45 lines
1.9 KiB
Diff
45 lines
1.9 KiB
Diff
diff --git a/src/llama.cpp b/src/llama.cpp
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index 1fe2b9f7..a43312a7 100644
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--- a/src/llama.cpp
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+++ b/src/llama.cpp
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@@ -13689,7 +13689,7 @@ static size_t llama_output_reserve(llama_context & lctx, size_t n_outputs) {
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const auto n_embd = hparams.n_embd;
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// TODO: use a per-batch flag for logits presence instead
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- const bool has_logits = !cparams.embeddings;
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+ const bool has_logits = cparams.causal_attn;
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const bool has_embd = lctx.is_encoding || (cparams.embeddings && (cparams.pooling_type == LLAMA_POOLING_TYPE_NONE));
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const size_t logits_size = has_logits ? n_vocab*n_outputs_max : 0;
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@@ -13959,17 +13959,25 @@ static int llama_decode_internal(
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// no output
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res = nullptr;
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embd = nullptr;
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- } else if (cparams.embeddings) {
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- res = nullptr; // do not extract logits for embedding case
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- embd = gf->nodes[gf->n_nodes - 1];
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- if (strcmp(embd->name, "result_embd_pooled") != 0) {
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- embd = gf->nodes[gf->n_nodes - 2];
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+ }
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+
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+ if (cparams.embeddings) {
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+ for (int i = gf->n_nodes - 1; i >= 0; --i) {
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+ embd = gf->nodes[i];
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+ if (strcmp(embd->name, "result_embd_pooled") == 0) {
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+ break;
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+ }
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}
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GGML_ASSERT(strcmp(embd->name, "result_embd_pooled") == 0 && "missing embeddings tensor");
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- } else {
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+ } else {
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embd = nullptr; // do not extract embeddings when not needed
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GGML_ASSERT(strcmp(res->name, "result_output") == 0 && "missing result_output tensor");
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}
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+
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+ if (!cparams.causal_attn) {
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+ res = nullptr; // do not extract logits when not needed
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+ }
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+
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// LLAMA_LOG_INFO("graph build time: %.3f ms (%d nodes, %d leafs)\n", (ggml_time_us() - t_start_us)/1000.0, gf->n_nodes, gf->n_leafs);
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ggml_backend_sched_alloc_graph(lctx.sched, gf);
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