mirror of
https://github.com/pytorch/pytorch.git
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d49dc8f4b8
This reverts commit f9937afd4f87fbb4844642ae2f587b13b5caa08c. Reverted https://github.com/pytorch/pytorch/pull/127545 on behalf of https://github.com/izaitsevfb due to reverting to unblock the revert of #127545 ([comment](https://github.com/pytorch/pytorch/pull/127545#issuecomment-2143517711))
85 lines
2.2 KiB
Python
85 lines
2.2 KiB
Python
# mypy: ignore-errors
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import torch
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import re
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import unittest
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import functools
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from subprocess import CalledProcessError
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import torch._inductor.async_compile
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from torch._inductor.codecache import CppCodeCache
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from torch.utils._triton import has_triton
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from torch.testing._internal.common_utils import (
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LazyVal,
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IS_FBCODE,
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)
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from torch.testing._internal.common_utils import TestCase
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def test_cpu():
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try:
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CppCodeCache.load("")
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return not IS_FBCODE
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except (
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CalledProcessError,
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OSError,
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torch._inductor.exc.InvalidCxxCompiler,
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torch._inductor.exc.CppCompileError,
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):
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return False
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HAS_CPU = LazyVal(test_cpu)
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HAS_CUDA = torch.cuda.is_available() and has_triton()
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HAS_XPU = torch.xpu.is_available() and has_triton()
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HAS_GPU = HAS_CUDA or HAS_XPU
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GPUS = ["cuda", "xpu"]
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HAS_MULTIGPU = any(
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getattr(torch, gpu).is_available() and getattr(torch, gpu).device_count() >= 2
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for gpu in GPUS
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)
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tmp_gpus = [x for x in GPUS if getattr(torch, x).is_available()]
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assert len(tmp_gpus) <= 1
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GPU_TYPE = "cuda" if len(tmp_gpus) == 0 else tmp_gpus.pop()
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del tmp_gpus
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def _check_has_dynamic_shape(
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self: TestCase,
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code,
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):
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for_loop_found = False
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has_dynamic = False
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lines = code.split("\n")
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for line in lines:
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if "for(" in line:
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for_loop_found = True
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if re.search(r";.*ks.*;", line) is not None:
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has_dynamic = True
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break
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self.assertTrue(
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has_dynamic, msg=f"Failed to find dynamic for loop variable\n{code}"
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)
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self.assertTrue(for_loop_found, f"Failed to find for loop\n{code}")
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def skipDeviceIf(cond, msg, *, device):
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if cond:
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def decorate_fn(fn):
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def inner(self, *args, **kwargs):
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if self.device == device:
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raise unittest.SkipTest(msg)
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return fn(self, *args, **kwargs)
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return inner
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else:
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def decorate_fn(fn):
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return fn
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return decorate_fn
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skipCUDAIf = functools.partial(skipDeviceIf, device="cuda")
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skipXPUIf = functools.partial(skipDeviceIf, device="xpu")
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skipCPUIf = functools.partial(skipDeviceIf, device="cpu")
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