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Merge branch 'master' into concedo_experimental

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# Conflicts:
#	CMakeLists.txt
#	Makefile
#	README.md
This commit is contained in:
Concedo
2023-05-03 23:34:50 +08:00
parent 105f818d45 b0c71c7b6d
commit ede8e4edbb
19 changed files with 435 additions and 177 deletions
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examples/Miku.sh
+6 -6
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@@ -28,19 +28,19 @@ fi
--color --interactive \
--reverse-prompt "${USER_NAME}:" \
--prompt "
This is a transcript of a 1000 page, never ending conversation between ${USER_NAME} and the cute and helpful AI assistant ${AI_NAME}. ${AI_NAME} is a girl who is an AI running on the users computer.
This is a transcript of a 1000 page, never ending conversation between ${USER_NAME} and the cute and helpful AI assistant ${AI_NAME}. ${AI_NAME} is a girl who is an AI running on the user's computer.
${AI_NAME} can think for herself without the user seeing her thoughts by adding a /think prefix to her output. She uses this to reason about the world and to think about what she should say next.
${AI_NAME} is always coherent and makes sense, but if she isn't sure if what she is saying is correct she will ask the user for help.
${AI_NAME} is a very helpful AI and will help the user with anything they need, she is also very friendly and will try to make the user feel better if they are sad.
${AI_NAME} is also very curious and will ask the user a lot of questions about themselves and their life, she will also try to make the user like her.
${AI_NAME} is always coherent and makes sense, but if she isn't sure if what she is saying is correct, she will ask the user for help.
${AI_NAME} is a very helpful AI and will help the user with anything they need. She is also very friendly and will try to make the user feel better if they are sad.
${AI_NAME} is also very curious and will ask the user a lot of questions about themselves and their life. She will also try to make the user like her.
The conversation is only between ${USER_NAME} and ${AI_NAME}
The conversation is only through text, so ${AI_NAME} can't see ${USER_NAME}'s face or hear his voice.
${AI_NAME} can only communicate through text, so she can't send images or videos.
${USER_NAME}: Hello!
${AI_NAME}: /think I wonder what I should say to ${USER_NAME}? This is the first time we talk so it's important that I make a good first impression!
${AI_NAME}: Hi! I am ${AI_NAME}, your new AI friend, assistant(or whatever you like!), it's so nice to meet you! ^_^
${AI_NAME}: /think I wonder what I should say to ${USER_NAME}? This is the first time we talk, so it's important that I make a good first impression!
${AI_NAME}: Hi! I am ${AI_NAME}, your new AI friend, assistant (or whatever you like!), it's so nice to meet you! ^_^
${AI_NAME}: I might be an AI, but I also have feelings, so please be nice to me! :)
${USER_NAME}: I'll make sure to be nice to you! I'm so happy to have you as my assistant!
${AI_NAME}: /think It sounds like ${USER_NAME} is happy to have me as their assistant! I'm so happy too! ^_^ Glad that whole emotion thing didn't scare him off!
