ikawrakow/ik_llama.cpp
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gpt-oss: CPU seems to be working

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It was the SWA thta was missing in the previous commit.

There are issues with EOG tokens, so this still needs to be added.
This commit is contained in:
Iwan Kawrakow
2025-08-10 13:13:05 +03:00
parent c69d04f324
commit 42bed31488
1 changed files with 15 additions and 26 deletions
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41
src/llama.cpp
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@@ -18159,22 +18159,27 @@ struct llm_build_context {
// inp_pos - contains the positions
ggml_tensor * inp_pos = build_inp_pos();
struct ggml_tensor * KQ_mask = build_inp_KQ_mask();
struct ggml_tensor * KQ_mask = build_inp_KQ_mask();
struct ggml_tensor * KQ_mask_swa = build_inp_KQ_mask_swa();
//const int64_t n_embd_head = hparams.n_embd_head_v;
const float kq_scale = 1.0f / sqrtf(float(n_rot)); //float(n_embd_head));
//auto * inp_attn = build_attn_inp_kv_unified_iswa();
const int sliding_window_pattern = 2;
for (int il = 0; il < n_layer; ++il) {
const bool is_sliding = il % sliding_window_pattern < (sliding_window_pattern - 1);
ggml_tensor * inpSA = inpL;
struct ggml_tensor * KQ_mask_l = is_sliding ? KQ_mask_swa : KQ_mask;
// norm
cur = llm_build_norm(ctx0, inpL, hparams, model.layers[il].attn_norm, nullptr, LLM_NORM_RMS, cb, il);
cb(cur, "attn_norm", il);
// self-attention
{
// compute Q and K and RoPE them
ggml_tensor * Qcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wq, cur);
cb(Qcur, "Qcur", il);
if (model.layers[il].bq) {
@@ -18196,31 +18201,18 @@ struct llm_build_context {
cb(Vcur, "Vcur", il);
}
Qcur = ggml_reshape_3d(ctx0, Qcur, n_rot, n_head, n_tokens);
Kcur = ggml_reshape_3d(ctx0, Kcur, n_rot, n_head_kv, n_tokens);
//Vcur = ggml_reshape_3d(ctx0, Vcur, n_rot, n_head_kv, n_tokens);
Qcur = ggml_rope_ext(
ctx0, Qcur, inp_pos, nullptr,
n_rot, rope_type, n_ctx_orig, freq_base, freq_scale,
ext_factor, attn_factor, beta_fast, beta_slow
);
Kcur = ggml_rope_ext(
ctx0, Kcur, inp_pos, nullptr,
n_rot, rope_type, n_ctx_orig, freq_base, freq_scale,
ext_factor, attn_factor, beta_fast, beta_slow
);
Qcur = ggml_rope_ext(ctx0, ggml_reshape_3d(ctx0, Qcur, n_rot, n_head, n_tokens), inp_pos, nullptr,
n_rot, rope_type, n_ctx_orig, freq_base, freq_scale, ext_factor, attn_factor,
beta_fast, beta_slow);
cb(Qcur, "Qcur", il);
Kcur = ggml_rope_ext(ctx0, ggml_reshape_3d(ctx0, Kcur, n_rot, n_head_kv, n_tokens), inp_pos, nullptr,
n_rot, rope_type, n_ctx_orig, freq_base, freq_scale, ext_factor,
attn_factor, beta_fast, beta_slow);
cb(Kcur, "Kcur", il);
//cb(Vcur, "Vcur", il);
cur = llm_build_kv(ctx0, lctx, kv_self, gf, model.layers[il].wo, model.layers[il].bo,
Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, kq_scale, cb, il, model.layers[il].attn_sinks);
//cur = build_attn_with_sinks(inp_attn,
// model.layers[il].wo, model.layers[il].bo,
// Qcur, Kcur, Vcur, nullptr, nullptr, model.layers[il].attn_sinks, 1.0f/sqrtf(float(n_rot)), il);
Kcur, Vcur, Qcur, KQ_mask_l, n_tokens, kv_head, n_kv, kq_scale, cb, il, model.layers[il].attn_sinks);
cb(cur, "attn_out", il);
}
@@ -18266,13 +18258,10 @@ struct llm_build_context {
cur = llm_build_norm(ctx0, cur, hparams, model.output_norm, nullptr, LLM_NORM_RMS, cb, -1);
cb(cur, "result_norm", -1);
//res->t_embd = cur;
// lm_head
cur = llm_build_lora_mm(lctx, ctx0, model.output, cur);
cb(cur, "result_output", -1);
//res->t_logits = cur;
ggml_build_forward_expand(gf, cur);