feat: add Ray GRPO runtime image (CUDA 12.8, Python 3.12)

[Fiona-Waters]

Summary

Adds a new Ray runtime image for LoRA-GRPO training on KubeRay, extending quay.io/modh/ray:2.53.0-py312-cu128 with the ML stack required by training-hub's GRPO backend.

The image layers vLLM 0.12.0, verl 0.7.1, flash-attn 2.8.3, PyTorch 2.9.0, and training-hub on top of the existing base Ray CUDA 12.8 image, following the same directory layout as the existing runtime images.

Key packages

Package	Version	Role
vLLM	0.12.0	LLM rollout engine
PyTorch	2.9.0	Deep learning framework
verl	0.7.1	GRPO training orchestrator (FSDP + vLLM)
flash-attn	2.8.3	Memory-efficient attention (pre-built wheel, cxx11abiTRUE)
training-hub	latest	High-level GRPO training API
peft	≥0.15	LoRA adapters
transformers	≥4.57.6	HuggingFace model loading

Notes

• Git branch installs (temporary): instructlab-training and rhai-innovation-mini-trainer are installed from their main branches to pick up the relaxed numba>=0.61.2 constraint (merged but not yet released to PyPI). training-hub[grpo] is installed from the lora-grpo branch (GRPO code not yet merged to main). Once all packages are released, Step 4 simplifies to pip install "training-hub[grpo]".

Changes

• New directory images/runtime/ray/cuda/2.53.0-py312-cu128-grpo/ with Dockerfile and README

Test Plan

• Image built and pushed as quay.io/rh_ee_fwaters/ray-grpo:2.53.0-py312-cu128-v6
• Smoke test passes (ray, vllm, torch, verl, training_hub, lora_grpo, VeRLLoRAGRPOBackend imports verified)
• Successful end-to-end GRPO training run on KubeRay cluster

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