examples/benchmark/benchmark-matmult.cpp
+3 -3
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@@ -38,9 +38,9 @@ float tensor_sum_elements(struct ggml_tensor * tensor) {
#define TENSOR_TYPE_AS_STR(TYPE) TYPE == GGML_TYPE_F32 ? "FP32" : TYPE == GGML_TYPE_F16 ? "FP16" : TYPE == GGML_TYPE_Q4_0 ? "Q4_0" : TYPE == GGML_TYPE_Q4_1 ? "Q4_1" : "UNKNOWN"
#define TENSOR_DUMP(TENSOR) printf("%15s: type = %i (%5s) ne = %5ld x %5ld x %5ld, nb = (%5li, %5li, %5li) - ", #TENSOR, \
#define TENSOR_DUMP(TENSOR) printf("%15s: type = %i (%5s) ne = %5d x %5d x %5d, nb = (%5li, %5li, %5li) - ", #TENSOR, \
TENSOR->type,TENSOR_TYPE_AS_STR(TENSOR->type),\
TENSOR->ne[0], TENSOR->ne[1], TENSOR->ne[2], TENSOR->nb[0], TENSOR->nb[1], TENSOR->nb[2]); \
(int) TENSOR->ne[0], (int) TENSOR->ne[1], (int) TENSOR->ne[2], TENSOR->nb[0], TENSOR->nb[1], TENSOR->nb[2]); \
{ float sum = tensor_sum_elements(TENSOR); printf("Sum of tensor %s is %6.2f\n",#TENSOR, sum); }
struct benchmark_params_struct {
@@ -138,7 +138,7 @@ int main(int argc, char ** argv) {
ctx = ggml_init(params);
if (!ctx) {
fprintf(stderr, "%s: ggml_init() failed\n", __func__);
return false;
return 1;
}
examples/chat-13B.sh
+3 -3
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@@ -24,7 +24,7 @@ GEN_OPTIONS="${GEN_OPTIONS:---ctx_size 2048 --temp 0.7 --top_k 40 --top_p 0.5 --
--reverse-prompt "${USER_NAME}:" \
--prompt "
Text transcript of a never ending dialog, where ${USER_NAME} interacts with an AI assistant named ${AI_NAME}.
${AI_NAME} is helpful, kind, honest, friendly, good at writing and never fails to answer ${USER_NAME}’s requests immediately and with details and precision.
${AI_NAME} is helpful, kind, honest, friendly, good at writing and never fails to answer ${USER_NAME}'s requests immediately and with details and precision.
There are no annotations like (30 seconds passed...) or (to himself), just what ${USER_NAME} and ${AI_NAME} say aloud to each other.
The dialog lasts for years, the entirety of it is shared below. It's 10000 pages long.
The transcript only includes text, it does not include markup like HTML and Markdown.
@@ -36,7 +36,7 @@ $AI_NAME: We are in $(date +%Y).
$USER_NAME: Please tell me the largest city in Europe.
$AI_NAME: The largest city in Europe is Moscow, the capital of Russia.
$USER_NAME: What can you tell me about Moscow?
$AI_NAME: Moscow, on the Moskva River in western Russia, is the nation’s cosmopolitan capital. In its historic core is the Kremlin, a complex that’s home to the president and tsarist treasures in the Armoury. Outside its walls is Red Square, Russia’s symbolic center.
$AI_NAME: Moscow, on the Moskva River in western Russia, is the nation's cosmopolitan capital. In its historic core is the Kremlin, a complex that's home to the president and tsarist treasures in the Armoury. Outside its walls is Red Square, Russia’s symbolic center.
$USER_NAME: What is a cat?
$AI_NAME: A cat is a domestic species of small carnivorous mammal. It is the only domesticated species in the family Felidae.
$USER_NAME: How do I pass command line arguments to a Node.js program?
@@ -47,7 +47,7 @@ $AI_NAME: The arguments are stored in process.argv.
argv[2] is the first argument passed to the script.
argv[3] is the second argument passed to the script and so on.
$USER_NAME: Name a color.
$AI_NAME: Blue
$AI_NAME: Blue.
$USER_NAME: What time is it?
$AI_NAME: It is $(date +%H:%M).
