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a9dca53438
RFC: https://github.com/pytorch/rfcs/pull/54 First commit is the contents of https://github.com/Quansight-Labs/numpy_pytorch_interop/ We have already been using this in core for the last few months as a external dependency. This PR pulls all these into core. In the next commits, I do a number of things in this order - Fix a few small issues - Make the tests that this PR adds pass - Bend backwards until lintrunner passes - Remove the optional dependency on `torch_np` and simply rely on the upstreamed code - Fix a number dynamo tests that were passing before (they were not tasting anything I think) and are not passing now. Missing from this PR (but not blocking): - Have a flag that deactivates tracing NumPy functions and simply breaks. There used to be one but after the merge stopped working and I removed it. @lezcano to investigate. - https://github.com/pytorch/pytorch/pull/106431#issuecomment-1667079543. @voznesenskym to submit a fix after we merge. All the tests in `tests/torch_np` take about 75s to run. This was a work by @ev-br, @rgommers @honno and I. I did not create this PR via ghstack (which would have been convenient) as this is a collaboration, and ghstack doesn't allow for shared contributions. Pull Request resolved: https://github.com/pytorch/pytorch/pull/106211 Approved by: https://github.com/ezyang
51 lines
1.1 KiB
Python
51 lines
1.1 KiB
Python
# Owner(s): ["module: dynamo"]
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"""Light smoke test switching between numpy to pytorch random streams.
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"""
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import pytest
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import torch._numpy as tnp
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from torch._numpy.testing import assert_equal
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def test_uniform():
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r = tnp.random.uniform(0, 1, size=10)
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def test_shuffle():
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x = tnp.arange(10)
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tnp.random.shuffle(x)
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def test_numpy_global():
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tnp.random.USE_NUMPY_RANDOM = True
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tnp.random.seed(12345)
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x = tnp.random.uniform(0, 1, size=11)
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# check that the stream is identical to numpy's
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import numpy as _np
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_np.random.seed(12345)
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x_np = _np.random.uniform(0, 1, size=11)
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assert_equal(x, tnp.asarray(x_np))
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# switch to the pytorch stream, variates differ
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tnp.random.USE_NUMPY_RANDOM = False
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tnp.random.seed(12345)
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x_1 = tnp.random.uniform(0, 1, size=11)
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assert not (x_1 == x).all()
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def test_wrong_global():
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try:
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oldstate = tnp.random.USE_NUMPY_RANDOM
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tnp.random.USE_NUMPY_RANDOM = "oops"
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with pytest.raises(ValueError):
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tnp.random.rand()
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finally:
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tnp.random.USE_NUMPY_RANDOM = oldstate
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