[MLX] Gemma4-31B ondevice sampling

[kiymetakdemir]

Summary

Lets the MLX-exported Gemma 4 31B model sample the next token on-device instead of returning logits for host-side sampling. Sampling is opt-in at export (--sample); temperature, top_p, and seed are runtime inputs, and the runner increments the seed per token.

Changes

• export.py --sample flag wraps the model so forward(tokens, input_pos, temperature,
  top_p, seed) → int64 token; records a use_sampling constant-method flag. Non-sample export unchanged.
• gemma4_31b_engine.cpp reads use_sampling from metadata; when set, consumes the int64 token directly instead of logits_to_token, feeds the scalar inputs in prefill/decode (across the min/max prefill chunking), and manages the per-token seed schedule. top_k is still rejected; top_p is range-checked to (0, 1]; top_p/seed are rejected on non-sample models.
• main.cpp --top_p / --seed flags wired into SamplingConfig; an unset seed is randomized
  only for sampling models (non-sample keep seed 0, so they don't trip the guard).
• tests/test_mlx_pipeline.py adds test_export_to_pte_with_sampling: tiny-model MLX export with --sample, asserting the use_sampling flag, int64 token output, and same-seed reproducibility.

[pytorch-bot]

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❌ 2 Pending, 2 Unclassified Failures

As of commit 373b79d with merge base 825bd30 ():

UNCLASSIFIED FAILURES - DrCI could not classify the following jobs because the workflow did not run on the merge base. The failures may be pre-existing on trunk or introduced by this PR:

• Build Aarch64 Linux Wheels / pytorch/executorch / build-wheel-py3_10-cpu-aarch64 (gh) (this job did not run on the merge base, so DrCI cannot tell whether the failure is pre-existing)
  /__w/executorch/executorch/pytorch/executorch/backends/apple/coreml/runtime/inmemoryfs/inmemory_filesystem.cpp:722:48: error: ‘inmemoryfs::InMemoryFileSystem::InMemoryNode::Kind’ has not been declared
• Build Aarch64 Linux Wheels / pytorch/executorch / upload / upload-wheel-py3_10-cpu-aarch64 (gh) (this job did not run on the merge base, so DrCI cannot tell whether the failure is pre-existing)
  Unable to download artifact(s): Artifact not found for name: pytorch_executorch__3.10_cpu_aarch64

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