DarthAffe/stable-diffusion.cpp
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fix: convert f64 to f32 and i64 to i32 when loading weights

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leejet 2025-07-24 00:59:38 +08:00
parent ab835f7d39
commit bd1eaef93e
2 changed files with 57 additions and 5 deletions
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54
model.cpp
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@ -815,6 +815,7 @@ void f8_e4m3_to_f16_vec(uint8_t* src, uint16_t* dst, int64_t n) {
dst[i] = f8_e4m3_to_f16(src[i]);
}
}
void f8_e5m2_to_f16_vec(uint8_t* src, uint16_t* dst, int64_t n) {
// support inplace op
for (int64_t i = n - 1; i >= 0; i--) {
@ -822,6 +823,20 @@ void f8_e5m2_to_f16_vec(uint8_t* src, uint16_t* dst, int64_t n) {
}
}
void f64_to_f32_vec(double* src, float* dst, int64_t n) {
// support inplace op
for (int64_t i = 0; i < n; i++) {
dst[i] = (float)src[i];
}
}
void i64_to_i32_vec(int64_t* src, int32_t* dst, int64_t n) {
// support inplace op
for (int64_t i = 0; i < n; i++) {
dst[i] = (int32_t)src[i];
}
}
void convert_tensor(void* src,
ggml_type src_type,
void* dst,
@ -1057,13 +1072,13 @@ ggml_type str_to_ggml_type(const std::string& dtype) {
} else if (dtype == "F32") {
ttype = GGML_TYPE_F32;
} else if (dtype == "F64") {
ttype = GGML_TYPE_F64;
ttype = GGML_TYPE_F32;
} else if (dtype == "F8_E4M3") {
ttype = GGML_TYPE_F16;
} else if (dtype == "F8_E5M2") {
ttype = GGML_TYPE_F16;
} else if (dtype == "I64") {
ttype = GGML_TYPE_I64;
ttype = GGML_TYPE_I32;
}
return ttype;
}
@ -1185,6 +1200,14 @@ bool ModelLoader::init_from_safetensors_file(const std::string& file_path, const
tensor_storage.is_f8_e5m2 = true;
// f8 -> f16
GGML_ASSERT(tensor_storage.nbytes() == tensor_data_size * 2);
} else if (dtype == "F64") {
tensor_storage.is_f64 = true;
// f64 -> f32
GGML_ASSERT(tensor_storage.nbytes() * 2 == tensor_data_size);
} else if (dtype == "I64") {
tensor_storage.is_i64 = true;
// i64 -> i32
GGML_ASSERT(tensor_storage.nbytes() * 2 == tensor_data_size);
} else {
GGML_ASSERT(tensor_storage.nbytes() == tensor_data_size);
}
@ -1945,7 +1968,12 @@ bool ModelLoader::load_tensors(on_new_tensor_cb_t on_new_tensor_cb, ggml_backend
// for the CPU and Metal backend, we can copy directly into the tensor
if (tensor_storage.type == dst_tensor->type) {
GGML_ASSERT(ggml_nbytes(dst_tensor) == tensor_storage.nbytes());
read_data(tensor_storage, (char*)dst_tensor->data, nbytes_to_read);
if (tensor_storage.is_f64 || tensor_storage.is_i64) {
read_buffer.resize(tensor_storage.nbytes_to_read());
read_data(tensor_storage, (char*)read_buffer.data(), nbytes_to_read);
} else {
read_data(tensor_storage, (char*)dst_tensor->data, nbytes_to_read);
}
if (tensor_storage.is_bf16) {
// inplace op
@ -1956,9 +1984,13 @@ bool ModelLoader::load_tensors(on_new_tensor_cb_t on_new_tensor_cb, ggml_backend
} else if (tensor_storage.is_f8_e5m2) {
// inplace op