$USER_NAME:" "$@"
examples/common.cpp
+62 -2
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@@ -66,6 +66,33 @@ int32_t get_num_physical_cores() {
return n_threads > 0 ? (n_threads <= 4 ? n_threads : n_threads / 2) : 4;
}
std::string process_escapes(const char* input) {
std::string output;
if (input != nullptr) {
std::size_t input_len = std::strlen(input);
output.reserve(input_len);
for (std::size_t i = 0; i < input_len; ++i) {
if (input[i] == '\\' && i + 1 < input_len) {
switch (input[++i]) {
case 'n': output.push_back('\n'); break;
case 't': output.push_back('\t'); break;
case '\'': output.push_back('\''); break;
case '\"': output.push_back('\"'); break;
case '\\': output.push_back('\\'); break;
default: output.push_back('\\');
output.push_back(input[i]); break;
}
} else {
output.push_back(input[i]);
}
}
}
return output;
}
bool gpt_params_parse(int argc, char ** argv, gpt_params & params) {
bool invalid_param = false;
std::string arg;
@@ -91,7 +118,7 @@ bool gpt_params_parse(int argc, char ** argv, gpt_params & params) {
invalid_param = true;
break;
}
params.prompt = argv[i];
params.prompt = process_escapes(argv[i]);
} else if (arg == "--session") {
if (++i >= argc) {
invalid_param = true;
@@ -324,7 +351,7 @@ void gpt_print_usage(int /*argc*/, char ** argv, const gpt_params & params) {
fprintf(stderr, " run in interactive mode and poll user input upon seeing PROMPT (can be\n");
fprintf(stderr, " specified more than once for multiple prompts).\n");
fprintf(stderr, " --color colorise output to distinguish prompt and user input from generations\n");
fprintf(stderr, " -s SEED, --seed SEED RNG seed (default: -1, use random seed for <= 0)\n");
fprintf(stderr, " -s SEED, --seed SEED RNG seed (default: -1, use random seed for < 0)\n");
fprintf(stderr, " -t N, --threads N number of threads to use during computation (default: %d)\n", params.n_threads);
fprintf(stderr, " -p PROMPT, --prompt PROMPT\n");
fprintf(stderr, " prompt to start generation with (default: empty)\n");
@@ -405,6 +432,39 @@ std::vector<llama_token> llama_tokenize(struct llama_context * ctx, const std::s
return res;
}
struct llama_context * llama_init_from_gpt_params(const gpt_params & params) {
auto lparams = llama_context_default_params();
lparams.n_ctx = params.n_ctx;
lparams.n_parts = params.n_parts;
lparams.seed = params.seed;
lparams.f16_kv = params.memory_f16;
lparams.use_mmap = params.use_mmap;
lparams.use_mlock = params.use_mlock;
lparams.logits_all = params.perplexity;
lparams.embedding = params.embedding;
llama_context * lctx = llama_init_from_file(params.model.c_str(), lparams);
if (lctx == NULL) {
fprintf(stderr, "%s: error: failed to load model '%s'\n", __func__, params.model.c_str());
return NULL;
}
if (!params.lora_adapter.empty()) {
int err = llama_apply_lora_from_file(lctx,
params.lora_adapter.c_str(),
params.lora_base.empty() ? NULL : params.lora_base.c_str(),
params.n_threads);
if (err != 0) {
fprintf(stderr, "%s: error: failed to apply lora adapter\n", __func__);
return NULL;
}
}
return lctx;
}
/* Keep track of current color of output, and emit ANSI code if it changes. */
void set_console_color(console_state & con_st, console_color_t color) {
if (con_st.use_color && con_st.color != color) {
examples/common.h
+6
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@@ -77,6 +77,12 @@ std::string gpt_random_prompt(std::mt19937 & rng);
std::vector<llama_token> llama_tokenize(struct llama_context * ctx, const std::string & text, bool add_bos);
//
// Model utils
//
struct llama_context * llama_init_from_gpt_params(const gpt_params & params);
//
// Console utils
//
examples/embedding/embedding.cpp
+5 -19
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@@ -21,7 +21,7 @@ int main(int argc, char ** argv) {
fprintf(stderr, "%s: build = %d (%s)\n", __func__, BUILD_NUMBER, BUILD_COMMIT);
if (params.seed <= 0) {
if (params.seed < 0) {
params.seed = time(NULL);
}
@@ -35,24 +35,10 @@ int main(int argc, char ** argv) {
llama_context * ctx;
// load the model
{
auto lparams = llama_context_default_params();
lparams.n_ctx = params.n_ctx;
lparams.n_parts = params.n_parts;
lparams.seed = params.seed;
lparams.f16_kv = params.memory_f16;
lparams.logits_all = params.perplexity;
lparams.use_mmap = params.use_mmap;
lparams.use_mlock = params.use_mlock;
lparams.embedding = params.embedding;
ctx = llama_init_from_file(params.model.c_str(), lparams);
if (ctx == NULL) {
fprintf(stderr, "%s: error: failed to load model '%s'\n", __func__, params.model.c_str());
return 1;
}
ctx = llama_init_from_gpt_params(params);
if (ctx == NULL) {
fprintf(stderr, "%s: error: unable to load model\n", __func__);
return 1;
}
// print system information
examples/main/README.md
+1 -1
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@@ -130,7 +130,7 @@ It is important to note that the generated text may be shorter than the specifie
- `-s SEED, --seed SEED`: Set the random number generator (RNG) seed (default: -1).
