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# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Tests for tf.dynamic_stitch."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
from tensorflow.compiler.tests import xla_test
from tensorflow.python.framework import dtypes
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import data_flow_ops
from tensorflow.python.platform import googletest
class DynamicStitchTest(xla_test.XLATestCase):
def _AssertDynamicStitchResultIs(self, indices, data, expected):
with self.cached_session() as session:
index_placeholders = [
array_ops.placeholder(dtypes.as_dtype(arg.dtype)) for arg in indices
]
data_placeholders = [
array_ops.placeholder(dtypes.as_dtype(arg.dtype)) for arg in data
]
with self.test_scope():
output = data_flow_ops.dynamic_stitch(index_placeholders,
data_placeholders)
feed_dict = {}
for placeholder, value in zip(index_placeholders, indices):
feed_dict[placeholder] = value
for placeholder, value in zip(data_placeholders, data):
feed_dict[placeholder] = value
result = session.run(output, feed_dict=feed_dict)
self.assertAllClose(expected, result, rtol=1e-3)
def testSimpleEmpty(self):
idx1 = np.array([0, 2], dtype=np.int32)
idx2 = np.array([[1], [3]], dtype=np.int32)
val1 = np.array([[], []], dtype=np.int32)
val2 = np.array([[[]], [[]]], dtype=np.int32)
self._AssertDynamicStitchResultIs(
[idx1, idx2], [val1, val2],
expected=np.array([[], [], [], []], np.int32))
def testSimple1D(self):
val1 = np.array([0, 4, 7], dtype=np.int32)
val2 = np.array([1, 6, 2, 3, 5], dtype=np.int32)
val3 = np.array([0, 40, 70], dtype=np.float32)
val4 = np.array([10, 60, 20, 30, 50], dtype=np.float32)
expected = np.array([0, 10, 20, 30, 40, 50, 60, 70], dtype=np.float32)
self._AssertDynamicStitchResultIs(
[val1, val2], [val3, val4], expected=expected)
def testSimple2D(self):
val1 = np.array([0, 4, 7], dtype=np.int32)
val2 = np.array([1, 6], dtype=np.int32)
val3 = np.array([2, 3, 5], dtype=np.int32)
val4 = np.array([[0, 1], [40, 41], [70, 71]], dtype=np.float32)
val5 = np.array([[10, 11], [60, 61]], dtype=np.float32)
val6 = np.array([[20, 21], [30, 31], [50, 51]], dtype=np.float32)
expected = np.array(
[[0, 1], [10, 11], [20, 21], [30, 31], [40, 41], [50, 51], [60, 61],
[70, 71]],
dtype=np.float32)
self._AssertDynamicStitchResultIs(
[val1, val2, val3], [val4, val5, val6], expected=expected)
if __name__ == "__main__":
googletest.main()
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