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Merged
ggerganov merged 1 commit into from
Jan 2, 2026
+14 −20
Merged

graph : reduce topology branching #18548

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8 changes: 5 additions & 3 deletions src/models/cogvlm.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -3,12 +3,14 @@
llm_build_cogvlm::llm_build_cogvlm(const llama_model & model, const llm_graph_params & params) :
llm_graph_context(params) {
const int64_t n_embd_head = hparams.n_embd_head_v;
float kq_scale = 1.0f / sqrtf(float(n_embd_head));
const float kq_scale = 1.0f / sqrtf(float(n_embd_head));

GGML_ASSERT(n_embd_head == hparams.n_embd_head_k);
GGML_ASSERT(n_embd_head == hparams.n_rot);

ggml_tensor *inpL, *cur;
ggml_tensor * inpL;
ggml_tensor * cur;

inpL = build_inp_embd(model.tok_embd);

ggml_tensor * inp_pos = build_inp_pos();
Expand Down Expand Up @@ -44,7 +46,7 @@ llm_build_cogvlm::llm_build_cogvlm(const llama_model & model, const llm_graph_pa
}

ggml_tensor * inpSA = inpL;
cur = build_norm(inpSA, model.layers[il].attn_norm, NULL, LLM_NORM_RMS, il);
cur = build_norm(inpSA, model.layers[il].attn_norm, NULL, LLM_NORM_RMS, il);

// build self attention
{
Expand Down
8 changes: 2 additions & 6 deletions src/models/gemma-embedding.cpp
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Original file line number Diff line number Diff line change
@@ -1,7 +1,5 @@
#include "models.h"



llm_build_gemma_embedding::llm_build_gemma_embedding(const llama_model & model, const llm_graph_params & params) :
llm_graph_context(params) {
const int64_t n_embd_head = hparams.n_embd_head_k;
Expand All @@ -12,10 +10,8 @@ llm_build_gemma_embedding::llm_build_gemma_embedding(const llama_model & model,
inpL = build_inp_embd(model.tok_embd);

// important: do not normalize weights for raw embeddings input (i.e. encoded image emdeddings)
if (ubatch.token) {
inpL = ggml_scale(ctx0, inpL, sqrtf(n_embd));
cb(inpL, "inp_scaled", -1);
}
inpL = ggml_scale(ctx0, inpL, ubatch.token ? sqrtf(n_embd) : 1.0f);
cb(inpL, "inp_scaled", -1);

// inp_pos - contains the positions
ggml_tensor * inp_pos = build_inp_pos();
Expand Down
7 changes: 3 additions & 4 deletions src/models/gemma3.cpp
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Expand Up @@ -10,10 +10,9 @@ llm_build_gemma3<iswa>::llm_build_gemma3(const llama_model & model, const llm_gr
inpL = build_inp_embd(model.tok_embd);

// important: do not normalize weights for raw embeddings input (i.e. encoded image emdeddings)
if (ubatch.token) {
inpL = ggml_scale(ctx0, inpL, sqrtf(n_embd));
cb(inpL, "inp_scaled", -1);
}
inpL = ggml_scale(ctx0, inpL, ubatch.token ? sqrtf(n_embd) : 1.0f);
cb(inpL, "inp_scaled", -1);

// inp_pos - contains the positions
ggml_tensor * inp_pos = build_inp_pos();

Expand Down
11 changes: 4 additions & 7 deletions src/models/gemma3n-iswa.cpp
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Original file line number Diff line number Diff line change
@@ -1,7 +1,5 @@
#include "models.h"



llm_build_gemma3n_iswa::llm_build_gemma3n_iswa(const llama_model & model, const llm_graph_params & params) :
llm_graph_context(params),
model(model),
Expand All @@ -15,10 +13,9 @@ llm_build_gemma3n_iswa::llm_build_gemma3n_iswa(const llama_model & model, const
inpL = build_inp_embd(model.tok_embd);

// important: do not normalize weights for raw embeddings input (i.e. encoded image emdeddings)
if (ubatch.token) {
inpL = ggml_scale(ctx0, inpL, sqrtf(n_embd));
cb(inpL, "inp_scaled", -1);
}
inpL = ggml_scale(ctx0, inpL, ubatch.token ? sqrtf(n_embd) : 1.0f);
cb(inpL, "inp_scaled", -1);

// inp_pos - contains the positions
ggml_tensor * inp_pos = build_inp_pos();

Expand Down Expand Up @@ -248,7 +245,7 @@ ggml_tensor * llm_build_gemma3n_iswa::view_2d_slice(ggml_tensor * x, int idx) {
// equivalent to get_per_layer_inputs() in python code
// output shape: [n_embd_altup, n_layer, n_tokens]
ggml_tensor * llm_build_gemma3n_iswa::get_per_layer_inputs() {
auto inp = std::make_unique<llm_graph_input_embd>();
auto inp = std::make_unique<llm_graph_input_embd>();
ggml_tensor * inp_per_layer;
if (ubatch.token) {
inp->tokens = ggml_new_tensor_1d(ctx0, GGML_TYPE_I32, ubatch.n_tokens);
Expand Down
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