<pre class="m-0"><code class="hljs text-sm leading-relaxed">{@html highlightedHtml}</code></pre>
|
||||
|
||||
@@ -4,9 +4,10 @@
|
||||
import * as Dialog from '$lib/components/ui/dialog';
|
||||
import { fly } from 'svelte/transition';
|
||||
import { McpServerCardCompact, McpServerForm } from '$lib/components/app/mcp';
|
||||
import { RECOMMENDED_MCP_SERVERS } from '$lib/constants';
|
||||
import { RECOMMENDED_MCP_SERVERS, SETTINGS_KEYS } from '$lib/constants';
|
||||
import { conversationsStore } from '$lib/stores/conversations.svelte';
|
||||
import { mcpStore } from '$lib/stores/mcp.svelte';
|
||||
import { settingsStore } from '$lib/stores/settings.svelte';
|
||||
import { uuid } from '$lib/utils';
|
||||
import { MCP_SERVERS_ADDED_TO_CHAT_LOCALSTORAGE_KEY, MCP_SERVER_ID_PREFIX } from '$lib/constants';
|
||||
import type { MCPServerSettingsEntry } from '$lib/types';
|
||||
@@ -24,6 +25,22 @@
|
||||
);
|
||||
|
||||
let addedServers = $state<MCPServerSettingsEntry[]>([]);
|
||||
let didAddAny = $state(false);
|
||||
|
||||
let selectedRecommendedCount = $derived.by(
|
||||
() => RECOMMENDED_MCP_SERVERS.filter((server) => selected[server.id]).length
|
||||
);
|
||||
|
||||
let footerLabel = $derived.by(() => {
|
||||
const recommended = selectedRecommendedCount;
|
||||
const custom = addedServers.length;
|
||||
const total = recommended + custom;
|
||||
|
||||
if (total === 0) return 'Continue';
|
||||
if (recommended === 0) return custom === 1 ? 'Add server' : `Add ${custom} servers`;
|
||||
if (custom === 0) return recommended === 1 ? 'Add server' : `Add ${recommended} servers`;
|
||||
return `Add ${recommended} servers and ${custom} custom`;
|
||||
});
|
||||
|
||||
let showAddForm = $state(false);
|
||||
let newServerUrl = $state('');
|
||||
@@ -44,9 +61,14 @@
|
||||
showAddForm = false;
|
||||
newServerUrl = '';
|
||||
newServerHeaders = '';
|
||||
addedServers = [];
|
||||
|
||||
if (!didAddAny) {
|
||||
settingsStore.updateConfig(SETTINGS_KEYS.MCP_SERVERS, []);
|
||||
}
|
||||
|
||||
localStorage.setItem(MCP_SERVERS_ADDED_TO_CHAT_LOCALSTORAGE_KEY, 'true');
|
||||
addedServers = [];
|
||||
didAddAny = false;
|
||||
}
|
||||
open = value;
|
||||
onOpenChange?.(value);
|
||||
@@ -59,6 +81,7 @@
|
||||
}
|
||||
|
||||
function enableSelected() {
|
||||
didAddAny = true;
|
||||
localStorage.setItem(MCP_SERVERS_ADDED_TO_CHAT_LOCALSTORAGE_KEY, 'true');
|
||||
|
||||
for (const server of RECOMMENDED_MCP_SERVERS) {
|
||||
@@ -83,6 +106,8 @@
|
||||
function saveNewServer() {
|
||||
if (newServerUrlError) return;
|
||||
|
||||
didAddAny = true;
|
||||
|
||||
const newServerId = uuid() ?? `${MCP_SERVER_ID_PREFIX}-${Date.now()}`;
|
||||
|
||||
localStorage.setItem(MCP_SERVERS_ADDED_TO_CHAT_LOCALSTORAGE_KEY, 'true');
|
||||
@@ -174,7 +199,12 @@
|
||||
<Dialog.Footer>
|
||||
<Button variant="secondary" size="sm" onclick={() => handleOpenChange(false)}>Not now</Button>
|
||||
|
||||
<Button variant="default" size="sm" onclick={enableSelected}>Add selected</Button>
|
||||
<Button
|
||||
variant="default"
|
||||
size="sm"
|
||||
onclick={enableSelected}
|
||||
disabled={footerLabel === 'Continue'}>{footerLabel}</Button
|
||||
>
|
||||
</Dialog.Footer>
|
||||
</Dialog.Content>
|
||||
</Dialog.Root>
|
||||
|
||||
@@ -39,13 +39,17 @@
|
||||
{@const faviconUrl = group.serverId ? mcpStore.getServerFavicon(group.serverId) : null}
|
||||
|
||||
<span class="inline-flex min-w-0 items-center gap-1.5 font-medium">
|
||||
<McpServerIdentity
|
||||
iconClass="h-4 w-4"
|
||||
iconRounded="rounded-sm"
|
||||
showVersion={false}
|
||||
