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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
94 lines
3.4 KiB
Python
94 lines
3.4 KiB
Python
# Owner(s): ["module: dynamo"]
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import pytest
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import torch._numpy as np
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from pytest import raises as assert_raises
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from torch._numpy.testing import assert_array_equal, assert_equal
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class TestArange:
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def test_infinite(self):
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assert_raises(
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(RuntimeError, ValueError), np.arange, 0, np.inf
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) # "size exceeded",
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def test_nan_step(self):
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assert_raises(
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(RuntimeError, ValueError), np.arange, 0, 1, np.nan
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) # "cannot compute length",
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def test_zero_step(self):
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assert_raises(ZeroDivisionError, np.arange, 0, 10, 0)
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assert_raises(ZeroDivisionError, np.arange, 0.0, 10.0, 0.0)
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# empty range
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assert_raises(ZeroDivisionError, np.arange, 0, 0, 0)
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assert_raises(ZeroDivisionError, np.arange, 0.0, 0.0, 0.0)
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def test_require_range(self):
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assert_raises(TypeError, np.arange)
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assert_raises(TypeError, np.arange, step=3)
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assert_raises(TypeError, np.arange, dtype="int64")
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@pytest.mark.xfail(reason="XXX: arange(start=0, stop, step=1)")
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def test_require_range_2(self):
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assert_raises(TypeError, np.arange, start=4)
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def test_start_stop_kwarg(self):
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keyword_stop = np.arange(stop=3)
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keyword_zerotostop = np.arange(start=0, stop=3)
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keyword_start_stop = np.arange(start=3, stop=9)
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assert len(keyword_stop) == 3
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assert len(keyword_zerotostop) == 3
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assert len(keyword_start_stop) == 6
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assert_array_equal(keyword_stop, keyword_zerotostop)
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@pytest.mark.xfail(reason="XXX: arange(..., dtype=bool)")
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def test_arange_booleans(self):
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# Arange makes some sense for booleans and works up to length 2.
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# But it is weird since `arange(2, 4, dtype=bool)` works.
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# Arguably, much or all of this could be deprecated/removed.
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res = np.arange(False, dtype=bool)
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assert_array_equal(res, np.array([], dtype="bool"))
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res = np.arange(True, dtype="bool")
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assert_array_equal(res, [False])
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res = np.arange(2, dtype="bool")
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assert_array_equal(res, [False, True])
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# This case is especially weird, but drops out without special case:
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res = np.arange(6, 8, dtype="bool")
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assert_array_equal(res, [True, True])
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with pytest.raises(TypeError):
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np.arange(3, dtype="bool")
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@pytest.mark.parametrize("which", [0, 1, 2])
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def test_error_paths_and_promotion(self, which):
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args = [0, 10, 2] # start, stop, and step
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args[which] = np.float64(2.0) # should ensure float64 output
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assert np.arange(*args).dtype == np.float64
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# Cover stranger error path, test only to achieve code coverage!
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args[which] = [None, []]
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with pytest.raises((ValueError, RuntimeError)):
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# Fails discovering start dtype
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np.arange(*args)
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class TestAppend:
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# tests taken from np.append docstring
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def test_basic(self):
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result = np.append([1, 2, 3], [[4, 5, 6], [7, 8, 9]])
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assert_equal(result, np.arange(1, 10, dtype=int))
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# When `axis` is specified, `values` must have the correct shape.
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result = np.append([[1, 2, 3], [4, 5, 6]], [[7, 8, 9]], axis=0)
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assert_equal(result, np.arange(1, 10, dtype=int).reshape((3, 3)))
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with pytest.raises((RuntimeError, ValueError)):
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np.append([[1, 2, 3], [4, 5, 6]], [7, 8, 9], axis=0)
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