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sampling : optimize dist sampler - #15704
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…upport * origin/master: (72 commits) metal : Add template specialization for mul_mm_id w/ ne20 == 10 (ggml-org#15799) llama : set n_outputs to 1 to avoid 0 outputs mean-pooling (ggml-org#15791) CANN: Refactor ND to NZ workspace to be per-device (ggml-org#15763) server: add exceed_context_size_error type (ggml-org#15780) Document the new max GPU layers default in help (ggml-org#15771) ggml: add ops for WAN video model (cuda && cpu) (ggml-org#15669) CANN: Fix precision issue on 310I DUO multi-devices (ggml-org#15784) opencl: add hs=40 to FA (ggml-org#15758) CANN: fix acl_rstd allocation size in ggml_cann_rms_norm (ggml-org#15760) vulkan: fix mmv subgroup16 selection (ggml-org#15775) vulkan: don't use std::string in load_shaders, to improve compile time (ggml-org#15724) vulkan : update ggml_vk_instance_validation_ext_available (ggml-org#15666) ggml vulkan: add hardsigmoid and hardswish operations (ggml-org#15762) CUDA: Optimize `rms_norm_f32` kernel and its fused variants, giving 1-6% perf E2E (ggml-org#15715) model-conversion : fix pyright errors (ggml-org#15770) sampling : optimize dist sampler (ggml-org#15704) llama : fix incorrect model type for Gemma 270M (ggml-org#15764) model-conversion : remove hardcoded /bin/bash shebangs [no ci] (ggml-org#15765) CANN: Add RoPE contiguous check for 310I DUP device (ggml-org#15735) ggml-cpu : optimize RVV kernels (ggml-org#15720) ...
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| if (!found) { | ||
| // accumulate probs until we reach the target sum | ||
| sum_run += cur_p->data[i].p; | ||
| if (sum_run >= sum_tgt) { |
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This line makes an assumption that cur_p->sorted is true. At least in the unit-test this is not the case (adding an assertion would fail). Do we have a potential issue here when cur_p is not sorted? I have not tested with actual models yet.
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cont #15665
When the dist sampler runs on the full vocabulary (e.g.
top-p = 1, top-k = 0, min-p = 0), the sampling time can have a non-negligible effect. This PR fuses the probability normalization loop with the inverse transform sampling.On M2 Ultra, the tg with
gpt-oss-120bgoes from ~70t/s -> 78t/s at empty context.