ikawrakow/ik_llama.cpp
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Kawrakow
2026-01-23 16:35:50 +00:00
parent f5754f5f82
commit 485d23d91c
1 changed files with 49 additions and 34 deletions
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83
src/llama-build-context.cpp
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@@ -1343,12 +1343,18 @@ static ggml_tensor * build_glm45_fa(ggml_context * ctx, ggml_tensor * q, ggml_te
auto ne1 = 8*v->ne[0];
auto ne2 = 4*v->ne[0];
auto q1 = ggml_view_3d(ctx, q, q->ne[0], 8, k->ne[2]*q->ne[1], q->nb[2], q->nb[1]/k->ne[2], 0);
auto q2 = ggml_view_3d(ctx, q, q->ne[0], 4, k->ne[2]*q->ne[1], q->nb[2], q->nb[1]/k->ne[2], 8*q->ne[0]*ggml_element_size(q));
q1 = ggml_reshape_3d(ctx, ggml_cont(ctx, q1), q->ne[0], 8*k->ne[2], q->ne[1]);
q2 = ggml_reshape_3d(ctx, ggml_cont(ctx, q2), q->ne[0], 4*k->ne[2], q->ne[1]);
q1 = ggml_permute(ctx, q1, 0, 2, 1, 3);
q2 = ggml_permute(ctx, q2, 0, 2, 1, 3);
ggml_tensor *q1, *q2;
if (q->ne[1] == 1 && k->ne[2] == 1) {
q1 = ggml_view_3d(ctx, q, q->ne[0], 1, 8, q->nb[1], q->nb[2], 0);
q2 = ggml_view_3d(ctx, q, q->ne[0], 1, 4, q->nb[1], q->nb[2], 8*q->ne[0]*ggml_element_size(q));
} else {
q1 = ggml_view_3d(ctx, q, q->ne[0], 8, k->ne[2]*q->ne[1], q->nb[2], q->nb[1]/k->ne[2], 0);
q2 = ggml_view_3d(ctx, q, q->ne[0], 4, k->ne[2]*q->ne[1], q->nb[2], q->nb[1]/k->ne[2], 8*q->ne[0]*ggml_element_size(q));
q1 = ggml_reshape_3d(ctx, ggml_cont(ctx, q1), q->ne[0], 8*k->ne[2], q->ne[1]);
q2 = ggml_reshape_3d(ctx, ggml_cont(ctx, q2), q->ne[0], 4*k->ne[2], q->ne[1]);
q1 = ggml_permute(ctx, q1, 0, 2, 1, 3);
q2 = ggml_permute(ctx, q2, 0, 2, 1, 3);
}
auto fa1 = ggml_flash_attn_ext(ctx, q1, k, v, kq_mask, kq_scale, 0.0f, 0.0f);
if (should_use_f32_precision) {
@@ -1435,7 +1441,7 @@ static ggml_tensor * llm_build_kqv(
0);
cb(v, "v", il);
if (/*k->ne[1] >= 8192 &&*/ q->ne[2] / k->ne[2] == 12 && !sinks && n_swa == 0 &&
if (q->ne[1] == 1 && k->ne[1] >= 8192 && q->ne[2] / k->ne[2] == 12 && !sinks && n_swa == 0 &&
k->view_src && k->view_src->buffer && !ggml_backend_buffer_is_host(k->view_src->buffer)) {
cur = build_glm45_fa(ctx, q, k, v, kq_mask, kq_scale, should_use_f32_precision);
} else {
@@ -9225,6 +9231,22 @@ ggml_tensor * llm_build_context::build_std_attention(ggml_cgraph * gf, ggml_tens
float freq_base_l = n_swa > 0 ? hparams.rope_freq_base_train_swa : cparams.rope_freq_base;
float freq_scale_l = n_swa > 0 ? hparams.rope_freq_scale_train_swa : hparams.rope_freq_scale_train;
#ifdef GGML_USE_VULKAN
constexpr bool use_f32_precision = true;
#else
constexpr bool use_f32_precision = false;
#endif
bool should_use_f32_precision = use_f32_precision
|| model.arch == LLM_ARCH_PHI2
|| model.arch == LLM_ARCH_PHI3
|| model.arch == LLM_ARCH_GPTNEOX
|| model.arch == LLM_ARCH_QWEN2
|| model.arch == LLM_ARCH_COHERE2
|| model.arch == LLM_ARCH_GLM4
