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llama : profiling the attention compute
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22c69a2794
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18
llama.cpp
18
llama.cpp
@ -5815,6 +5815,24 @@ static struct ggml_cgraph * llama_build_graph(
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GGML_ASSERT(false);
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}
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#if 1
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for (int i = 0; i < result->n_nodes; ++i) {
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struct ggml_tensor * node = result->nodes[i];
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if (getenv("SKIP_KQ_ALL")) {
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if (
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strcmp(node->name, "KQ") == 0 ||
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strcmp(node->name, "KQ_scaled") == 0 ||
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strcmp(node->name, "KQ_masked") == 0 ||
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strcmp(node->name, "KQ_soft_max") == 0 ||
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strcmp(node->name, "KQV") == 0 ||
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false) {
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//printf("skipping %s\n", dst->name);
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node->op = GGML_OP_NONE;
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}
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}
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}
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#endif
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return result;
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}
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