Enable CUDA Graphs with vLLM Data Parallel

[ihebchaa]

Problem:

When using vLLM with data_parallel_size > 1, the current implementation forces enforce_eager=True, which disables CUDA graphs and significantly impacts performance. This is particularly problematic for Reasoning models that require large max_new_tokens (e.g., 32k+ tokens).

Solution:

this PR removes the forced enforce_eager=True when using data parallel.

Key Changes

• Improved CUDA device isolation: Each worker process correctly sets its CUDA_VISIBLE_DEVICES by running in an isolated env.
• Removed forced eager execution

Tests

Tested with tp=2 and dp (1, 2, 4) with a 7b reasoning model

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[baberabb]

Hi! thanks for the PR. Are you aware why they enforce eager if you follow their public API?

[ihebchaa]

It's not clear to me why it's forced here
Multiple vLLM instances are created separately on each dp rank and do not communicate with each other, so I don't see why enforce_eager is enforced.