# 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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"""Tests for tf.dynamic_stitch."""
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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 numpy as np
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from tensorflow.compiler.tests import xla_test
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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 data_flow_ops
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from tensorflow.python.platform import googletest
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class DynamicStitchTest(xla_test.XLATestCase):
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def _AssertDynamicStitchResultIs(self, indices, data, expected):
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with self.cached_session() as session:
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index_placeholders = [
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array_ops.placeholder(dtypes.as_dtype(arg.dtype)) for arg in indices
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]
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data_placeholders = [
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array_ops.placeholder(dtypes.as_dtype(arg.dtype)) for arg in data
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]
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with self.test_scope():
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output = data_flow_ops.dynamic_stitch(index_placeholders,
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data_placeholders)
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feed_dict = {}
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for placeholder, value in zip(index_placeholders, indices):
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feed_dict[placeholder] = value
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for placeholder, value in zip(data_placeholders, data):
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feed_dict[placeholder] = value
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result = session.run(output, feed_dict=feed_dict)
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self.assertAllClose(expected, result, rtol=1e-3)
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def testSimpleEmpty(self):
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idx1 = np.array([0, 2], dtype=np.int32)
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idx2 = np.array([[1], [3]], dtype=np.int32)
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val1 = np.array([[], []], dtype=np.int32)
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val2 = np.array([[[]], [[]]], dtype=np.int32)
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self._AssertDynamicStitchResultIs(
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[idx1, idx2], [val1, val2],
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expected=np.array([[], [], [], []], np.int32))
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def testEmptyIndex(self):
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idx1 = np.array([], dtype=np.int32)
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idx2 = np.array([[], []], dtype=np.int32)
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val1 = np.ndarray(shape=(0, 9), dtype=np.int32)
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val2 = np.ndarray(shape=(2, 0, 9), dtype=np.int32)
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self._AssertDynamicStitchResultIs([idx1, idx2], [val1, val2],
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expected=np.ndarray(
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shape=(0, 9), dtype=np.int32))
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def testSimple1D(self):
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val1 = np.array([0, 4, 7], dtype=np.int32)
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val2 = np.array([1, 6, 2, 3, 5], dtype=np.int32)
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val3 = np.array([0, 40, 70], dtype=np.float32)
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val4 = np.array([10, 60, 20, 30, 50], dtype=np.float32)
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expected = np.array([0, 10, 20, 30, 40, 50, 60, 70], dtype=np.float32)
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self._AssertDynamicStitchResultIs(
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[val1, val2], [val3, val4], expected=expected)
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def testSimple2D(self):
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val1 = np.array([0, 4, 7], dtype=np.int32)
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val2 = np.array([1, 6], dtype=np.int32)
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val3 = np.array([2, 3, 5], dtype=np.int32)
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val4 = np.array([[0, 1], [40, 41], [70, 71]], dtype=np.float32)
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val5 = np.array([[10, 11], [60, 61]], dtype=np.float32)
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val6 = np.array([[20, 21], [30, 31], [50, 51]], dtype=np.float32)
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expected = np.array(
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[[0, 1], [10, 11], [20, 21], [30, 31], [40, 41], [50, 51], [60, 61],
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[70, 71]],
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dtype=np.float32)
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self._AssertDynamicStitchResultIs(
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[val1, val2, val3], [val4, val5, val6], expected=expected)
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if __name__ == "__main__":
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googletest.main()
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