[Bugfix][Memory] Fix PYTORCH_ALLOC_CONF in KV-transfer and CuMem safeguards

[ztxing462]

Purpose

PyTorch accepts the backend-specific PYTORCH_CUDA_ALLOC_CONF and PYTORCH_HIP_ALLOC_CONF variables as well as the unified PYTORCH_ALLOC_CONF name. Two allocator safeguards in vLLM currently inspect only PYTORCH_CUDA_ALLOC_CONF:

1. The KV-transfer compatibility check can miss PYTORCH_ALLOC_CONF=expandable_segments:True, even though PyTorch has enabled expandable segments. This bypasses the existing protection for pinned or registered KV memory whose physical backing must remain stable.
2. CuMemAllocator.use_memory_pool() can miss the same unified setting. When it recognizes the legacy setting, it replaces the complete allocator input with expandable_segments:False and later restores expandable_segments:True, dropping settings such as max_split_size_mb and garbage_collection_threshold.

This PR makes both paths use the same allocator-settings semantics:

• Prefer PyTorch's runtime allocator-settings getter when available. On versions without it, including PyTorch 2.11, follow PyTorch's first-present environment precedence: PYTORCH_CUDA_ALLOC_CONF, PYTORCH_HIP_ALLOC_CONF, then PYTORCH_ALLOC_CONF.
• Parse expandable_segments as a complete option, including whitespace and duplicate-key last-value-wins behavior.
• Apply the safety gate on CUDA, ROCm, and XPU, whose expandable allocators use remappable virtual memory, while leaving CPU and TPU connector configs unaffected.
• In the outermost CuMem pool, snapshot the allocator-settings string exposed by PyTorch, append a final expandable_segments:False override, and restore the snapshot verbatim on normal or exceptional exit. Nested pools do not retoggle the process-global setting.

Fresh-process checks against origin/main and this PR produced:

Case	origin/main	This PR
Unified setting + NixlConnector VllmConfig	accepted	rejected
Unified setting + native offloading config	accepted	rejected
Effective expandable_segments inside a CUDA CuMem pool	True	False
Legacy setting + other options after leaving a CuMem pool	reset to defaults	preserved

The NixlConnector row covers full VllmConfig construction and the admission check. It does not claim that a NIXL agent, memory registration, or cross-node KV transfer was exercised.

Limitations

PyTorch 2.11 does not expose the allocator-settings getter to Python, so the environment fallback cannot observe runtime changes made after PyTorch cached the environment. On newer PyTorch versions, the getter exposes the last parsed settings string rather than a canonical serialization of every effective allocator field. Consequently, arbitrary third-party partial setter calls cannot always be reconstructed; the environment and full-string paths covered by this PR remain observable.

The nesting logic provides LIFO restoration for one CuMem allocator instance; it does not introduce thread-local allocator settings.

Relationship to existing PRs

I searched open PRs for PYTORCH_ALLOC_CONF, allocator settings, expandable_segments, CuMem, and KV connectors. The closest related changes are:

• #51096 uses the same snapshot/append/restore mechanism in gpu_worker._scoped_allocator_max_split. It does not change the KV-transfer gate or CuMemAllocator.use_memory_pool() addressed here. If it lands first, this PR will rebase and consolidate the shared helper where appropriate.
• #43923 temporarily disables expandable segments for custom-allreduce CUDA IPC. It changes a separate allocation scope and does not cover the unified-variable KV/CuMem paths here.
• #42405 and #48243 adjust connector exemption policy. This PR instead fixes how the active allocator setting is detected and preserved while retaining the existing conservative policy.

This PR intentionally does not modify the gpu_worker, custom-allreduce, Sharded-RDT warning, or collect-env diagnostic paths.

Test Plan

Allocator parsing, runtime getter, and environment fallback:

.venv/bin/python -m pytest tests/utils_/test_torch_utils.py \
  -k torch_allocator -q

KV connector checks for unified and legacy settings, CUDA/ROCm/XPU gating, CPU/TPU exclusion, and existing exemptions:

.venv/bin/python -m pytest tests/v1/kv_connector/unit/test_config.py \
  -k 'expandable_segments or alloc_conf' -q

CuMem setting preservation, trailing commas, exceptions, and nested pools:

.venv/bin/python -m pytest tests/basic_correctness/test_mem.py \
  -k 'cumem_preserves_allocator_settings or cumem_restores_allocator_settings or nested_cumem_pool' -q

Real CUDA CuMem smoke test with the unified variable:

env -u PYTORCH_CUDA_ALLOC_CONF -u PYTORCH_HIP_ALLOC_CONF \
  PYTORCH_ALLOC_CONF=expandable_segments:True \
  .venv/bin/python -m pytest \
  tests/basic_correctness/test_mem.py::test_basic_cumem -q -s

Formatting and repository checks:

.venv/bin/pre-commit run --files \
  vllm/utils/torch_utils.py \
  vllm/config/vllm.py \
  vllm/device_allocator/cumem.py \
  tests/utils_/test_torch_utils.py \
  tests/v1/kv_connector/unit/test_config.py \
  tests/basic_correctness/test_mem.py
git diff --check

Model evaluation is not applicable because this change does not modify model code, operators, kernels, sampling, or generated outputs.

Test Result

Tested on an NVIDIA GeForce RTX 5090 D with PyTorch 2.13.0+cu130:

10 passed, 33 deselected  # allocator helper
11 passed, 6 deselected   # KV connector/platform compatibility
5 passed, 13 deselected   # CuMem preservation/error/nesting
1 passed                  # real CUDA CuMem smoke test
pre-commit: passed
git diff --check: passed

The CUDA runtime checks used real allocator settings, a real CuMem pool, and PyTorch allocator snapshots. The CUDA/ROCm/XPU/CPU/TPU gate branches were covered with platform stubs; no ROCm, XPU, or TPU hardware integration test was run.

AI assistance

This change was developed with OpenAI Codex assistance. I reviewed every changed line, understand the implementation end-to-end, and personally reran the tests reported above.

[claude]

Claude Code Review

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[chatgpt-codex-connector]

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Review	Status	Commit	Review trigger
📝 Code Review	✅ Completed 2026-08-29T11:55:19.564313Z	ef010a3	PR opened

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[ztxing462]

Hi maintainers, this PR is ready for review.
I have completed the implementation and verified the relevant tests locally. This is my first contribution to this repository, so the pre-commit gate currently reports 0 previously merged PRs.
Please review it when convenient. Thank you.

[mergify]

This pull request has merge conflicts that must be resolved before it can be
merged. Please rebase the PR, @ztxing462.

https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/working-with-forks/syncing-a-fork

[mergify]

This pull request has merge conflicts that must be resolved before it can be
merged. Please rebase the PR, @ztxing462.

https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/working-with-forks/syncing-a-fork