vbatts/llama.cpp
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remove unused functions

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xaedes 2023-05-22 16:54:21 +02:00
parent 42d9b4cfc2
commit b763d6f1f2
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1 changed files with 0 additions and 68 deletions
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68
examples/baby-llama/baby-llama-text.cpp
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@ -1144,72 +1144,6 @@ struct ggml_tensor * forward_batch_wo_cache(
return inpL; return inpL;
} }
void sample_softmax(struct ggml_tensor * logits, struct ggml_tensor * probs, struct ggml_tensor * best_samples) {
assert(logits->n_dims == 2);
assert(probs->n_dims == 2);
assert(best_samples->n_dims == 1);
assert(logits->ne[1] == best_samples->ne[0]);
assert(logits->ne[0] == probs->ne[0]);
assert(logits->ne[1] == probs->ne[1]);
for (int i = 0; i < logits->ne[1]; ++i) {
float max_logit = ggml_get_f32_1d(logits, i * logits->ne[0]);
ggml_set_i32_1d(best_samples, i, 0);
for (int k = 0; k < logits->ne[0]; ++k) {
float logit = ggml_get_f32_1d(logits, i * logits->ne[0] + k);
if (logit > max_logit) {
max_logit = logit;
ggml_set_i32_1d(best_samples, i, k);
}
}
float psum = 0;
for (int k = 0; k < logits->ne[0]; ++k) {
float logit = ggml_get_f32_1d(logits, i * logits->ne[0] + k);
float p = (logit == -INFINITY) ? 0 : expf(logit - max_logit);
psum += p;
ggml_set_f32_1d(probs, i * probs->ne[0] + k, p);
}
for (int k = 0; k < logits->ne[0]; ++k) {
float p = ggml_get_f32_1d(probs, i*probs->ne[0] + k);
ggml_set_f32_1d(probs, i * probs->ne[0] + k, p / psum);
}
}
}
void sample_softmax_batch(struct ggml_context * ctx, struct ggml_tensor * logits, struct ggml_tensor * probs, struct ggml_tensor * best_samples) {
GGML_ASSERT(best_samples->n_dims == 2);
GGML_ASSERT(logits->n_dims == 3);
GGML_ASSERT(probs->n_dims == 3);
int n_tokens = best_samples->ne[0];
int n_batch = best_samples->ne[1];
int n_vocab = logits->ne[0];
GGML_ASSERT(n_tokens == logits->ne[1]);
GGML_ASSERT(n_batch == logits->ne[2]);
GGML_ASSERT(n_vocab == probs->ne[0]);
GGML_ASSERT(n_tokens == probs->ne[1]);
GGML_ASSERT(n_batch == probs->ne[2]);
for (int k = 0; k < n_batch; ++k) {
struct ggml_tensor * best_samples_k = ggml_view_1d(ctx,
best_samples,
best_samples->ne[0],
k*best_samples->nb[1]);
struct ggml_tensor * logits_k = ggml_view_2d(ctx,
logits,
logits->ne[0],
logits->ne[1],
logits->nb[1],
k*logits->nb[2]);
struct ggml_tensor * probs_k = ggml_view_2d(ctx,
probs,
probs->ne[0],
probs->ne[1],
probs->nb[1],
k*probs->nb[2]);
sample_softmax(logits_k, probs_k, best_samples_k);
}
}
void print_row(struct ggml_tensor * probs, int i) { void print_row(struct ggml_tensor * probs, int i) {
for (int k = 0; k < probs->ne[0]; ++k) { for (int k = 0; k < probs->ne[0]; ++k) {
float p = ggml_get_f32_1d(probs, i*probs->ne[0] + k); float p = ggml_get_f32_1d(probs, i*probs->ne[0] + k);
@ -2116,7 +2050,6 @@ int main(int argc, char ** argv) {
} }
} }
// sample_softmax_batch(ctx0, logits, after_opt_probs, after_opt_best_samples);
// printf("probabilities after optimization:\n"); // printf("probabilities after optimization:\n");
// print_matrix(after_opt_probs); // print_matrix(after_opt_probs);
printf("Example:\n---\n"); printf("Example:\n---\n");
@ -2184,7 +2117,6 @@ int main(int argc, char ** argv) {
(float *) ((char *) logits->data + (sample_ctx-1)*logits->nb[1]), (float *) ((char *) logits->data + (sample_ctx-1)*logits->nb[1]),
(llama_token *) tokens_input->data, (llama_token *) tokens_input->data,
sample_ctx-1); sample_ctx-1);
// sample_softmax(logits, probs, best_samples);
//int token = ggml_get_i32_1d(best_samples, sample_ctx-1); //int token = ggml_get_i32_1d(best_samples, sample_ctx-1);
// print_row(probs, sample_at); // print_row(probs, sample_at);