Pre-release / continuous build: this is an experimental build, not a stable release.
graph: skip the LM head for pooled embeddings (#30445) * graph: skip the LM head for pooled embeddings A context that extracts pooled embeddings outputs one vector per sequence, but every model still expanded its LM head, so the graph computed n_vocab logits per token and the context kept a host buffer for them. The models now only declare t_logits, and set_outputs() expands it unless the context extracts embeddings with a pooling type other than NONE. Since the toggle changes the graph shape for a pooled context, set_embeddings() schedules a re-reserve in that case. * graph: drop the redundant t_embd expand Address review from @CISC: with embeddings on, build_pooling() already expands its output for every pooling type, and a decoder graph without embeddings does not read t_embd, so set_outputs() only expands t_logits. * graph: add build_logits() for the LM head output Address review from @ggerganov: the LM head is expanded by a dedicated build_logits(), called from llama_model::build_graph() like build_pooling(), and set_outputs() only marks the outputs again. * graph: call build_logits() before build_sampling() Address review from @ggerganov: build_sampling() reads t_logits, so the LM head is built first. A pooled context then skips the sampling layers too, since it has no logits to sample from. * nitWebsite: - https://llama.app
Attestations: - https://github.com/ggml-org/llama.cpp/attestations/55574302
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