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finetune : fix ggml_allocr lifetimes (tmp workaround) (#5033)
* Fix issue with alloc causing max_compute_size to be calculated * remove ggml_allocr_free as suggested in issue #4791
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@ -263,7 +263,6 @@ static void init_model(struct my_llama_model * model) {
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model->data.resize(size + tensor_alignment);
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model->data.resize(size + tensor_alignment);
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alloc = ggml_allocr_new(model->data.data(), model->data.size(), tensor_alignment);
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alloc = ggml_allocr_new(model->data.data(), model->data.size(), tensor_alignment);
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alloc_model(alloc, model);
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alloc_model(alloc, model);
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ggml_allocr_free(alloc);
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}
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}
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static void randomize_model(struct my_llama_model * model, int seed, float mean, float std, float min, float max) {
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static void randomize_model(struct my_llama_model * model, int seed, float mean, float std, float min, float max) {
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@ -1102,7 +1101,6 @@ int main(int argc, char ** argv) {
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alloc = ggml_allocr_new(mem_input_data.data(), mem_input_data.size(), tensor_alignment);
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alloc = ggml_allocr_new(mem_input_data.data(), mem_input_data.size(), tensor_alignment);
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ggml_allocr_alloc(alloc, tokens_input);
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ggml_allocr_alloc(alloc, tokens_input);
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ggml_allocr_alloc(alloc, target_probs);
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ggml_allocr_alloc(alloc, target_probs);
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ggml_allocr_free(alloc);
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// context for compute tensors without their data
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// context for compute tensors without their data
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const size_t estimated_compute_size_wo_data = (
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const size_t estimated_compute_size_wo_data = (
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@ -1149,7 +1147,6 @@ int main(int argc, char ** argv) {
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best_compute_size = max_compute_size;
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best_compute_size = max_compute_size;
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best_order = gf->order;
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best_order = gf->order;
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}
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}
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ggml_allocr_free(alloc);
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ggml_free(ctx_compute);
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ggml_free(ctx_compute);
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}
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}
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size_t max_compute_size = best_compute_size;
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size_t max_compute_size = best_compute_size;
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@ -1177,7 +1174,6 @@ int main(int argc, char ** argv) {
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params.common.use_flash,
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params.common.use_flash,
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params.common.use_checkpointing
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params.common.use_checkpointing
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);
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);
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ggml_allocr_free(alloc);
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std::vector<llama_token> train_tokens;
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std::vector<llama_token> train_tokens;
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std::vector<size_t> train_samples_begin;
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std::vector<size_t> train_samples_begin;
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