infrastructure-gpu-memory-profiling-vllm-fails-to-allocate-kv-cache-blocks-even-when-s-69d5e472

THEN Disable CUDA graph execution with the `--enforce-eager` flag to reduce memory overhead. Alternatively, lower `gpu_memory_utilization` or ensure other processes are not sharing the GPU to avoid memory attribution conflicts. The issue stems from PR #2031 which changed memory profiling to assume all occupied GPU memory belongs to the current instance.

Add `--enforce-eager` to the vLLM command line arguments when initializing the engine, e.g., `python -m vllm.entrypoints.openai.api_server --model mymodel --enforce-eager`.