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llama : fix names [no ci]

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Georgi Gerganov 2025-01-15 13:35:56 +02:00
parent 40b521b656
commit 0c9f5aff83
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GPG Key ID: 449E073F9DC10735
1 changed files with 12 additions and 12 deletions
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src/llama.cpp
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@ -1373,9 +1373,9 @@ struct llm_build_context {
inp = ggml_graph_node(gf, i);
if (strcmp(inp->name, "result_norm") == 0 || strcmp(inp->name, "result_embd") == 0) {
break;
} else {
inp = nullptr;
}
inp = nullptr;
}
GGML_ASSERT(inp != nullptr && "missing result_norm/result_embd tensor");
@ -1431,7 +1431,7 @@ struct llm_build_context {
return gf;
}
struct ggml_tensor * llm_build_pos_bucket(bool causal) {
struct ggml_tensor * build_pos_bucket(bool causal) {
if (causal) {
lctx.inp_pos_bucket = ggml_new_tensor_2d(ctx0, GGML_TYPE_I32, n_kv, n_tokens);
} else {
@ -1444,7 +1444,7 @@ struct llm_build_context {
return lctx.inp_pos_bucket;
}
struct ggml_tensor * llm_build_pos_bias(struct ggml_tensor * pos_bucket, struct ggml_tensor * attn_rel_b) {
struct ggml_tensor * build_pos_bias(struct ggml_tensor * pos_bucket, struct ggml_tensor * attn_rel_b) {
struct ggml_tensor * pos_bucket_1d = ggml_view_1d(ctx0, pos_bucket, pos_bucket->ne[0] * pos_bucket->ne[1], 0);
cb(pos_bucket_1d, "pos_bucket_1d", -1);
@ -1463,7 +1463,7 @@ struct llm_build_context {
return pos_bias;
}
struct ggml_tensor * llm_build_inp_embd_enc() {
struct ggml_tensor * build_inp_embd_enc() {
const int64_t n_embd = hparams.n_embd;
lctx.inp_embd_enc = ggml_new_tensor_2d(ctx0, GGML_TYPE_F32, n_embd, n_outputs_enc);
ggml_set_input(lctx.inp_embd_enc);
@ -1471,7 +1471,7 @@ struct llm_build_context {
return lctx.inp_embd_enc;
}
struct ggml_tensor * llm_build_inp_KQ_mask_cross() {
struct ggml_tensor * build_inp_KQ_mask_cross() {
lctx.inp_KQ_mask_cross = ggml_new_tensor_2d(ctx0, GGML_TYPE_F32, n_outputs_enc, GGML_PAD(n_tokens, GGML_KQ_MASK_PAD));
ggml_set_input(lctx.inp_KQ_mask_cross);
cb(lctx.inp_KQ_mask_cross, "KQ_mask_cross", -1);
@ -6775,7 +6775,7 @@ struct llm_build_context {
inpL = llm_build_inp_embd(ctx0, lctx, hparams, ubatch, model.tok_embd, cb);
GGML_ASSERT(lctx.is_encoding);
struct ggml_tensor * pos_bucket_enc = llm_build_pos_bucket(false);
struct ggml_tensor * pos_bucket_enc = build_pos_bucket(false);
// KQ_mask (mask for 1 head, it will be broadcasted to all heads)
struct ggml_tensor * KQ_mask_enc = build_inp_KQ_mask(false);
@ -6810,7 +6810,7 @@ struct llm_build_context {
cb(kq, "kq", il);
struct ggml_tensor * attn_rel_b = model.layers[il].attn_rel_b_enc ? model.layers[il].attn_rel_b_enc : model.layers[0].attn_rel_b_enc;
struct ggml_tensor * pos_bias = llm_build_pos_bias(pos_bucket_enc, attn_rel_b);
struct ggml_tensor * pos_bias = build_pos_bias(pos_bucket_enc, attn_rel_b);
struct ggml_tensor * kq_b = ggml_add(ctx0, kq, pos_bias);
cb(kq_b, "kq_b", il);
@ -6909,11 +6909,11 @@ struct llm_build_context {
GGML_ASSERT(!lctx.is_encoding);
GGML_ASSERT(n_outputs_enc > 0 && "call llama_encode() first");
struct ggml_tensor * embd_enc = llm_build_inp_embd_enc();
struct ggml_tensor * pos_bucket_dec = llm_build_pos_bucket(true);
struct ggml_tensor * embd_enc = build_inp_embd_enc();
struct ggml_tensor * pos_bucket_dec = build_pos_bucket(true);
struct ggml_tensor * KQ_mask_dec = build_inp_KQ_mask();
struct ggml_tensor * KQ_mask_cross = llm_build_inp_KQ_mask_cross();
struct ggml_tensor * KQ_mask_cross = build_inp_KQ_mask_cross();
for (int il = 0; il < n_layer; ++il) {
struct ggml_tensor * inpSA = inpL;
@ -6961,7 +6961,7 @@ struct llm_build_context {
cb(kq, "kq", il);
struct ggml_tensor * attn_rel_b = model.layers[il].attn_rel_b ? model.layers[il].attn_rel_b : model.layers[0].attn_rel_b;
struct ggml_tensor * pos_bias = llm_build_pos_bias(pos_bucket_dec, attn_rel_b);
struct ggml_tensor * pos_bias = build_pos_bias(pos_bucket_dec, attn_rel_b);
struct ggml_tensor * kq_b = ggml_add(ctx0, kq, pos_bias);
cb(kq_b, "kq_b", il);