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https://github.com/pytorch/pytorch.git
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e3c5c369ba
Part of my effort to move everything to pytest and decrease the number of testrunner frameworks in ci Gives xmls but they might look a weird b/c module level tests vs tests in classes. Doesn't give skip/disable test infra because those are tied to classes. (for future ref, could either put tests in classes or move the check_if_enable stuff into a pytest hook) Tested in CI and checked that the same number of tests are run Pull Request resolved: https://github.com/pytorch/pytorch/pull/95659 Approved by: https://github.com/huydhn
144 lines
3.1 KiB
Python
144 lines
3.1 KiB
Python
# Owner(s): ["oncall: distributed"]
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# Copyright 2019 Kakao Brain
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#
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# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
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#
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# This source code is licensed under the BSD license found in the
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# LICENSE file in the root directory of this source tree.
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import pytest
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import torch
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from torch import nn
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from torch.distributed.pipeline.sync.skip import pop, skippable, stash
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from torch.distributed.pipeline.sync.skip.tracker import SkipTracker, use_skip_tracker
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from torch.testing._internal.common_utils import run_tests
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@pytest.fixture(autouse=True)
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def skip_tracker():
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skip_tracker = SkipTracker()
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with use_skip_tracker(skip_tracker):
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yield skip_tracker
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def test_stash(skip_tracker):
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@skippable(stash=["foo"])
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class Stash(nn.Module):
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def forward(self, input):
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yield stash("foo", input)
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return input * 2 # noqa: B901
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l1 = Stash()
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assert len(skip_tracker.tensors) == 0
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with use_skip_tracker(skip_tracker):
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l1(torch.tensor(42))
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assert len(skip_tracker.tensors) == 1
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def test_pop():
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@skippable(stash=["foo"])
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class Stash(nn.Module):
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def forward(self, input):
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yield stash("foo", input)
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return input * 2 # noqa: B901
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@skippable(pop=["foo"])
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class Pop(nn.Module):
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def forward(self, input):
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foo = yield pop("foo")
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return foo
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l1 = Stash()
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l2 = Pop()
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output = l2(l1(torch.tensor(42)))
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assert output.item() == 42
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def test_declare_but_not_use():
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@skippable(stash=["foo"])
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class Stash(nn.Module):
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def forward(self, input):
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return input * 2
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@skippable(pop=["foo"])
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class Pop(nn.Module):
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def forward(self, input):
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return input * 3
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l1 = Stash()
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l2 = Pop()
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with pytest.raises(RuntimeError):
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l1(torch.tensor(42))
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with pytest.raises(RuntimeError):
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l2(torch.tensor(42))
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def test_stash_not_declared():
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@skippable()
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class Stash(nn.Module):
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def forward(self, input):
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yield stash("foo", input)
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return input * 2 # noqa: B901
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l1 = Stash()
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with pytest.raises(RuntimeError):
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l1(torch.tensor(42))
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def test_pop_not_declared():
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@skippable(stash=["foo"])
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class Stash(nn.Module):
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def forward(self, input):
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yield stash("foo", input)
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return input * 2 # noqa: B901
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@skippable()
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class Pop(nn.Module):
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def forward(self, input):
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foo = yield pop("foo")
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return foo
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l1 = Stash()
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l2 = Pop()
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latent = l1(torch.tensor(42))
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with pytest.raises(RuntimeError):
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l2(latent)
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def test_pop_not_stashed():
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@skippable(pop=["foo"])
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class Pop(nn.Module):
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def forward(self, input):
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yield pop("foo")
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l1 = Pop()
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with pytest.raises(RuntimeError):
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l1(torch.tensor(42))
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def test_stash_none():
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@skippable(stash=["foo"])
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class Stash(nn.Module):
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def forward(self, input):
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yield stash("foo", None)
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return input * 2 # noqa: B901
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l1 = Stash()
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l1(torch.tensor(42))
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if __name__ == "__main__":
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run_tests()
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