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918ece4f4d
See https://github.com/pytorch/pytorch/pull/129751#issue-2380881501. Most changes are auto-generated by linter. You can review these PRs via: ```bash git diff --ignore-all-space --ignore-blank-lines HEAD~1 ``` Pull Request resolved: https://github.com/pytorch/pytorch/pull/129762 Approved by: https://github.com/anijain2305
98 lines
2.3 KiB
Python
98 lines
2.3 KiB
Python
# Owner(s): ["module: dynamo"]
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import unittest.mock
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import torch
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import torch._dynamo.test_case
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import torch._dynamo.testing
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from torch._dynamo.testing import same
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try:
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from diffusers.models import unet_2d
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except ImportError:
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unet_2d = None
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def maybe_skip(fn):
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if unet_2d is None:
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return unittest.skip("requires diffusers")(fn)
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return fn
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class TestBaseOutput(torch._dynamo.test_case.TestCase):
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@maybe_skip
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def test_create(self):
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def fn(a):
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tmp = unet_2d.UNet2DOutput(a + 1)
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return tmp
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torch._dynamo.testing.standard_test(self, fn=fn, nargs=1, expected_ops=1)
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@maybe_skip
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def test_assign(self):
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def fn(a):
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tmp = unet_2d.UNet2DOutput(a + 1)
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tmp.sample = a + 2
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return tmp
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args = [torch.randn(10)]
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obj1 = fn(*args)
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cnts = torch._dynamo.testing.CompileCounter()
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opt_fn = torch._dynamo.optimize_assert(cnts)(fn)
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obj2 = opt_fn(*args)
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self.assertTrue(same(obj1.sample, obj2.sample))
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self.assertEqual(cnts.frame_count, 1)
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self.assertEqual(cnts.op_count, 2)
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def _common(self, fn, op_count):
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args = [
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unet_2d.UNet2DOutput(
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sample=torch.randn(10),
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)
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]
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obj1 = fn(*args)
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cnts = torch._dynamo.testing.CompileCounter()
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opt_fn = torch._dynamo.optimize_assert(cnts)(fn)
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obj2 = opt_fn(*args)
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self.assertTrue(same(obj1, obj2))
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self.assertEqual(cnts.frame_count, 1)
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self.assertEqual(cnts.op_count, op_count)
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@maybe_skip
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def test_getattr(self):
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def fn(obj: unet_2d.UNet2DOutput):
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x = obj.sample * 10
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return x
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self._common(fn, 1)
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@maybe_skip
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def test_getitem(self):
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def fn(obj: unet_2d.UNet2DOutput):
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x = obj["sample"] * 10
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return x
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self._common(fn, 1)
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@maybe_skip
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def test_tuple(self):
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def fn(obj: unet_2d.UNet2DOutput):
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a = obj.to_tuple()
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return a[0] * 10
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self._common(fn, 1)
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@maybe_skip
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def test_index(self):
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def fn(obj: unet_2d.UNet2DOutput):
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return obj[0] * 10
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self._common(fn, 1)
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if __name__ == "__main__":
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from torch._dynamo.test_case import run_tests
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run_tests()
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