displayName={group.label}
|
||||
{faviconUrl}
|
||||
/>
|
||||
{#if group.source === 'mcp'}
|
||||
<McpServerIdentity
|
||||
iconClass="h-4 w-4"
|
||||
iconRounded="rounded-sm"
|
||||
showVersion={false}
|
||||
displayName={group.label}
|
||||
{faviconUrl}
|
||||
/>
|
||||
{:else}
|
||||
<TruncatedText text={group.label} class="font-medium" />
|
||||
{/if}
|
||||
</span>
|
||||
|
||||
<span class="ml-auto shrink-0 text-xs text-muted-foreground">
|
||||
|
||||
@@ -0,0 +1,31 @@
|
||||
<script lang="ts">
|
||||
import { LinkPreview as HoverCardPrimitive } from 'bits-ui';
|
||||
import { cn, type WithoutChildrenOrChild } from '$lib/components/ui/utils.js';
|
||||
import HoverCardPortal from './hover-card-portal.svelte';
|
||||
import type { ComponentProps } from 'svelte';
|
||||
|
||||
let {
|
||||
ref = $bindable(null),
|
||||
class: className,
|
||||
align = 'center',
|
||||
sideOffset = 4,
|
||||
portalProps,
|
||||
...restProps
|
||||
}: HoverCardPrimitive.ContentProps & {
|
||||
portalProps?: WithoutChildrenOrChild<ComponentProps<typeof HoverCardPortal>>;
|
||||
} = $props();
|
||||
</script>
|
||||
|
||||
<HoverCardPortal {...portalProps}>
|
||||
<HoverCardPrimitive.Content
|
||||
bind:ref
|
||||
data-slot="hover-card-content"
|
||||
{align}
|
||||
{sideOffset}
|
||||
class={cn(
|
||||
'data-open:animate-in data-closed:animate-out data-closed:fade-out-0 data-open:fade-in-0 data-closed:zoom-out-95 data-open:zoom-in-95 data-[side=bottom]:slide-in-from-top-2 data-[side=left]:slide-in-from-right-2 data-[side=right]:slide-in-from-left-2 data-[side=top]:slide-in-from-bottom-2 ring-foreground/10 bg-popover text-popover-foreground w-64 rounded-lg p-2.5 text-sm shadow-md ring-1 duration-100 z-50 origin-(--transform-origin) outline-hidden',
|
||||
className
|
||||
)}
|
||||
{...restProps}
|
||||
/>
|
||||
</HoverCardPortal>
|
||||
@@ -0,0 +1,7 @@
|
||||
<script lang="ts">
|
||||
import { LinkPreview as HoverCardPrimitive } from 'bits-ui';
|
||||
|
||||
let { ...restProps }: HoverCardPrimitive.PortalProps = $props();
|
||||
</script>
|
||||
|
||||
<HoverCardPrimitive.Portal {...restProps} />
|
||||
@@ -0,0 +1,7 @@
|
||||
<script lang="ts">
|
||||
import { LinkPreview as HoverCardPrimitive } from 'bits-ui';
|
||||
|
||||
let { ref = $bindable(null), ...restProps }: HoverCardPrimitive.TriggerProps = $props();
|
||||
</script>
|
||||
|
||||
<HoverCardPrimitive.Trigger bind:ref data-slot="hover-card-trigger" {...restProps} />
|
||||
@@ -0,0 +1,7 @@
|
||||
<script lang="ts">
|
||||
import { LinkPreview as HoverCardPrimitive } from 'bits-ui';
|
||||
|
||||
let { open = $bindable(false), ...restProps }: HoverCardPrimitive.RootProps = $props();
|
||||
</script>
|
||||
|
||||
<HoverCardPrimitive.Root bind:open {...restProps} />
|
||||
@@ -0,0 +1,15 @@
|
||||
import Root from './hover-card.svelte';
|
||||
import Content from './hover-card-content.svelte';
|
||||
import Trigger from './hover-card-trigger.svelte';
|
||||
import Portal from './hover-card-portal.svelte';
|
||||
|
||||
export {
|
||||
Root,
|
||||
Content,
|
||||
Trigger,
|
||||
Portal,
|
||||
Root as HoverCard,
|
||||
Content as HoverCardContent,
|
||||
Trigger as HoverCardTrigger,
|
||||
Portal as HoverCardPortal
|
||||
};
|
||||
@@ -1,4 +1,3 @@
|
||||
export const CONTEXT_KEY_MESSAGE_EDIT = 'chat-message-edit';
|
||||
export const CONTEXT_KEY_CHAT_ACTIONS = 'chat-actions';
|
||||
export const CONTEXT_KEY_CHAT_SETTINGS_CONFIG = 'chat-settings-config';
|
||||
export const CONTEXT_KEY_PROCESSING_INFO = 'processing-info';
|
||||
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user