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finetune : keep allocs alive until all allocations are done (#4486)

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slaren 2023-12-17 16:05:56 +01:00 committed by GitHub
parent 0ffc92d2d2
commit 45668633fd
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1 changed files with 7 additions and 8 deletions
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15
examples/finetune/finetune.cpp
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@ -1620,8 +1620,6 @@ int main(int argc, char ** argv) {
opt->params.adam.gclip = params.common.adam_gclip; opt->params.adam.gclip = params.common.adam_gclip;
opt->params.adam.eps_f = params.common.adam_eps_f; opt->params.adam.eps_f = params.common.adam_eps_f;
ggml_allocr * alloc = NULL;
printf("%s: init model\n", __func__); printf("%s: init model\n", __func__);
bool existed = load_checkpoint_lora_file(params.common.fn_checkpoint_in, &model, &lora, train); bool existed = load_checkpoint_lora_file(params.common.fn_checkpoint_in, &model, &lora, train);
@ -1725,10 +1723,9 @@ int main(int argc, char ** argv) {
// allocate input tensors // allocate input tensors
mem_input_data.resize(max_input_size); mem_input_data.resize(max_input_size);
alloc = ggml_allocr_new(mem_input_data.data(), mem_input_data.size(), tensor_alignment); ggml_allocr_t alloc_inps = ggml_allocr_new(mem_input_data.data(), mem_input_data.size(), tensor_alignment);
ggml_allocr_alloc(alloc, tokens_input); ggml_allocr_alloc(alloc_inps, tokens_input);
ggml_allocr_alloc(alloc, target_probs); ggml_allocr_alloc(alloc_inps, target_probs);
ggml_allocr_free(alloc);
// context for compute tensors without their data // context for compute tensors without their data
const size_t estimated_compute_size_wo_data = ( const size_t estimated_compute_size_wo_data = (
@ -1755,7 +1752,7 @@ int main(int argc, char ** argv) {
// find best evaluation order // find best evaluation order
for (unsigned order = 0; order < (unsigned) GGML_CGRAPH_EVAL_ORDER_COUNT; ++order) { for (unsigned order = 0; order < (unsigned) GGML_CGRAPH_EVAL_ORDER_COUNT; ++order) {
ctx_compute = ggml_init(ctx_compute_params); ctx_compute = ggml_init(ctx_compute_params);
alloc = ggml_allocr_new_measure(tensor_alignment); ggml_allocr_t alloc = ggml_allocr_new_measure(tensor_alignment);
gf = ggml_new_graph_custom(ctx_compute, LLAMA_TRAIN_MAX_NODES, true); gf = ggml_new_graph_custom(ctx_compute, LLAMA_TRAIN_MAX_NODES, true);
gf->order = (enum ggml_cgraph_eval_order) order; gf->order = (enum ggml_cgraph_eval_order) order;
gb = ggml_new_graph_custom(ctx_compute, LLAMA_TRAIN_MAX_NODES, true); gb = ggml_new_graph_custom(ctx_compute, LLAMA_TRAIN_MAX_NODES, true);
@ -1788,7 +1785,7 @@ int main(int argc, char ** argv) {
// allocate compute tensors // allocate compute tensors
mem_compute_data.resize(max_compute_size); mem_compute_data.resize(max_compute_size);
ctx_compute = ggml_init(ctx_compute_params); ctx_compute = ggml_init(ctx_compute_params);
alloc = ggml_allocr_new(mem_compute_data.data(), mem_compute_data.size(), tensor_alignment); ggml_allocr_t alloc = ggml_allocr_new(mem_compute_data.data(), mem_compute_data.size(), tensor_alignment);
gf = ggml_new_graph_custom(ctx_compute, LLAMA_TRAIN_MAX_NODES, true); gf = ggml_new_graph_custom(ctx_compute, LLAMA_TRAIN_MAX_NODES, true);
gf->order = best_order; gf->order = best_order;
gb = ggml_new_graph_custom(ctx_compute, LLAMA_TRAIN_MAX_NODES, true); gb = ggml_new_graph_custom(ctx_compute, LLAMA_TRAIN_MAX_NODES, true);
@ -1804,6 +1801,8 @@ int main(int argc, char ** argv) {
params.common.use_checkpointing params.common.use_checkpointing
); );
ggml_allocr_free(alloc); ggml_allocr_free(alloc);
ggml_allocr_free(alloc_inps);
// tokenize data // tokenize data
std::vector<llama_token> train_tokens; std::vector<llama_token> train_tokens;