// || model.arch == LLM_ARCH_GLM4_MOE
|| model.arch == LLM_ARCH_MIMO2;
// || (model.arch == LLM_ARCH_DEEPSEEK2 && q->ne[1] <= 8);
if (!model.layers[il].wqkv && !model.layers[il].wqk && cparams.flash_attn &&
model.layers[il].wq->extra && model.layers[il].wk->extra && model.layers[il].wv->extra && model.layers[il].wo->extra) {
@@ -9367,35 +9389,28 @@ ggml_tensor * llm_build_context::build_std_attention(ggml_cgraph * gf, ggml_tens
ggml_row_size(split_vl->type, n_embd_head_v), 0);
cb(v, "v", il_cb);
#ifdef GGML_USE_VULKAN
constexpr bool use_f32_precision = true;
#else
constexpr bool use_f32_precision = false;
#endif
if (/*k->ne[1] >= 8192 &&*/ q->ne[2] / k->ne[2] == 12 && !sinks && n_swa == 0 &&
if (q->ne[1] == 1 && k->ne[1] >= 65536/k->ne[2] && q->ne[2] / k->ne[2] == 12 && !sinks && n_swa == 0 &&
k->view_src && k->view_src->buffer && !ggml_backend_buffer_is_host(k->view_src->buffer)) {
cur = build_glm45_fa(ctx0, q, k, v, KQ_mask, KQ_scale, use_f32_precision);
cur = build_glm45_fa(ctx0, q, k, v, KQ_mask, KQ_scale, should_use_f32_precision);
} else {
cur = ggml_flash_attn_ext(ctx0, q, k, v, KQ_mask, KQ_scale, hparams.f_max_alibi_bias,
hparams.attn_soft_cap ? hparams.f_attn_logit_softcapping : 0.0f);
cb(cur, "flash_attn", il_cb);
if (model.layers[il].attn_sinks && model.layers[il].attn_sinks->extra) {
auto split = (ggml_split_tensor_t *)model.layers[il].attn_sinks->extra;
GGML_ASSERT(split->n_device == wq->n_device);
GGML_ASSERT(split->splits[id]);
ggml_flash_attn_ext_add_sinks(cur, split->splits[id]);
} else {
ggml_flash_attn_ext_add_sinks(cur, sinks);
}
if (n_swa > 0) {
((int32_t *)cur->op_params)[4] = n_swa;
}
// Some models produced NaNs/gibberish when FA is computed with f16 precision on CUDA
if (use_f32_precision || model.arch == LLM_ARCH_PHI2 || model.arch == LLM_ARCH_PHI3 || model.arch == LLM_ARCH_GPTNEOX ||
(model.arch == LLM_ARCH_DEEPSEEK2 && q->ne[1] <= 8) || model.arch == LLM_ARCH_COHERE2 || model.arch == LLM_ARCH_GLM4 ||
model.arch == LLM_ARCH_GLM4_MOE) {
ggml_flash_attn_ext_set_prec(cur, GGML_PREC_F32);
}
cur = ggml_flash_attn_ext(ctx0, q, k, v, KQ_mask, KQ_scale, hparams.f_max_alibi_bias,
hparams.attn_soft_cap ? hparams.f_attn_logit_softcapping : 0.0f);
cb(cur, "flash_attn", il_cb);
if (model.layers[il].attn_sinks && model.layers[il].attn_sinks->extra) {
auto split = (ggml_split_tensor_t *)model.layers[il].attn_sinks->extra;
GGML_ASSERT(split->n_device == wq->n_device);
GGML_ASSERT(split->splits[id]);
ggml_flash_attn_ext_add_sinks(cur, split->splits[id]);
} else {
ggml_flash_attn_ext_add_sinks(cur, sinks);
}
if (n_swa > 0) {
((int32_t *)cur->op_params)[4] = n_swa;
}
// Some models produced NaNs/gibberish when FA is computed with f16 precision on CUDA
if (should_use_f32_precision) {
ggml_flash_attn_ext_set_prec(cur, GGML_PREC_F32);
}
}
cur = ggml_reshape_2d(ctx0, cur, split_wo->ne[0], n_tokens);