10000 llama : fix loading models with shared tok_embd and output by slaren · Pull Request #5651 · ggml-org/llama.cpp · GitHub
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llama : fix loading models with shared tok_embd and output #5651

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merged 1 commit into from
Feb 21, 2024
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llama : fix loading models with shared tok_embd and output #5651

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12 changes: 4 additions & 8 deletions llama.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -2791,13 +2791,7 @@ struct llama_model_loader {

std::vector<no_init<uint8_t>> read_buf;

for (int i = 0; i < gguf_get_n_tensors(ctx_gguf); i++) {
struct ggml_tensor * cur = ggml_get_tensor(ctx, gguf_get_tensor_name(ctx_gguf, i));
if (!cur) {
// some tensors may be allocated in a different context
continue;
}

for (struct ggml_tensor * cur = ggml_get_first_tensor(ctx); cur != NULL; cur = ggml_get_next_tensor(ctx, cur)) {
if (progress_callback) {
if (!progress_callback((float) size_done / size_data, progress_callback_user_data)) {
return false;
Expand Down Expand Up @@ -3722,7 +3716,7 @@ static bool llm_load_tensors(
}

// create one context per buffer type
size_t ctx_size = ggml_tensor_overhead()*ml.n_tensors;
size_t ctx_size = ggml_tensor_overhead()*(ml.n_tensors + 1); // +1 for models where tok_embd is duplicated as output
std::map<ggml_backend_buffer_type_t, ggml_context *> ctx_map;
for (auto & it : buft_layer_count) {
struct ggml_init_params params = {
Expand Down Expand Up @@ -3860,6 +3854,7 @@ static bool llm_load_tensors(
} else {
model.output = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}); // needs to be on GPU
ml.n_created--; // artificial tensor
ml.size_data += ggml_nbytes(model.output);
}
}

Expand Down Expand Up @@ -4396,6 +4391,7 @@ static bool llm_load_tensors(
model.output_norm = ml.create_tensor(ctx_output, tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd});
model.output = ml.create_tensor(ctx_output, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}); // same as tok_embd, duplicated to allow offloading
ml.n_created--; // artificial tensor
ml.size_data += ggml_nbytes(model.output);

const int64_t n_ff = hparams.n_ff;
const int64_t n_embd_head_k = hparams.n_embd_head_k;
Expand Down
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