vbatts/llama.cpp
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replace custom data getters and setters by ggml functions

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xaedes 2023-08-30 15:19:26 +02:00
parent d487e0531f
commit e6b7158123
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GPG key ID: 30030EDD817EA2B1
2 changed files with 12 additions and 81 deletions
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37
examples/finetune/finetune.cpp
View file

@ -854,31 +854,6 @@ struct ggml_tensor * llama_build_lora_finetune_graphs(
return t36;
}
void set_f32_3d(struct ggml_tensor * tensor, int64_t i0, int64_t i1, int64_t i2, float value) {
float * ptr = (float *) ((char *) tensor->data + i0*tensor->nb[0] + i1*tensor->nb[1] + i2*tensor->nb[2]);
*ptr = value;
}
void set_f32_2d(struct ggml_tensor * tensor, int64_t i0, int64_t i1, float value) {
float * ptr = (float *) ((char *) tensor->data + i0*tensor->nb[0] + i1*tensor->nb[1]);
*ptr = value;
}
void set_i32_2d(struct ggml_tensor * tensor, int64_t i0, int64_t i1, int32_t value) {
int32_t * ptr = (int32_t *) ((char *) tensor->data + i0*tensor->nb[0] + i1*tensor->nb[1]);
*ptr = value;
}
float get_f32_2d(struct ggml_tensor * tensor, int64_t i0, int64_t i1) {
float * ptr = (float *) ((char *) tensor->data + i0*tensor->nb[0] + i1*tensor->nb[1]);
return *ptr;
}
int32_t get_i32_2d(struct ggml_tensor * tensor, int64_t i0, int64_t i1) {
int32_t * ptr = (int32_t *) ((char *) tensor->data + i0*tensor->nb[0] + i1*tensor->nb[1]);
return *ptr;
}
void get_example_targets(struct llama_context * lctx, const int * train_samples, size_t n_train_samples, const llama_token * train_data, size_t n_train_data, int example_id, struct ggml_tensor * tokens_input, struct ggml_tensor * target_logits, struct ggml_tensor * target_probs) {
int n_tokens = tokens_input->ne[0];
int n_vocab = target_logits->ne[0];
@ -891,8 +866,8 @@ void get_example_targets(struct llama_context * lctx, const int * train_samples,
ggml_set_i32_1d(tokens_input, 0, llama_token_bos(lctx));
for (int i=1; i<n_tokens+1; ++i) {
int token = clamp(train_data[sample+i-1], 0, n_vocab-1);
set_f32_2d(target_logits, token, i-1, +1.0f);
set_f32_2d(target_probs, token, i-1, +1.0f);
ggml_set_f32_nd(target_logits, token, i-1, 0, 0, +1.0f);
ggml_set_f32_nd(target_probs, token, i-1, 0, 0, +1.0f);
if (i<n_tokens) {
ggml_set_i32_1d(tokens_input, i, token);
}
@ -922,13 +897,13 @@ void get_example_targets_batch(struct llama_context* lctx, const int * train_sam
// printf("%s: sample_idx=%zu sample=%zu\n", __func__, sample_idx, sample);
GGML_ASSERT(sample+n_tokens-1 < n_train_data);
set_i32_2d(tokens_input, 0, k, llama_token_bos(lctx));
ggml_set_i32_nd(tokens_input, 0, k, 0, 0, llama_token_bos(lctx));
for (int i=1; i<n_tokens+1; ++i) {
int token = clamp(train_data[sample+i-1], 0, n_vocab-1);
set_f32_3d(target_logits, token, i-1, k, +1.0f);
set_f32_3d(target_probs, token, i-1, k, +1.0f);
ggml_set_f32_nd(target_logits, token, i-1, k, 0, +1.0f);
ggml_set_f32_nd(target_probs, token, i-1, k, 0, +1.0f);
if (i<n_tokens) {
set_i32_2d(tokens_input, i, k, token);
ggml_set_i32_nd(tokens_input, i, k, 0, 0, token);
}
}
}

