CS348Project/llama.cpp
5
0
Fork 0
mirror of https://github.com/ggml-org/llama.cpp.git synced 2025-10-31 08:51:55 +00:00
Code Issues Packages Projects Releases Wiki Activity

llama2c : rename function

Browse Source
This commit is contained in:
Georgi Gerganov
2023-09-01 17:00:40 +03:00
parent 6c9c23429b
commit 0d58936686
1 changed files with 14 additions and 14 deletions
Download Patch File Download Diff File Expand all files Collapse all files

28
examples/convert-llama2c-to-ggml/convert-llama2c-to-ggml.cpp
View File

@@ -637,7 +637,7 @@ void load_vocab(const char *filename, Config *config, struct llama_vocab *vocab)
} }
} }
void stuff_karpathy_weights_into_gg(struct ggml_tensor * gg_weights, const float * karpathy_weights) { void convert_weights_ak_to_gg(struct ggml_tensor * gg_weights, const float * karpathy_weights) {
int ct; int ct;
switch (gg_weights->n_dims){ switch (gg_weights->n_dims){
case 1: case 1:
@@ -674,13 +674,13 @@ void stuff_karpathy_weights_into_gg(struct ggml_tensor * gg_weights, const float
} }
void save_as_llama_model(struct llama_vocab * vocab, struct my_llama_model * model, TransformerWeights* w, const char * filename) { void save_as_llama_model(struct llama_vocab * vocab, struct my_llama_model * model, TransformerWeights* w, const char * filename) {
// stuff AK weights into GG weights one by one. // convert AK weights into GG weights one by one.
// w->token_embedding_table -> model->tok_embeddings // w->token_embedding_table -> model->tok_embeddings
// float* -> struct ggml_tensor // float* -> struct ggml_tensor
stuff_karpathy_weights_into_gg(model->tok_embeddings, w->token_embedding_table); convert_weights_ak_to_gg(model->tok_embeddings, w->token_embedding_table);
stuff_karpathy_weights_into_gg(model->output, w->wcls ? w->wcls : w->token_embedding_table); convert_weights_ak_to_gg(model->output, w->wcls ? w->wcls : w->token_embedding_table);
stuff_karpathy_weights_into_gg(model->norm, w->rms_final_weight); convert_weights_ak_to_gg(model->norm, w->rms_final_weight);
//print_row(model->norm, 0); //print_row(model->norm, 0);
// for rms-att-weight // for rms-att-weight
@@ -690,18 +690,18 @@ void save_as_llama_model(struct llama_vocab * vocab, struct my_llama_model * mod
for (uint32_t i = 0; i < model->hparams.n_layer; ++i){ for (uint32_t i = 0; i < model->hparams.n_layer; ++i){
auto & layer = model->layers[i]; auto & layer = model->layers[i];
// 1d // 1d
stuff_karpathy_weights_into_gg(layer.attention_norm, &w->rms_att_weight[i*row_length]); convert_weights_ak_to_gg(layer.attention_norm, &w->rms_att_weight[i*row_length]);
stuff_karpathy_weights_into_gg(layer.ffn_norm , &w->rms_ffn_weight[i*row_length]); convert_weights_ak_to_gg(layer.ffn_norm , &w->rms_ffn_weight[i*row_length]);
// from 3d matrix layer x dim x dim to 2d matrix dim x dim // from 3d matrix layer x dim x dim to 2d matrix dim x dim
stuff_karpathy_weights_into_gg(layer.wq , &w->wq[i*row_length*row_length]); convert_weights_ak_to_gg(layer.wq , &w->wq[i*row_length*row_length]);
stuff_karpathy_weights_into_gg(layer.wk , &w->wk[i*row_length*row_length]); convert_weights_ak_to_gg(layer.wk , &w->wk[i*row_length*row_length]);
stuff_karpathy_weights_into_gg(layer.wv , &w->wv[i*row_length*row_length]); convert_weights_ak_to_gg(layer.wv , &w->wv[i*row_length*row_length]);
stuff_karpathy_weights_into_gg(layer.wo , &w->wo[i*row_length*row_length]); convert_weights_ak_to_gg(layer.wo , &w->wo[i*row_length*row_length]);
stuff_karpathy_weights_into_gg(layer.w1 , &w->w1[i*row_length*n_ff]); convert_weights_ak_to_gg(layer.w1 , &w->w1[i*row_length*n_ff]);
stuff_karpathy_weights_into_gg(layer.w2 , &w->w2[i*n_ff*row_length]); convert_weights_ak_to_gg(layer.w2 , &w->w2[i*n_ff*row_length]);
stuff_karpathy_weights_into_gg(layer.w3 , &w->w3[i*row_length*n_ff]); convert_weights_ak_to_gg(layer.w3 , &w->w3[i*row_length*n_ff]);
} }
struct gguf_context * ctx = gguf_init_empty(); struct gguf_context * ctx = gguf_init_empty();