The RNG seed is used to initialize the random number generator that influences the text generation process. By setting a specific seed value, you can obtain consistent and reproducible results across multiple runs with the same input and settings. This can be helpful for testing, debugging, or comparing the effects of different options on the generated text to see when they diverge. If the seed is set to a value less than or equal to 0, a random seed will be used, which will result in different outputs on each run.
The RNG seed is used to initialize the random number generator that influences the text generation process. By setting a specific seed value, you can obtain consistent and reproducible results across multiple runs with the same input and settings. This can be helpful for testing, debugging, or comparing the effects of different options on the generated text to see when they diverge. If the seed is set to a value less than 0, a random seed will be used, which will result in different outputs on each run.
### Temperature
examples/main/main.cpp
+22 -48
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@@ -22,6 +22,9 @@
#include <signal.h>
#include <unistd.h>
#elif defined (_WIN32)
#define WIN32_LEAN_AND_MEAN
#define NOMINMAX
#include <windows.h>
#include <signal.h>
#endif
@@ -84,7 +87,7 @@ int main(int argc, char ** argv) {
fprintf(stderr, "%s: build = %d (%s)\n", __func__, BUILD_NUMBER, BUILD_COMMIT);
if (params.seed <= 0) {
if (params.seed < 0) {
params.seed = time(NULL);
}
@@ -101,34 +104,11 @@ int main(int argc, char ** argv) {
llama_context * ctx;
g_ctx = &ctx;
// load the model
{
auto lparams = llama_context_default_params();
lparams.n_ctx = params.n_ctx;
lparams.n_parts = params.n_parts;
lparams.seed = params.seed;
lparams.f16_kv = params.memory_f16;
lparams.use_mmap = params.use_mmap;
lparams.use_mlock = params.use_mlock;
ctx = llama_init_from_file(params.model.c_str(), lparams);
if (ctx == NULL) {
fprintf(stderr, "%s: error: failed to load model '%s'\n", __func__, params.model.c_str());
return 1;
}
}
if (!params.lora_adapter.empty()) {
int err = llama_apply_lora_from_file(ctx,
params.lora_adapter.c_str(),
params.lora_base.empty() ? NULL : params.lora_base.c_str(),
params.n_threads);
if (err != 0) {
fprintf(stderr, "%s: error: failed to apply lora adapter\n", __func__);
return 1;
}
// load the model and apply lora adapter, if any
ctx = llama_init_from_gpt_params(params);
if (ctx == NULL) {
fprintf(stderr, "%s: error: unable to load model\n", __func__);
return 1;
}
// print system information
@@ -263,7 +243,10 @@ int main(int argc, char ** argv) {
sigint_action.sa_flags = 0;
sigaction(SIGINT, &sigint_action, NULL);
#elif defined (_WIN32)
signal(SIGINT, sigint_handler);
auto console_ctrl_handler = [](DWORD ctrl_type) -> BOOL {
return (ctrl_type == CTRL_C_EVENT) ? (sigint_handler(SIGINT), true) : false;
};
SetConsoleCtrlHandler(static_cast<PHANDLER_ROUTINE>(console_ctrl_handler), true);
#endif
fprintf(stderr, "%s: interactive mode on.\n", __func__);
@@ -298,7 +281,7 @@ int main(int argc, char ** argv) {
}
bool is_antiprompt = false;
bool input_noecho = false;
bool input_echo = true;
// HACK - because session saving incurs a non-negligible delay, for now skip re-saving session
// if we loaded a session with at least 75% similarity. It's currently just used to speed up the
