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llama : set n_outputs to 1 to avoid 0 outputs mean-pooling #15791

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Merged
merged 3 commits into from
Sep 4, 2025
Merged

llama : set n_outputs to 1 to avoid 0 outputs mean-pooling #15791

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af61b63
llama : set n_outputs to 1 to avoid 0 outputs mean-pooling
danbev Sep 4, 2025
4bf6181
add comment about not reserving graphs with zero outputs
danbev Sep 4, 2025
d3c0635
add assert in graph_reserve to ensure n_outputs >= 1
danbev Sep 4, 2025
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4 changes: 4 additions & 0 deletions src/llama-context.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -285,6 +285,9 @@ llama_context::llama_context(
const uint32_t n_seqs = cparams.kv_unified ? 1 : cparams.n_seq_max;
const uint32_t n_tokens = std::min(cparams.n_ctx, cparams.n_ubatch);

// avoid reserving graphs with zero outputs
n_outputs = 1;

LLAMA_LOG_DEBUG("%s: worst-case: n_tokens = %d, n_seqs = %d, n_outputs = %d\n", __func__, n_tokens, n_seqs, n_outputs);

// resolve automatic Flash Attention use
Expand Down Expand Up @@ -1368,6 +1371,7 @@ llm_graph_result * llama_context::get_gf_res_reserve() const {

ggml_cgraph * llama_context::graph_reserve(uint32_t n_tokens, uint32_t n_seqs, uint32_t n_outputs, const llama_memory_context_i * mctx, bool split_only) {
LLAMA_LOG_DEBUG("%s: reserving a graph for ubatch with n_tokens = %4u, n_seqs = %2u, n_outputs = %4u\n", __func__, n_tokens, n_seqs, n_outputs);
GGML_ASSERT(n_outputs >= 1);

if (n_tokens % n_seqs != 0) {
n_tokens = ((n_tokens + (n_seqs - 1)) / n_seqs) * n_seqs; // round to next multiple of n_seqs
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