chore: Bump vllm to 0.11.2, torch to 2.9, transformers to 4.57.1

[yfw]

What does this PR do ?

Updates vllm to 0.11.2, torch to 2.9, transformers to 4.57.1. Also updates Automodel to use main branch.

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Summary by CodeRabbit

Release Notes

• Updates

  • Upgraded core dependencies: PyTorch (2.9.0), Transformers (4.57.1), and vLLM (0.11.2)
  • Added multi-node distributed training configuration support

• Improvements

  • Enhanced vLLM integration robustness and compatibility
  • Optimized FP8 weight handling for improved efficiency

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❌ Submodule Fast-Forward Check Failed

Check based on commit: 82b6f9576ead74d58a15597ce35570aece72404c (PR #1563 from yifu/vllm0112_bump)

❌ Submodules that need attention:

Automodel: ❌ Commits have DIVERGED from a common ancestor TARGET (main branch): https://github.com/NVIDIA-NeMo/Automodel/commits/a2db048383cd54b3fafc928df4c30bf7bbf7c430/ CURRENT (PR #1563 from yifu/vllm0112_bump): https://github.com/NVIDIA-NeMo/Automodel/commits/f9fc82c055e1cc69a68ff0bc7614aabe507a43ea/

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✅ Submodule Fast-Forward Check Results

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📝 Walkthrough

Walkthrough

This PR updates core dependencies (PyTorch 2.9.0, transformers 4.57.1, vLLM 0.11.2), refactors vLLM worker initialization to use dynamic file lookup instead of hardcoded paths, introduces in-place FP8 weight post-processing, and migrates test configurations from single-node to two-node setups.

Changes

Cohort / File(s)	Summary
Dependency Updates pyproject.toml, tools/build-custom-vllm.sh	Bumped PyTorch from 2.8.0 to 2.9.0, transformers from ≥4.55.4 to ≥4.57.1, and vLLM from 0.11.0 to 0.11.2; updated CUDA wheel index from cu128 to cu129.
Submodule Updates .gitmodules, 3rdparty/Automodel-workspace/Automodel	Changed Automodel submodule branch to yifu/bump-torch-and-hf and updated commit pointer.
Configuration & Test Updates examples/configs/recipes/llm/grpo-llama3.1-8b-instruct-2n8g-megatron-fp8-e2e.yaml, tests/test_suites/llm/grpo-llama3.1-8b-instruct-2n8g-megatron-fp8-e2e.sh, tests/test_suites/nightly.txt	Updated checkpoint/log paths from 1n8g to 2n8g, set cluster.num_nodes: 2, changed NUM_NODES from 1 to 2, and switched nightly test reference from 1n8g to 2n8g configuration.
FP8 Weight Processing nemo_rl/models/generation/fp8.py	Added maybe_post_process_fp8_weight_block() function for in-place FP8 weight and scale re-quantization; adjusted process_weights_after_loading() to call the new function without extra parameters.
vLLM Worker Initialization nemo_rl/models/generation/vllm/vllm_worker.py	Replaced hardcoded vLLM import paths with dynamic file lookup via importlib.find_spec(); introduced _get_vllm_file() helper and two new patching functions (_patch_vllm_init_workers_ray() and _patch_vllm_vit_flash_attn_backend()) for robust version-agnostic patching.

Estimated code review effort

🎯 3 (Moderate) | ⏱️ ~20 minutes

• vllm_worker.py: Carefully verify dynamic file lookup logic handles vLLM versions robustly and that patched behaviors (Ray executor env variables, attention backend override) remain correct.
• fp8.py: Ensure in-place weight/scale updates preserve gradient flow and model training behavior; confirm compatibility with DeepGemm E8M0 quantization.
• Dependency compatibility: Cross-check PyTorch 2.9.0, transformers 4.57.1, and vLLM 0.11.2 compatibility across different compute environments and CUDA versions (cu129).
• Multi-node test configurations: Validate that 2-node setup produces expected distributed behavior and resource allocation.

Possibly related PRs

• NVIDIA-NeMo/RL#1116: Updates custom vLLM build tooling and dependency instructions similar to this PR's torch/vLLM version bumps.
• NVIDIA-NeMo/RL#1334: Modifies the same vLLM worker integration and related dependency/test configurations.

Suggested reviewers

• terrykong
• parthchadha
• guyueh1

Pre-merge checks and finishing touches

❌ Failed checks (2 warnings)

Check name	Status	Explanation	Resolution
Docstring Coverage	⚠️ Warning	Docstring coverage is 75.00% which is insufficient. The required threshold is 80.00%.	You can run @coderabbitai generate docstrings to improve docstring coverage.
Test Results For Major Changes	⚠️ Warning	PR introduces major dependency bumps (torch 2.9.0, transformers 4.57.1, vllm 0.11.2) and code changes to FP8 quantization and vLLM workers, but PR description contains no test results, performance benchmarks, or compatibility verification. Review comments flag incompatibility issues with this dependency combination.	Document comprehensive test results in PR description including: integration test results with updated dependencies, training convergence verification, 2-node test configuration results, FP8 quantization validation, and confirmation that torch 2.9.0 + transformers 4.57.1 combination has been tested.

✅ Passed checks (2 passed)

Check name	Status	Explanation
Description Check	✅ Passed	Check skipped - CodeRabbit’s high-level summary is enabled.
Title check	✅ Passed	The title accurately summarizes the main changes: dependency version bumps for vllm, torch, and transformers, which are the primary modifications across multiple files.

✨ Finishing touches

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• [ ] Commit unit tests in branch yifu/vllm0112_bump

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✅ Submodule Fast-Forward Check Results

Check based on commit: c5c3eca1ed41f31f8ad9f6ff5fed11872727713c (PR #1563 from yifu/vllm0112_bump)

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✅ Submodule Fast-Forward Check Results

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[guyueh1]

@yfw we need to update the torch version in tools/build-custom-vllm.sh as well

[yfw]

@yfw we need to update the torch version in tools/build-custom-vllm.sh as well

I pulled in this change for this: https://github.com/NVIDIA-NeMo/RL/pull/1563/commits/eab60198c430cdd2750388951c76e3bc101d64b8

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✅ Submodule Fast-Forward Check Results

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