56
examples/train-text-from-scratch/train-text-from-scratch.cpp
View file

@ -627,50 +627,6 @@ struct ggml_tensor * llama_build_train_graphs(
return t36;
}
void set_f32_3d(struct ggml_tensor * tensor, int64_t i0, int64_t i1, int64_t i2, float value) {
float * ptr = (float *) ((char *) tensor->data + i0*tensor->nb[0] + i1*tensor->nb[1] + i2*tensor->nb[2]);
*ptr = value;
}
void set_f32_2d(struct ggml_tensor * tensor, int64_t i0, int64_t i1, float value) {
float * ptr = (float *) ((char *) tensor->data + i0*tensor->nb[0] + i1*tensor->nb[1]);
*ptr = value;
}
void set_i32_2d(struct ggml_tensor * tensor, int64_t i0, int64_t i1, int32_t value) {
int32_t * ptr = (int32_t *) ((char *) tensor->data + i0*tensor->nb[0] + i1*tensor->nb[1]);
*ptr = value;
}
float get_f32_2d(struct ggml_tensor * tensor, int64_t i0, int64_t i1) {
float * ptr = (float *) ((char *) tensor->data + i0*tensor->nb[0] + i1*tensor->nb[1]);
return *ptr;
}
int32_t get_i32_2d(struct ggml_tensor * tensor, int64_t i0, int64_t i1) {
int32_t * ptr = (int32_t *) ((char *) tensor->data + i0*tensor->nb[0] + i1*tensor->nb[1]);
return *ptr;
}
void print_row(struct ggml_tensor * probs, int i) {
for (int k = 0; k < probs->ne[0]; ++k) {
float p = get_f32_2d(probs, k, i);
printf(" %.2f", p);
}
printf("\n");
}
void print_matrix(struct ggml_tensor * probs) {
assert(probs->n_dims == 2);
for (int i = 0; i < probs->ne[1]; ++i) {
for (int k = 0; k < probs->ne[0]; ++k) {
float p = get_f32_2d(probs, k, i);
printf(" %.2f", p);
}
printf("\n");
}
}
void get_example_targets(struct llama_context * lctx, const int * train_samples, size_t n_train_samples, const llama_token * train_data, size_t n_train_data, int example_id, struct ggml_tensor * tokens_input, struct ggml_tensor * target_logits, struct ggml_tensor * target_probs) {
int n_tokens = tokens_input->ne[0];
int n_vocab = target_logits->ne[0];
@ -683,8 +639,8 @@ void get_example_targets(struct llama_context * lctx, const int * train_samples,
ggml_set_i32_1d(tokens_input, 0, llama_token_bos(lctx));
for (int i=1; i<n_tokens+1; ++i) {
int token = clamp(train_data[sample+i-1], 0, n_vocab-1);
set_f32_2d(target_logits, token, i-1, +1.0f);
set_f32_2d(target_probs, token, i-1, +1.0f);
ggml_set_f32_nd(target_logits, token, i-1, 0, 0, +1.0f);
ggml_set_f32_nd(target_probs, token, i-1, 0, 0, +1.0f);
if (i<n_tokens) {
ggml_set_i32_1d(tokens_input, i, token);
}
@ -714,13 +670,13 @@ void get_example_targets_batch(struct llama_context * lctx, const int * train_sa
// printf("%s: sample_idx=%zu sample=%zu\n", __func__, sample_idx, sample);
GGML_ASSERT(sample+n_tokens-1 < n_train_data);
set_i32_2d(tokens_input, 0, k, llama_token_bos(lctx));
ggml_set_i32_nd(tokens_input, 0, k, 0, 0, llama_token_bos(lctx));
for (int i=1; i<n_tokens+1; ++i) {
int token = clamp(train_data[sample+i-1], 0, n_vocab-1);
set_f32_3d(target_logits, token, i-1, k, +1.0f);
set_f32_3d(target_probs, token, i-1, k, +1.0f);
ggml_set_f32_nd(target_logits, token, i-1, k, 0, +1.0f);
ggml_set_f32_nd(target_probs, token, i-1, k, 0, +1.0f);
if (i<n_tokens) {
set_i32_2d(tokens_input, i, k, token);
ggml_set_i32_nd(tokens_input, i, k, 0, 0, token);
}
}
}