[Core] Update PyTorch to 2.12.0, torchvision to 0.27.0, triton to 3.7.0

[atalman]

Purpose

Update the PyTorch ecosystem to the released versions:

• torch: 2.11.0 → 2.12.0
• torchvision: 0.26.0 → 0.27.0
• triton: 3.6.0 → 3.7.0
• torchaudio: stays at 2.11.0

This PR supersedes #40077. Now that the torch 2.12.0 release is published on PyPI / download.pytorch.org/whl/, no temporary whl/test/ index URLs are needed — wheels resolve from the regular indexes.

CUDA 13 transitive deps

Bumped to match torch==2.12.0+cu130:

• nvidia-cudnn-cu13: 9.19.0.56 → 9.20.0.48
• nvidia-cusparselt-cu13: 0.8.0 → 0.8.1
• nvidia-nccl-cu13: 2.28.9 → 2.29.7

CPU compatibility test fix

.buildkite/scripts/hardware_ci/run-cpu-compatibility-test.sh previously set TORCH_COMPILE_DISABLE=1 to skip torch.compile (slow under SDE). On torch 2.11 this turned every torch.compile call site into a silent no-op. On torch 2.12, call sites that pass fullgraph=True now raise:

RuntimeError: Worker failed with error 'torch.compile with fullgraph=True
found no compiled frames. The frame was likely skipped (...).'

Engine init goes through vLLM's piecewise-compile path (which uses fullgraph=True), so init crashes inside determine_available_memory. Switched to vLLM's canonical --enforce-eager engine flag, which never constructs a torch.compile wrapper at all — same SDE speedup, no contract violation, works on both torch 2.11 and 2.12.

Tracked upstream as pytorch/pytorch#181247 (under umbrella pytorch/pytorch#180899).

Test Plan

CI sign-off — Buildkite full daily / full nightly runs on this branch:

• CUDA build + tests (CUDA 13)
• CPU build + tests (x86_64, aarch64, s390x)
• ROCm build
• CPU SDE compatibility test (Sky Lake / Cascade Lake / Cooper Lake)

Test Result

To be filled in once CI completes on this branch.

Duplicate-work check

• [WIP][Core] Update PyTorch to 2.12.0, torchvision to 0.27.0, triton to 3.7.0 #40077 — same author's WIP draft for the same upgrade, kept open while torch 2.12 was on whl/test/. This PR is the clean release-channel version and supersedes it.
• [WIP][XPU] upgrade torch-xpu to 2.12 #42262 — XPU-only torch-xpu==2.12 upgrade. Different scope; this PR doesn't touch XPU.
• Update gpu.xpu.inc.md to use triton-xpu 3.7.0 #39715 — XPU docs change for triton-xpu 3.7. Unrelated.

AI-assistance disclosure

AI assistance (Claude) was used to draft the changes. Every changed line was reviewed and the test plan above was constructed and run by a human submitter.

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Essential Elements of an Effective PR Description Checklist

• The purpose of the PR, such as "Fix some issue (link existing issues this PR will resolve)".
• The test plan, such as providing test command.
• The test results, such as pasting the results comparison before and after, or e2e results
• (Optional) The necessary documentation update, such as updating supported_models.md and examples for a new model.

[gemini-code-assist]

Code Review

This pull request updates the project's dependencies to support PyTorch 2.12.0 across various build and environment configurations, including CUDA, ROCm, CPU, and s390x. Key changes include version bumps for torch, torchvision, triton, and several NVIDIA libraries. Additionally, the hardware CI script for CPU compatibility was updated to use the --enforce-eager flag, replacing the TORCH_COMPILE_DISABLE environment variable to prevent crashes during engine initialization with the new PyTorch version. I have no further feedback to provide.