vbatts/llama.cpp
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ggml : remove ggml_cplan + rework ggml_cgraph

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ggml-ci
This commit is contained in:
Georgi Gerganov 2024-09-11 13:05:10 +03:00
parent ee154457dd
commit 119e0bc9ae
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GPG key ID: 449E073F9DC10735
10 changed files with 248 additions and 175 deletions
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28
examples/baby-llama/baby-llama.cpp
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@ -17,17 +17,6 @@ constexpr float rms_norm_eps = LLAMA_DEFAULT_RMS_EPS;
constexpr float rms_norm_eps = 5e-6f;
#endif
static void ggml_graph_compute_helper(std::vector<uint8_t> & buf, ggml_cgraph * graph, int n_threads) {
struct ggml_cplan plan = ggml_graph_plan(graph, n_threads, nullptr);
if (plan.work_size > 0) {
buf.resize(plan.work_size);
plan.work_data = buf.data();
}
ggml_graph_compute(graph, &plan);
}
static struct ggml_tensor * randomize_tensor(
struct ggml_tensor * tensor, int ndims, const int64_t ne[], float fmin, float fmax
) {
@ -1514,8 +1503,6 @@ int main(int argc, char ** argv) {
int n_tokens = model.hparams.n_ctx;
int n_vocab = model.hparams.n_vocab;
std::vector<uint8_t> work_buffer;
for (int ex=0; ex<n_examples; ++ex) {
struct ggml_init_params params = {
/*.mem_size =*/ compute_size,
@ -1542,7 +1529,10 @@ int main(int argc, char ** argv) {
struct ggml_tensor * e = square_error_loss(ctx0, targets, logits);
ggml_build_forward_expand(gf, e);
ggml_graph_compute_helper(work_buffer, gf, /*n_threads*/ 1);
ggml_graph_prepare(gf, 1, nullptr);
ggml_graph_work_init(gf, nullptr);
ggml_graph_compute(gf);
ggml_graph_work_free(gf);
float error_before_opt = ggml_get_f32_1d(e, 0);
@ -1553,7 +1543,10 @@ int main(int argc, char ** argv) {
ggml_opt(ctx0, opt_params_lbfgs, e);
//
ggml_build_forward_expand(gf, e);
ggml_graph_compute_helper(work_buffer, gf, /*n_threads*/ 1);
ggml_graph_prepare(gf, 1, nullptr);
ggml_graph_work_init(gf, nullptr);
ggml_graph_compute(gf);
ggml_graph_work_free(gf);
float error_after_opt = ggml_get_f32_1d(e, 0);
@ -1607,7 +1600,10 @@ int main(int argc, char ** argv) {
struct ggml_tensor * logits = forward(&model, &kv_self, ctx0, gf, tokens_input, sample_ctx, n_past);
ggml_build_forward_expand(gf, logits);
ggml_graph_compute_helper(work_buffer, gf, /*n_threads*/ 1);
ggml_graph_prepare(gf, 1, nullptr);
ggml_graph_work_init(gf, nullptr);
ggml_graph_compute(gf);
ggml_graph_work_free(gf);
struct ggml_tensor * best_samples = ggml_new_tensor_1d(ctx0, GGML_TYPE_I32, sample_ctx);
struct ggml_tensor * probs = ggml_new_tensor_2d(ctx0, GGML_TYPE_F32, n_vocab, sample_ctx);