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sd: sync to master-391-5865b5e (#1878)

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This commit is contained in:
Wagner Bruna
2025-12-08 08:53:52 -03:00
committed by GitHub
parent 242ae8b8f3
commit 801840d3bd
23 changed files with 250 additions and 216 deletions
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otherarch/sdcpp/model.cpp
+5 -22
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@@ -107,8 +107,8 @@ const char* unused_tensors[] = {
"embedding_manager",
"denoiser.sigmas",
"text_encoders.t5xxl.transformer.encoder.embed_tokens.weight", // only used during training
"ztsnr", // Found in some SDXL vpred models
"edm_vpred.sigma_min", // Found in CosXL
"ztsnr", // Found in some SDXL vpred models
"edm_vpred.sigma_min", // Found in CosXL
// TODO: find another way to avoid the "unknown tensor" for these two
// "edm_vpred.sigma_max", // Used to detect CosXL
// "v_pred", // Used to detect SDXL vpred models
@@ -140,11 +140,6 @@ std::string kcpp_fix_wrong_img_tensor_name(const std::string& name) //kcpp funct
return name;
}
float bf16_to_f32(uint16_t bfloat16) {
uint32_t val_bits = (static_cast<uint32_t>(bfloat16) << 16);
return *reinterpret_cast<float*>(&val_bits);
}
uint16_t f8_e4m3_to_f16(uint8_t f8) {
// do we need to support uz?
@@ -227,13 +222,6 @@ uint16_t f8_e5m2_to_f16(uint8_t fp8) {
return fp16_sign | (fp16_exponent << 10) | fp16_mantissa;
}
void bf16_to_f32_vec(uint16_t* src, float* dst, int64_t n) {
// support inplace op
for (int64_t i = n - 1; i >= 0; i--) {
dst[i] = bf16_to_f32(src[i]);
}
}
void f8_e4m3_to_f16_vec(uint8_t* src, uint16_t* dst, int64_t n) {
// support inplace op
for (int64_t i = n - 1; i >= 0; i--) {
@@ -523,7 +511,7 @@ ggml_type str_to_ggml_type(const std::string& dtype) {
if (dtype == "F16") {
ttype = GGML_TYPE_F16;
} else if (dtype == "BF16") {
ttype = GGML_TYPE_F32;
ttype = GGML_TYPE_BF16;
} else if (dtype == "F32") {
ttype = GGML_TYPE_F32;
} else if (dtype == "F64") {
@@ -658,10 +646,7 @@ bool ModelLoader::init_from_safetensors_file(const std::string& file_path, const
size_t tensor_data_size = end - begin;
if (dtype == "BF16") {
tensor_storage.is_bf16 = true;
GGML_ASSERT(tensor_storage.nbytes() == tensor_data_size * 2);
} else if (dtype == "F8_E4M3") {
if (dtype == "F8_E4M3") {
tensor_storage.is_f8_e4m3 = true;
// f8 -> f16
GGML_ASSERT(tensor_storage.nbytes() == tensor_data_size * 2);
@@ -1597,9 +1582,7 @@ bool ModelLoader::load_tensors(on_new_tensor_cb_t on_new_tensor_cb, int n_thread
read_time_ms.fetch_add(t1 - t0);
t0 = ggml_time_ms();
if (tensor_storage.is_bf16) {
bf16_to_f32_vec((uint16_t*)read_buf, (float*)target_buf, tensor_storage.nelements());
} else if (tensor_storage.is_f8_e4m3) {
if (tensor_storage.is_f8_e4m3) {
f8_e4m3_to_f16_vec((uint8_t*)read_buf, (uint16_t*)target_buf, tensor_storage.nelements());
} else if (tensor_storage.is_f8_e5m2) {
f8_e5m2_to_f16_vec((uint8_t*)read_buf, (uint16_t*)target_buf, tensor_storage.nelements());