[executorch][muse-glimmer] Add unified CUDA sample_token entry point

[Gasoonjia]

Stack from ghstack (oldest at bottom):

• [executorch][muse-glimmer] Run DFlash sampling on CUDA #22492
• [executorch][muse-glimmer] Add CUDA speculative sampling orchestration #22491
• -> [executorch][muse-glimmer] Add unified CUDA sample_token entry point #22490
• [executorch][muse-glimmer] Add CUDA residual correction sampling #22489
• [executorch][muse-glimmer] Add CUDA excluded-token correction #22488
• [executorch][muse-glimmer] Add CUDA speculative acceptance #22487
• [executorch][muse-glimmer] Add CUDA categorical sampling #22486
• [executorch][muse-glimmer] Add CUDA sampling probabilities #22485
• [executorch][muse-glimmer] Add CUDA argmax sampling primitive #22484

Add the CUDA counterpart of muse_glimmer::sample_token. Preserve greedy argmax, temperature/top-k/top-p probability construction, optional probabilities-only output, and stochastic categorical sampling behind one device-resident interface.

Differential Revision: D117826288

[pytorch-bot]

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❌ 1 New Failure, 2 Unclassified Failures

As of commit 92ce0ea with merge base c65ad53 ():

NEW FAILURE - The following job has failed:

• Lint / lintrunner (gh)
  >>> Lint for examples/models/muse-glimmer/tests/sampling_cuda_test.cpp:

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:

• MLX / test-mlx-muse-glimmer-build / test-mlx-muse-glimmer-build (gh) (this job did not run on the merge base, so DrCI cannot tell whether the failure is pre-existing)
  pytorch_tokenizers
• MLX / test-mlx-voxtral-realtime / test-mlx-voxtral-realtime (gh) (this job did not run on the merge base, so DrCI cannot tell whether the failure is pre-existing)
  ##[error]fatal: unable to access 'https://github.com/ml-explore/mlx.git/': Failed to connect to github.com port 443 after 7996 ms: Couldn't connect to server

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