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[PyTorch] torch.compile fails on FusedAttnBackend IntEnum comparisons

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@pggPL 已经在做这个了。

开始于 2026年10月20日。

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描述

bug

Describe the bug

torch.compile(fullgraph=True) fails in TE's fused DotProductAttention path when comparing FusedAttnBackend members:

fused_attention_backend != FusedAttnBackend["No_Backend"]
  -> FusedAttnBackend.__ne__
  -> FusedAttnBackend.__eq__
  -> int.__eq__(self, other)

torch._dynamo.exc.Unsupported: Missing tp_richcompare_impl override
Developer debug context:
tp_richcompare_impl UserDefinedObjectVariable(FusedAttnBackend) __eq__

This affects the fused DPA cases in tests/pytorch/test_torch_compile.py, before an attention kernel runs. The same failure can be reproduced using only PyTorch on CPU.

Minimal reproduction

from enum import IntEnum

import torch


class Backend(IntEnum):
    NO = 0
    YES = 1

    def __eq__(self, other):
        return int.__eq__(self, other)

    def __ne__(self, other):
        result = self.__eq__(other)
        return result if result is NotImplemented else not result


def f(x, backend):
    return x + 1 if backend != Backend.NO else x - 1


x = torch.ones(2)
print("eager:", f(x, Backend.YES))
print("compiled:", torch.compile(f, backend="eager", fullgraph=True)(x, Backend.YES))

Expected behavior

Both calls return tensor([2., 2.]). The compiled call instead raises the Dynamo error above.

Environment

  • CPU reproduction: Linux x86_64, Docker, Python 3.12.3.
  • PyTorch: 2.15.0a0+fd23299d96.nvinternal.main.
  • The reproducer requires neither TE nor CUDA.
  • The original TE failures were observed on A100, H100, B200, and GB200.

Upstream diagnosis and existing fix

The regression was introduced by pytorch/pytorch@95dddcf5d6388e7216717857b546df7cbfa073a7, “Remove _base_vt” (pytorch/pytorch#193679). With the same installed PyTorch binaries, importing the complete Dynamo sources from its parent 8ab021bb passes the reproducer; importing the sources from 95dddcf5 fails.

BuiltinVariable.call_method routes int.__eq__ through call_base_method before reaching the existing constant-folding path for explicit comparisons. Enum members use UserDefinedObjectVariable, whose MRO lacks the ConstantVariable implementation required by that route.

The open pytorch/pytorch#199496 (“Support unbound builtin method descriptors”, by KarhouTam) removes this early dispatch as part of a broader fix. Applying its relevant isolated change resolves this reproducer and passes 105 focused comparison checks; the full PR has not been validated here.

As of 2026-10-20, PyTorch main at ec16340feb88f278c3a76ded17e21ec3a143c7c4 still contains the problematic dispatch ordering (source inspection). This issue tracks the impact on TE and the upstream resolution.

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