root/llama.cpp
1
0
Fork 0
mirror of https://github.com/ggerganov/llama.cpp.git synced 2024-12-24 02:14:35 +00:00
Code Issues Actions 11 Packages Projects Releases Wiki Activity

export-lora : throw error if lora is quantized (#9002)

Browse Source
This commit is contained in:
Xuan Son Nguyen 2024-08-13 11:41:14 +02:00 committed by GitHub
parent fc4ca27b25
commit 828d6ff7d7
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
2 changed files with 29 additions and 12 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

6
examples/export-lora/README.md
View File

@ -17,9 +17,9 @@ For example:
```bash
./bin/llama-export-lora \
-m open-llama-3b-v2-q8_0.gguf \
-o open-llama-3b-v2-q8_0-english2tokipona-chat.gguf \
--lora lora-open-llama-3b-v2-q8_0-english2tokipona-chat-LATEST.gguf
-m open-llama-3b-v2.gguf \
-o open-llama-3b-v2-english2tokipona-chat.gguf \
--lora lora-open-llama-3b-v2-english2tokipona-chat-LATEST.gguf
```
Multiple LORA adapters can be applied by passing multiple `--lora FNAME` or `--lora-scaled FNAME S` command line parameters:

35
examples/export-lora/export-lora.cpp
View File

@ -10,6 +10,12 @@
static bool g_verbose = false;
struct tensor_transformation {
struct ggml_tensor * in;
struct ggml_tensor * out;
bool is_copy;
};
static std::string get_kv_str(struct gguf_context * ctx_gguf, const std::string & key){
int id = gguf_find_key(ctx_gguf, key.c_str());
return id < 0 ? "" : std::string(gguf_get_val_str(ctx_gguf, id));
@ -198,8 +204,7 @@ struct lora_merge_ctx {
}
// mapping base tensor to out tensor (same shape with base, but different type)
// if out_tensor == nullptr, we only copy it
std::vector<std::pair<struct ggml_tensor *, struct ggml_tensor *>> base_to_out_tensors;
std::vector<tensor_transformation> trans;
for (auto & it : base_model.tensors) {
bool t_a = true;
bool t_b = true;
@ -212,14 +217,22 @@ struct lora_merge_ctx {
// only copy
struct ggml_tensor * cpy_tensor = ggml_dup_tensor(ctx_out_ggml, base_tensor);
ggml_set_name(cpy_tensor, base_tensor->name);
base_to_out_tensors.push_back(std::make_pair(cpy_tensor, nullptr));
trans.push_back({
cpy_tensor,
cpy_tensor,
true,
});
gguf_add_tensor(ctx_out, cpy_tensor);
} else if (t_a && t_b) {
// need merging
struct ggml_tensor * out_tensor = ggml_new_tensor(
ctx_out_ggml, get_out_tensor_type(base_tensor), GGML_MAX_DIMS, base_tensor->ne);
ggml_set_name(out_tensor, base_tensor->name);
base_to_out_tensors.push_back(std::make_pair(base_tensor, out_tensor));
trans.push_back({
base_tensor,
out_tensor,
false,
});
gguf_add_tensor(ctx_out, out_tensor);
} else {
throw std::runtime_error("tensor " + it.first + " missing either lora_a or lora_b");
@ -234,12 +247,12 @@ struct lora_merge_ctx {
// process base model tensors
size_t n_merged = 0;
for (auto & it : base_to_out_tensors) {
if (it.second != nullptr) {
merge_tensor(it.first, it.second);
for (auto & it : trans) {
if (!it.is_copy) {
merge_tensor(it.in, it.out);
n_merged++;
} else {
copy_tensor(it.first);
copy_tensor(it.in);
}
}
@ -252,7 +265,7 @@ struct lora_merge_ctx {
}
printf("%s : merged %ld tensors with lora adapters\n", __func__, n_merged);
printf("%s : wrote %ld tensors to output file\n", __func__, base_to_out_tensors.size());
printf("%s : wrote %ld tensors to output file\n", __func__, trans.size());
}
void copy_tensor(struct ggml_tensor * base) {
@ -285,6 +298,10 @@ struct lora_merge_ctx {
for (size_t i = 0; i < adapters.size(); ++i) {
auto t_a = adapters[i]->get_tensor(name_lora_a);
auto t_b = adapters[i]->get_tensor(name_lora_b);
// TODO: add support for quantized lora
if (ggml_is_quantized(t_a->type) || ggml_is_quantized(t_b->type)) {
throw std::runtime_error("quantized LoRA adapters is not supported, please retry with f16 or f32");
}
inp_a[i] = ggml_dup_tensor(ctx, t_a);
inp_b[i] = ggml_dup_tensor(ctx, t_b);
}