mirror of
https://github.com/saymrwulf/pytorch.git
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3b1a5a1b8a
Summary: Followup to the [first refactor](https://github.com/pytorch/pytorch/pull/11350). Increase coverage of tests Pull Request resolved: https://github.com/pytorch/pytorch/pull/11811 Reviewed By: houseroad Differential Revision: D9923074 Pulled By: ajyu fbshipit-source-id: 0f899bb9e9a75bf7ed939e06cc9b028daa7f6bd9
69 lines
2.2 KiB
Python
69 lines
2.2 KiB
Python
# Copyright (c) 2016-present, Facebook, Inc.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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##############################################################################
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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from __future__ import unicode_literals
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import hypothesis.strategies as st
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import numpy as np
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from functools import partial
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from caffe2.python import core
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import caffe2.python.hypothesis_test_util as hu
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import caffe2.python.serialized_test.serialized_test_util as serial
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def _unique_ref(x, return_inverse):
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ret = np.unique(x, return_inverse=return_inverse)
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if not return_inverse:
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ret = [ret]
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return ret
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class TestUniqueOps(serial.SerializedTestCase):
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@serial.given(
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X=hu.tensor1d(
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# allow empty
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min_len=0,
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dtype=np.int32,
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# allow negatives
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elements=st.integers(min_value=-10, max_value=10)),
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return_remapping=st.booleans(),
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**hu.gcs
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)
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def test_unique_op(self, X, return_remapping, gc, dc):
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# impl of unique op does not guarantees return order, sort the input
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# so different impl return same outputs
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X = np.sort(X)
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op = core.CreateOperator(
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"Unique",
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['X'],
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["U", "remap"] if return_remapping else ["U"],
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)
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self.assertDeviceChecks(
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device_options=dc,
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op=op,
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inputs=[X],
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outputs_to_check=[0, 1] if return_remapping else [0]
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)
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self.assertReferenceChecks(
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device_option=gc,
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op=op,
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inputs=[X],
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reference=partial(_unique_ref, return_inverse=return_remapping),
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)
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