wehub-resource-sync
47 lines
1.7 KiB
Python
47 lines
1.7 KiB
Python
# Copyright 2023 The TensorFlow Authors. All Rights Reserved.
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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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"""Tests for unique ops."""
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import numpy as np
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from tensorflow.compiler.tests import xla_test
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from tensorflow.python.framework import constant_op
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from tensorflow.python.framework import dtypes
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from tensorflow.python.ops import array_ops
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from tensorflow.python.ops import gen_array_ops
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from tensorflow.python.platform import googletest
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class UniqueTest(xla_test.XLATestCase):
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def testNegativeAxis(self):
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"""Verifies that an axis with negative index is converted to positive."""
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with self.session() as session:
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with self.test_scope():
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px = array_ops.placeholder(dtypes.float32, [2, 1, 1], name="x")
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axis = constant_op.constant([-1], dtype=dtypes.int32)
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output = gen_array_ops.unique_v2(px, axis)
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result = session.run(
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output, {px: np.array([[[-2.0]], [[10.0]]], dtype=np.float32)}
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)
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self.assertAllEqual(
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result.y, np.array([[[-2.0]], [[10.0]]], dtype=np.float32)
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)
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self.assertAllEqual(result.idx, np.array([0], dtype=np.int32))
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if __name__ == "__main__":
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googletest.main()
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