ikawrakow/ik_llama.cpp
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Kawrakow
2026-02-23 09:42:21 +00:00
parent fd2a70913c
commit 35da97d53e
1 changed files with 4 additions and 20 deletions
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24
src/llama-build-context.cpp
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@@ -4463,31 +4463,16 @@ ggml_cgraph * llm_build_context::build_qwen3next() {
if (hparams.is_recurrent(il)) {
int idx = model.default_layer_device[il];
if (inpL->op == GGML_OP_REDUCE) {
if (model.layers[il].wqkv) {
int idx_wqkv = ggml_backend_sched_get_backend_idx(lctx.sched, model.layers[il].wqkv->buffer);
//int idx_s_l = -1;
//if (kv_self.s_l[il]) idx_s_l = ggml_backend_sched_get_backend_idx(lctx.sched, kv_self.s_l[il]->buffer);
//printf("Layer %2d: %d, %d, %d\n", il, idx, idx_wqkv, idx_s_l);
if (idx_wqkv >= 0) idx = idx_wqkv;
if (kv_self.s_l[il]) {
// This shouldn't be necessary, but just in case.
int idx_s_l = ggml_backend_sched_get_backend_idx(lctx.sched, kv_self.s_l[il]->buffer);
if (idx_s_l >= 0) idx = idx_s_l;
}
if (inpL->src[idx]) {
inpL->view_src = inpL->src[idx];
}
}
auto norm = model.layers[il].attn_norm->extra ? ((ggml_split_tensor_t *)model.layers[il].attn_norm->extra)->splits[idx] : model.layers[il].attn_norm;
//if (inpL->op == GGML_OP_REDUCE && inpL->src[model.default_layer_device[il]]) {
// if (model.layers[il].wqkv) {
// int idx = ggml_backend_sched_get_backend_idx(lctx.sched, model.layers[il].wqkv->buffer);
// printf("Layer %2d wqkv backend is %d\n", il, idx);
// //auto backend = ggml_backend_sched_get_tensor_backend(lctx.sched, model.layers[il].wqkv);
// //if (backend) printf("Layer %2d wqkv backend is %s\n", il, ggml_backend_name(backend));
// //else printf("Backend for wqkv in layer %2d is not known\n", il);
// }
// inpL->view_src = inpL->src[model.default_layer_device[il]];
// //printf("Using reduce result on device %d\n", model.default_layer_device[il]);
// //inpL = inpL->src[model.default_layer_device[il]];
//}
//auto norm = model.layers[il].attn_norm->extra ? ((ggml_split_tensor_t *)model.layers[il].attn_norm->extra)->splits[model.default_layer_device[il]] : model.layers[il].attn_norm;
cur = llm_build_norm(ctx0, inpL, hparams, norm, nullptr, LLM_NORM_RMS, cb, il);
cb(cur, "attn_norm", il);
cur = delta.build_layer_attn_linear(ctx0, gf, cur, causal_mask, identity, diag_mask, il, cb);
@@ -4498,7 +4483,6 @@ ggml_cgraph * llm_build_context::build_qwen3next() {
cur = ggml_add(ctx0, cur, inpSA);
cb(cur, "attn_residual", il);
} else {
//cur = build_layer_attn(cur, inp_pos, KQ_mask, il);
cur = build_std_attention(gf, model.layers[il].attn_norm, inpL, inp_pos, il == n_layer - 1 ? inp_out_ids : nullptr, nullptr,
KQ_mask, nullptr, nullptr, KQ_scale, 0.0f, 0, il, true, false, true, false, false);
}