vbatts/llama.cpp
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minor : clear whitespaces

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Georgi Gerganov 2024-04-03 21:04:47 +03:00 • committed by GitHub
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commit 40dd64ae77
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1 changed files with 4 additions and 5 deletions
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llama.cpp
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@ -4789,7 +4789,7 @@ static bool llm_load_tensors(
layer.attn_q_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q_NORM, "bias", i), {n_embd}, false); layer.attn_q_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q_NORM, "bias", i), {n_embd}, false);
layer.attn_k_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K_NORM, "weight", i), {n_embd}, false); layer.attn_k_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K_NORM, "weight", i), {n_embd}, false);
layer.attn_k_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K_NORM, "bias", i), {n_embd}, false); layer.attn_k_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K_NORM, "bias", i), {n_embd}, false);
// AWQ ScaleActivation layer // AWQ ScaleActivation layer
layer.ffn_act = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_ACT, "scales", i), {n_ff}, false); layer.ffn_act = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_ACT, "scales", i), {n_ff}, false);
@ -7616,14 +7616,14 @@ struct llm_build_context {
// positions of the tokens in the KV cache // positions of the tokens in the KV cache
struct ggml_tensor * KQ_pos = build_inp_KQ_pos(); struct ggml_tensor * KQ_pos = build_inp_KQ_pos();
if (model.pos_embd){ if (model.pos_embd) {
// inp_pos - contains the positions // inp_pos - contains the positions
struct ggml_tensor * inp_pos = build_inp_pos(); struct ggml_tensor * inp_pos = build_inp_pos();
pos = ggml_get_rows(ctx0, model.pos_embd, inp_pos); pos = ggml_get_rows(ctx0, model.pos_embd, inp_pos);
cb(pos, "pos_embd", -1); cb(pos, "pos_embd", -1);
inpL = ggml_add(ctx0, inpL, pos); inpL = ggml_add(ctx0, inpL, pos);
cb(inpL, "inpL", -1); cb(inpL, "inpL", -1);
} }
for (int il = 0; il < n_layer; ++il) { for (int il = 0; il < n_layer; ++il) {
@ -7673,14 +7673,13 @@ struct llm_build_context {
model.layers[il].attn_k_norm_b, model.layers[il].attn_k_norm_b,
LLM_NORM, cb, il); LLM_NORM, cb, il);
cb(Kcur, "Kcur", il); cb(Kcur, "Kcur", il);
Qcur = ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens); Qcur = ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens);
Kcur = ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens); Kcur = ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens);
cur = llm_build_kv(ctx0, model, hparams, kv_self, gf, cur = llm_build_kv(ctx0, model, hparams, kv_self, gf,
model.layers[il].wo, model.layers[il].bo, model.layers[il].wo, model.layers[il].bo,
Kcur, Vcur, Qcur, KQ_mask, nullptr, n_ctx, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); Kcur, Vcur, Qcur, KQ_mask, nullptr, n_ctx, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il);
} else { } else {
Qcur = ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens); Qcur = ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens);
cur = llm_build_kv(ctx0, model, hparams, kv_self, gf, cur = llm_build_kv(ctx0, model, hparams, kv_self, gf,