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https://github.com/zebrajr/pytorch.git
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806010b75e
Summary: Relate to https://github.com/pytorch/pytorch/issues/50483. Everything except ONNX, detectron and release notes tests are moved to use common_utils.run_tests() to ensure CI reports XML correctly. Pull Request resolved: https://github.com/pytorch/pytorch/pull/50923 Reviewed By: samestep Differential Revision: D26027621 Pulled By: walterddr fbshipit-source-id: b04c03f10d1fe96181b720c4c3868e86e4c6281a
55 lines
1.6 KiB
Python
55 lines
1.6 KiB
Python
import os
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import tempfile
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import torch
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from backend import Model, to_custom_backend, get_custom_backend_library_path
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from torch.testing._internal.common_utils import TestCase, run_tests
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class TestCustomBackend(TestCase):
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def setUp(self):
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# Load the library containing the custom backend.
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self.library_path = get_custom_backend_library_path()
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torch.ops.load_library(self.library_path)
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# Create an instance of the test Module and lower it for
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# the custom backend.
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self.model = to_custom_backend(torch.jit.script(Model()))
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def test_execute(self):
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"""
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Test execution using the custom backend.
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"""
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a = torch.randn(4)
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b = torch.randn(4)
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# The custom backend is hardcoded to compute f(a, b) = (a + b, a - b).
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expected = (a + b, a - b)
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out = self.model(a, b)
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self.assertTrue(expected[0].allclose(out[0]))
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self.assertTrue(expected[1].allclose(out[1]))
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def test_save_load(self):
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"""
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Test that a lowered module can be executed correctly
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after saving and loading.
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"""
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# Test execution before saving and loading to make sure
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# the lowered module works in the first place.
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self.test_execute()
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# Save and load.
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f = tempfile.NamedTemporaryFile(delete=False)
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try:
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f.close()
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torch.jit.save(self.model, f.name)
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loaded = torch.jit.load(f.name)
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finally:
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os.unlink(f.name)
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self.model = loaded
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# Test execution again.
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self.test_execute()
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if __name__ == "__main__":
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run_tests()
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