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synced 2026-08-12 22:31:11 +04:00
fit: Fix memory allocation for MTP layers (#26605)
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+4
-1
@@ -136,7 +136,10 @@ static std::vector<llama_device_memory_data> common_get_device_memory_data_impl(
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devs.push_back(llama_model_get_device(model, i));
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}
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hp_ngl = llama_model_n_layer(model) + llama_model_n_layer_nextn(model);
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hp_ngl = llama_model_n_layer(model);
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if (mparams->load_mtp) {
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hp_ngl += llama_model_n_layer_nextn(model);
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}
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hp_n_ctx_train = llama_model_n_ctx_train(model);
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hp_n_expert = llama_model_n_expert(model);
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@@ -2890,6 +2890,21 @@ void llama_model_base::create_tensor_qkv(llama_layer & layer, int bid,
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int64_t n_embd_, int64_t n_embd_q_, int64_t n_embd_k_, int64_t n_embd_v_,
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int flags) {
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const int64_t n_embd_qkv = n_embd_q_ + n_embd_k_ + n_embd_v_;
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if (flags & TENSOR_SKIP) {
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const int skip = TENSOR_NOT_REQUIRED | TENSOR_SKIP;
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create_tensor(tn(LLM_TENSOR_ATTN_QKV, "weight", bid), {n_embd_, n_embd_qkv}, skip | TENSOR_SKIP_IF_VIRTUAL);
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create_tensor(tn(LLM_TENSOR_ATTN_QKV, "bias", bid), {n_embd_qkv}, skip | TENSOR_SKIP_IF_VIRTUAL);
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create_tensor(tn(LLM_TENSOR_ATTN_Q, "weight", bid), {n_embd_, n_embd_q_}, skip);
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create_tensor(tn(LLM_TENSOR_ATTN_K, "weight", bid), {n_embd_, n_embd_k_}, skip);
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create_tensor(tn(LLM_TENSOR_ATTN_V, "weight", bid), {n_embd_, n_embd_v_}, skip);
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create_tensor(tn(LLM_TENSOR_ATTN_Q, "bias", bid), {n_embd_q_}, skip);
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create_tensor(tn(LLM_TENSOR_ATTN_K, "bias", bid), {n_embd_k_}, skip);
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create_tensor(tn(LLM_TENSOR_ATTN_V, "bias", bid), {n_embd_v_}, skip);
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return;
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}
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layer.wqkv = create_tensor(tn(LLM_TENSOR_ATTN_QKV, "weight", bid), {n_embd_, n_embd_qkv}, TENSOR_NOT_REQUIRED | TENSOR_SKIP_IF_VIRTUAL);
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if (layer.wqkv) {
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layer.wqkv_b = create_tensor(tn(LLM_TENSOR_ATTN_QKV, "bias", bid), {n_embd_qkv}, TENSOR_NOT_REQUIRED | TENSOR_SKIP_IF_VIRTUAL);
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