llama: refactor fused ops (#24646)
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+8
-1
@@ -1192,6 +1192,7 @@ void llm_graph_result::reset() {
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params = {};
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inputs.clear();
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fused_nodes.clear();
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buf_compute_meta.resize(ggml_tensor_overhead()*max_nodes + ggml_graph_overhead_custom(max_nodes, false));
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@@ -1293,6 +1294,10 @@ llm_graph_input_i * llm_graph_result::add_input(llm_graph_input_ptr input) {
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return inputs.back().get();
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}
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void llm_graph_result::add_fused_node(llm_graph_fused_node result) {
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fused_nodes.push_back(result);
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}
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void llm_graph_result::set_params(const llm_graph_params & params) {
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this->params = params;
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}
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@@ -1352,6 +1357,8 @@ void llm_graph_context::cb(ggml_tensor * cur, const char * name, int il) const {
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}
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}
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ggml_tensor * llm_graph_context::build_cvec(
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ggml_tensor * cur,
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int il) const {
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@@ -2402,7 +2409,7 @@ ggml_tensor * llm_graph_context::build_attn_mha(
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cur = ggml_flash_attn_ext(ctx0, q, k, v, kq_mask, kq_scale, hparams.f_max_alibi_bias,
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hparams.attn_soft_cap ? hparams.f_attn_logit_softcapping : 0.0f);
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cb(cur, LLAMA_TENSOR_NAME_FATTN, il);
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res->add_fused_node({LLM_FUSED_OP_FLASH_ATTN, cur, il});
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ggml_flash_attn_ext_add_sinks(cur, sinks);
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ggml_flash_attn_ext_set_prec (cur, GGML_PREC_F32);
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