From afbf2ef3e263e5bee3150cf9c422039aa406f10d Mon Sep 17 00:00:00 2001 From: Kawrakow Date: Sat, 19 Oct 2024 18:52:58 +0200 Subject: Bitnet: make the scale tensors optional (#97) Co-authored-by: Iwan Kawrakow --- src/llama.cpp | 19 ++++++++++++------- 1 file changed, 12 insertions(+), 7 deletions(-) (limited to 'src/llama.cpp') diff --git a/src/llama.cpp b/src/llama.cpp index 0aaedb96..c950a46d 100644 --- a/src/llama.cpp +++ b/src/llama.cpp @@ -7443,23 +7443,23 @@ static bool llm_load_tensors( layer.attn_sub_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_SUB_NORM, "weight", i), {n_embd}); layer.wq = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_Q, "weight", i), {n_embd, n_embd}); - layer.wq_scale = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_Q, "scale", i), {1}); + layer.wq_scale = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_Q, "scale", i), {1}, llama_model_loader::TENSOR_NOT_REQUIRED); layer.wk = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_K, "weight", i), {n_embd, n_embd_gqa}); - layer.wk_scale = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_K, "scale", i), {1}); + layer.wk_scale = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_K, "scale", i), {1}, llama_model_loader::TENSOR_NOT_REQUIRED); layer.wv = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_V, "weight", i), {n_embd, n_embd_gqa}); - layer.wv_scale = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_V, "scale", i), {1}); + layer.wv_scale = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_V, "scale", i), {1}, llama_model_loader::TENSOR_NOT_REQUIRED); layer.wo = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd, n_embd}); - layer.wo_scale = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "scale", i), {1}); + layer.wo_scale = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "scale", i), {1}, llama_model_loader::TENSOR_NOT_REQUIRED); layer.ffn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd}); layer.ffn_sub_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_SUB_NORM, "weight", i), {n_ff}); layer.ffn_gate = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE, "weight", i), {n_embd, n_ff}); - layer.ffn_gate_scale = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE, "scale", i), {1}); + layer.ffn_gate_scale = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE, "scale", i), {1}, llama_model_loader::TENSOR_NOT_REQUIRED); layer.ffn_down = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN, "weight", i), {n_ff, n_embd}); - layer.ffn_down_scale = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN, "scale", i), {1}); + layer.ffn_down_scale = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN, "scale", i), {1}, llama_model_loader::TENSOR_NOT_REQUIRED); layer.ffn_up = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP, "weight", i), {n_embd, n_ff}); - layer.ffn_up_scale = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP, "scale", i), {1}); + layer.ffn_up_scale = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP, "scale", i), {1}, llama_model_loader::TENSOR_NOT_REQUIRED); } } break; case LLM_ARCH_T5: @@ -7770,6 +7770,11 @@ static bool llm_load_tensors( if (model.arch == LLM_ARCH_BITNET) { auto set_scale = [] (ggml_tensor * w, ggml_tensor * s) { + if (!s) { + float one = 1; + std::memcpy(w->op_params, &one, sizeof(one)); + return; + } float scale = 1; if (ggml_backend_buffer_is_host(s->buffer)) { scale = *(const float *)s->data; -- cgit v1.2.3