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https://github.com/zebrajr/pytorch.git
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6ff1e43a41
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/129764 Approved by: https://github.com/ezyang
93 lines
2.9 KiB
Python
93 lines
2.9 KiB
Python
# Owner(s): ["oncall: jit"]
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import os
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import sys
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import unittest
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import torch
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# Make the helper files in test/ importable
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pytorch_test_dir = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
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sys.path.append(pytorch_test_dir)
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from torch.testing._internal.jit_utils import JitTestCase
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if __name__ == "__main__":
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raise RuntimeError(
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"This test file is not meant to be run directly, use:\n\n"
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"\tpython test/test_jit.py TESTNAME\n\n"
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"instead."
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)
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# NOTE: FIXING FAILING TESTS
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# If you are seeing a test failure from this file, congrats, you improved
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# parity between JIT and Python API. Before you fix the test, you must also update
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# the corresponding section in documentation that states the unsupported behavior.
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# see: `jit_unsupported.rst`
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class TestUnsupportedOps(JitTestCase):
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def test_factory_ops_requires_grad_fail(self):
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# Keyword argument {name} unknown is a JIT-only error message,
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# so these functions are succeeding in eager and failing in JIT
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# Complete issue and set of ops is https://github.com/pytorch/pytorch/issues/30761
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# only testing some because they should be fixed all at once
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def ones():
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return torch.ones([2], requires_grad=True)
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with self.assertRaisesRegexWithHighlight(
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Exception, "Keyword argument requires_grad unknown", "torch.ones"
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):
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torch.jit.script(ones)
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def randn():
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return torch.randn([2], requires_grad=True)
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with self.assertRaisesRegexWithHighlight(
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Exception, "Keyword argument requires_grad unknown", "torch.randn"
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):
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torch.jit.script(randn)
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def zeros():
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return torch.zeros([2], requires_grad=True)
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with self.assertRaisesRegexWithHighlight(
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Exception, "Keyword argument requires_grad unknown", "torch.zeros"
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):
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torch.jit.script(zeros)
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@unittest.skipIf(not torch._C.has_lapack, "PyTorch compiled without Lapack")
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def test_init_ops(self):
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def calculate_gain():
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return torch.nn.init.calculate_gain("leaky_relu", 0.2)
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def eye_():
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return torch.nn.init.eye_(torch.zeros([2, 2]))
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def dirac_():
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return torch.nn.init.dirac_(torch.empty(3, 16, 5, 5))
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def kaiming_uniform_():
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return torch.nn.init.kaiming_normal_(torch.empty(3, 5))
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def orthogonal_():
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return torch.nn.init.orthogonal_(torch.empty(3, 5))
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def sparse():
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return torch.nn.init.sparse_(torch.empty(3, 5), sparsity=0.1)
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for func in [
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calculate_gain,
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eye_,
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dirac_,
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kaiming_uniform_,
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orthogonal_,
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sparse,
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]:
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# doesn't error in eager
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func()
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with self.assertRaisesRegex(Exception, ""):
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torch.jit.script(func)
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