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gguf : start implementing quantization (WIP)

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M. Yusuf Sarıgöz 2023-08-12 11:32:34 +03:00
parent 4fa017a1f9
commit 0e1a3c7e7d
1 changed files with 27 additions and 6 deletions
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33
gguf-llama.cpp
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@ -615,6 +615,8 @@ struct gguf_file_saver {
gguf_file file; gguf_file file;
gguf_file_loader * fl; gguf_file_loader * fl;
size_t info_offset; size_t info_offset;
size_t tensor_offset = 0;
gguf_file_saver(const char * fname, gguf_file_loader * fl, enum llama_ftype new_ftype) gguf_file_saver(const char * fname, gguf_file_loader * fl, enum llama_ftype new_ftype)
: file(fname, "wb"), fl(fl) { : file(fname, "wb"), fl(fl) {
fprintf(stderr, "llama.cpp: saving model to %s\n", fname); fprintf(stderr, "llama.cpp: saving model to %s\n", fname);
@ -622,8 +624,6 @@ struct gguf_file_saver {
write_hparams(new_ftype); write_hparams(new_ftype);
} }
// TODO: probably it's better to move these to gguf_file
void write_header() { void write_header() {
const int32_t magic = GGUF_MAGIC; const int32_t magic = GGUF_MAGIC;
file.write_i32(magic); file.write_i32(magic);
@ -740,12 +740,26 @@ struct gguf_file_saver {
file.write_zeros(count); file.write_zeros(count);
} }
size_t write_tensor_info(llama_load_tensor & tensor) {
size_t total_written = 0;
file.seek(0, info_offset);
total_written += file.write_str(tensor.name);
int32_t n_dims = tensor.ne.size();
file.write_i32(n_dims);
for (int32_t i = 0; i < n_dims; ++i) {
total_written += file.write_i32(i);
}
total_written += file.write_u64(tensor_offset);
info_offset += total_written;
file.seek(0, SEEK_END);
return total_written;
}
void write_tensor(llama_load_tensor & tensor, enum ggml_type new_type, const void * new_data, size_t new_size) { void write_tensor(llama_load_tensor & tensor, enum ggml_type new_type, const void * new_data, size_t new_size) {
GGML_UNUSED(tensor);
GGML_UNUSED(new_data);
GGML_UNUSED(new_size);
switch (new_type) { switch (new_type) {
case GGML_TYPE_F32: case GGML_TYPE_F32:
case GGML_TYPE_F16: case GGML_TYPE_F16:
@ -763,6 +777,13 @@ struct gguf_file_saver {
default: GGML_ASSERT(false); default: GGML_ASSERT(false);
} }
write_tensor_info(tensor);
// file.write_raw(new_data);
GGML_UNUSED(new_data);
size_t padded_size = GGML_PAD(new_size, GGUF_DEFAULT_ALIGNMENT); // TODO: handle custom alignment
size_t pad = padded_size - new_size;
file.write_zeros(pad);
tensor_offset += padded_size;
} }
}; };