66c48046f1
This is mostly the result of an internal cleanup and formatting pass. PiperOrigin-RevId: 286318018 Change-Id: I8f9e2f7519070035da73f9f24d2fc90864abc51b
74 lines
2.6 KiB
Python
74 lines
2.6 KiB
Python
# Copyright 2017 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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"""Functional tests for XLA Reverse Ops."""
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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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import itertools
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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.platform import googletest
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class ReverseOpsTest(xla_test.XLATestCase):
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def testReverseOneDim(self):
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shape = (7, 5, 9, 11)
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for revdim in range(-len(shape), len(shape)):
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self._AssertReverseEqual([revdim], shape)
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def testReverseMoreThanOneDim(self):
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shape = (7, 5, 9, 11)
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# The offset is used to test various (but not all) combinations of negative
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# and positive axis indices that are guaranteed to not collide at the same
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# index.
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for revdims in itertools.chain.from_iterable(
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itertools.combinations(range(-offset,
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len(shape) - offset), k)
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for k in range(2,
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len(shape) + 1)
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for offset in range(0, len(shape))):
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self._AssertReverseEqual(revdims, shape)
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def _AssertReverseEqual(self, revdims, shape):
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np.random.seed(120)
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pval = np.random.randint(0, 100, size=shape).astype(float)
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with self.session():
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with self.test_scope():
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p = array_ops.placeholder(dtypes.int32, shape=shape)
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axis = constant_op.constant(
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np.array(revdims, dtype=np.int32),
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shape=(len(revdims),),
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dtype=dtypes.int32)
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rval = array_ops.reverse(p, axis).eval({p: pval})
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slices = [
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slice(-1, None, -1)
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if d in revdims or d - len(shape) in revdims else slice(None)
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for d in range(len(shape))
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]
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self.assertEqual(pval[slices].flatten().tolist(), rval.flatten().tolist())
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if __name__ == '__main__':
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googletest.main()
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