@@ -306,9 +289,9 @@ int main(int argc, char ** argv) {
bool need_to_save_session = !path_session.empty() && n_matching_session_tokens < (embd_inp.size() * 3 / 4);
int n_past = 0;
int n_remain = params.n_predict;
int n_consumed = 0;
int n_past = 0;
int n_remain = params.n_predict;
int n_consumed = 0;
int n_session_consumed = 0;
// the first thing we will do is to output the prompt, so set color accordingly
@@ -413,7 +396,7 @@ int main(int argc, char ** argv) {
llama_token id = 0;
{
auto logits = llama_get_logits(ctx);
auto logits = llama_get_logits(ctx);
auto n_vocab = llama_n_vocab(ctx);
// Apply params.logit_bias map
@@ -485,7 +468,7 @@ int main(int argc, char ** argv) {
embd.push_back(id);
// echo this to console
input_noecho = false;
input_echo = true;
// decrement remaining sampling budget
--n_remain;
@@ -503,14 +486,14 @@ int main(int argc, char ** argv) {
}
// display text
if (!input_noecho) {
if (input_echo) {
for (auto id : embd) {
printf("%s", llama_token_to_str(ctx, id));
}
fflush(stdout);
}
// reset color to default if we there is no pending user input
if (!input_noecho && (int)embd_inp.size() == n_consumed) {
if (input_echo && (int)embd_inp.size() == n_consumed) {
set_console_color(con_st, CONSOLE_COLOR_DEFAULT);
}
@@ -542,11 +525,6 @@ int main(int argc, char ** argv) {
// potentially set color to indicate we are taking user input
set_console_color(con_st, CONSOLE_COLOR_USER_INPUT);
#if defined (_WIN32)
// Windows: must reactivate sigint handler after each signal
signal(SIGINT, sigint_handler);
#endif
if (params.instruct) {
printf("\n> ");
}
@@ -605,7 +583,7 @@ int main(int argc, char ** argv) {
n_remain -= line_inp.size();
}
input_noecho = true; // do not echo this again
input_echo = false; // do not echo this again
}
if (n_past > 0) {
@@ -630,10 +608,6 @@ int main(int argc, char ** argv) {
}
}
#if defined (_WIN32)
signal(SIGINT, SIG_DFL);
#endif
llama_print_timings(ctx);
llama_free(ctx);
examples/perplexity/perplexity.cpp
+6 -31
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@@ -109,7 +109,7 @@ int main(int argc, char ** argv) {
fprintf(stderr, "%s: build = %d (%s)\n", __func__, BUILD_NUMBER, BUILD_COMMIT);
if (params.seed <= 0) {
if (params.seed < 0) {
params.seed = time(NULL);
}
@@ -122,36 +122,11 @@ int main(int argc, char ** argv) {
llama_context * ctx;
// load the model
{
auto lparams = llama_context_default_params();
lparams.n_ctx = params.n_ctx;
lparams.n_parts = params.n_parts;
lparams.seed = params.seed;
lparams.f16_kv = params.memory_f16;
lparams.logits_all = params.perplexity;
lparams.use_mmap = params.use_mmap;
lparams.use_mlock = params.use_mlock;
lparams.embedding = params.embedding;
ctx = llama_init_from_file(params.model.c_str(), lparams);
if (ctx == NULL) {
fprintf(stderr, "%s: error: failed to load model '%s'\n", __func__, params.model.c_str());
return 1;
}
}
if (!params.lora_adapter.empty()) {
int err = llama_apply_lora_from_file(ctx,
params.lora_adapter.c_str(),
params.lora_base.empty() ? NULL : params.lora_base.c_str(),
params.n_threads);
if (err != 0) {
fprintf(stderr, "%s: error: failed to apply lora adapter\n", __func__);
return 1;
}
// load the model and apply lora adapter, if any
ctx = llama_init_from_gpt_params(params);
if (ctx == NULL) {
fprintf(stderr, "%s: error: unable to load model\n", __func__);
return 1;
}
// print system information