f8_e5m2_to_f16_vec((uint8_t*)dst_tensor->data, (uint16_t*)dst_tensor->data, tensor_storage.nelements());
} else if (tensor_storage.is_f64) {
f64_to_f32_vec((double*)read_buffer.data(), (float*)dst_tensor->data, tensor_storage.nelements());
} else if (tensor_storage.is_i64) {
i64_to_i32_vec((int64_t*)read_buffer.data(), (int32_t*)dst_tensor->data, tensor_storage.nelements());
}
} else {
read_buffer.resize(tensor_storage.nbytes());
read_buffer.resize(std::max(tensor_storage.nbytes(), tensor_storage.nbytes_to_read()));
read_data(tensor_storage, (char*)read_buffer.data(), nbytes_to_read);
if (tensor_storage.is_bf16) {
@ -1970,13 +2002,19 @@ bool ModelLoader::load_tensors(on_new_tensor_cb_t on_new_tensor_cb, ggml_backend
} else if (tensor_storage.is_f8_e5m2) {
// inplace op
f8_e5m2_to_f16_vec((uint8_t*)read_buffer.data(), (uint16_t*)read_buffer.data(), tensor_storage.nelements());
} else if (tensor_storage.is_f64) {
// inplace op
f64_to_f32_vec((double*)read_buffer.data(), (float*)read_buffer.data(), tensor_storage.nelements());
} else if (tensor_storage.is_i64) {
// inplace op
i64_to_i32_vec((int64_t*)read_buffer.data(), (int32_t*)read_buffer.data(), tensor_storage.nelements());
}
convert_tensor((void*)read_buffer.data(), tensor_storage.type, dst_tensor->data,
dst_tensor->type, (int)tensor_storage.nelements() / (int)tensor_storage.ne[0], (int)tensor_storage.ne[0]);
}
} else {
read_buffer.resize(tensor_storage.nbytes());
read_buffer.resize(std::max(tensor_storage.nbytes(), tensor_storage.nbytes_to_read()));
read_data(tensor_storage, (char*)read_buffer.data(), nbytes_to_read);
if (tensor_storage.is_bf16) {
@ -1988,6 +2026,12 @@ bool ModelLoader::load_tensors(on_new_tensor_cb_t on_new_tensor_cb, ggml_backend
} else if (tensor_storage.is_f8_e5m2) {
// inplace op
f8_e5m2_to_f16_vec((uint8_t*)read_buffer.data(), (uint16_t*)read_buffer.data(), tensor_storage.nelements());
} else if (tensor_storage.is_f64) {
// inplace op
f64_to_f32_vec((double*)read_buffer.data(), (float*)read_buffer.data(), tensor_storage.nelements());
} else if (tensor_storage.is_i64) {
// inplace op
i64_to_i32_vec((int64_t*)read_buffer.data(), (int32_t*)read_buffer.data(), tensor_storage.nelements());
}
if (tensor_storage.type == dst_tensor->type) {

8
model.h
View File

@ -102,6 +102,8 @@ struct TensorStorage {
bool is_bf16 = false;
bool is_f8_e4m3 = false;
bool is_f8_e5m2 = false;
bool is_f64 = false;
bool is_i64 = false;
int64_t ne[SD_MAX_DIMS] = {1, 1, 1, 1, 1};
int n_dims = 0;
@ -133,6 +135,8 @@ struct TensorStorage {
int64_t nbytes_to_read() const {
if (is_bf16 || is_f8_e4m3 || is_f8_e5m2) {
return nbytes() / 2;
} else if (is_f64 || is_i64) {
return nbytes() * 2;
} else {
return nbytes();
}
@ -183,6 +187,10 @@ struct TensorStorage {
type_name = "f8_e4m3";
} else if (is_f8_e5m2) {
type_name = "f8_e5m2";
} else if (is_f64) {
type_name = "f64";
} else if (is_i64) {
type_name = "i64";
}
ss << name << " | " << type_name << " | ";
ss << n_dims << " [";