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[executorch][muse-glimmer] Bound the CUDA prefill logits selector by the sampler rows #24883

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[executorch][muse-glimmer] Bound the CUDA prefill logits selector by the sampler rows #24883

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11 changes: 7 additions & 4 deletions examples/models/muse-glimmer/export/export_solo.py
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Original file line number Diff line number Diff line change
Expand Up @@ -527,13 +527,16 @@ def export_cuda_batching( # noqa: C901
materialize_runtime_buffers(model, dtype=torch.bfloat16)
geometry = offgraph_kv_cache_geometry(model)

# A sequence prefill samples a few rows; tracing all rows creates a
# max_step_tokens * vocab FP32 output during AOTI's JIT validation.
example_rows = _CUDA_MIN_PREFILL_CHUNK if sequence_layout else max_step_tokens
# The selected logits feed the device samplers, which take at most
# MAX_SAMPLE_ROWS rows, so a step never selects more. Bounding the selector
# there instead of at the step width keeps the memory-planned FP32 logits
# output at MAX_SAMPLE_ROWS * vocab rather than max_step_tokens * vocab.
max_selected_rows = min(max_step_tokens, MAX_SAMPLE_ROWS)
example_rows = _CUDA_MIN_PREFILL_CHUNK if sequence_layout else max_selected_rows
width = Dim(
"width", min=max(widest_static, _CUDA_MIN_PREFILL_CHUNK), max=max_step_tokens
)
rows = Dim("rows", min=_CUDA_MIN_PREFILL_CHUNK, max=max_step_tokens)
rows = Dim("rows", min=_CUDA_MIN_PREFILL_CHUNK, max=max_selected_rows)
programs = {}
with (
common.BoundMethodForward(model, types.MethodType(step_forward, model)),
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