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# Copyright 2015 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 SparseReorder."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import sparse_tensor
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gradient_checker
from tensorflow.python.ops import sparse_ops
import tensorflow.python.ops.sparse_grad # pylint: disable=unused-import
from tensorflow.python.platform import test
class SparseReorderTest(test.TestCase):
def _SparseTensorPlaceholder(self):
return sparse_tensor.SparseTensor(
array_ops.placeholder(dtypes.int64),
array_ops.placeholder(dtypes.float64),
array_ops.placeholder(dtypes.int64))
def _SparseTensorValue_5x6(self, permutation):
ind = np.array([[0, 0], [1, 0], [1, 3], [1, 4], [3, 2],
[3, 3]]).astype(np.int64)
val = np.array([0, 10, 13, 14, 32, 33]).astype(np.float64)
ind = ind[permutation]
val = val[permutation]
shape = np.array([5, 6]).astype(np.int64)
return sparse_tensor.SparseTensorValue(ind, val, shape)
def testStaticShapeInfoPreserved(self):
sp_input = sparse_tensor.SparseTensor.from_value(
self._SparseTensorValue_5x6(np.arange(6)))
self.assertAllEqual((5, 6), sp_input.get_shape())
sp_output = sparse_ops.sparse_reorder(sp_input)
self.assertAllEqual((5, 6), sp_output.get_shape())
def testAlreadyInOrder(self):
with self.test_session(use_gpu=False) as sess:
input_val = self._SparseTensorValue_5x6(np.arange(6))
sp_output = sparse_ops.sparse_reorder(input_val)
output_val = sess.run(sp_output)
self.assertAllEqual(output_val.indices, input_val.indices)
self.assertAllEqual(output_val.values, input_val.values)
self.assertAllEqual(output_val.dense_shape, input_val.dense_shape)
def testFeedAlreadyInOrder(self):
with self.test_session(use_gpu=False) as sess:
sp_input = self._SparseTensorPlaceholder()
input_val = self._SparseTensorValue_5x6(np.arange(6))
sp_output = sparse_ops.sparse_reorder(sp_input)
output_val = sess.run(sp_output, {sp_input: input_val})
self.assertAllEqual(output_val.indices, input_val.indices)
self.assertAllEqual(output_val.values, input_val.values)
self.assertAllEqual(output_val.dense_shape, input_val.dense_shape)
def testOutOfOrder(self):
expected_output_val = self._SparseTensorValue_5x6(np.arange(6))
with self.test_session(use_gpu=False) as sess:
for _ in range(5): # To test various random permutations
input_val = self._SparseTensorValue_5x6(np.random.permutation(6))
sp_output = sparse_ops.sparse_reorder(input_val)
output_val = sess.run(sp_output)
self.assertAllEqual(output_val.indices, expected_output_val.indices)
self.assertAllEqual(output_val.values, expected_output_val.values)
self.assertAllEqual(output_val.dense_shape,
expected_output_val.dense_shape)
def testFeedOutOfOrder(self):
expected_output_val = self._SparseTensorValue_5x6(np.arange(6))
with self.test_session(use_gpu=False) as sess:
for _ in range(5): # To test various random permutations
sp_input = self._SparseTensorPlaceholder()
input_val = self._SparseTensorValue_5x6(np.random.permutation(6))
sp_output = sparse_ops.sparse_reorder(sp_input)
output_val = sess.run(sp_output, {sp_input: input_val})
self.assertAllEqual(output_val.indices, expected_output_val.indices)
self.assertAllEqual(output_val.values, expected_output_val.values)
self.assertAllEqual(output_val.dense_shape,
expected_output_val.dense_shape)
def testGradients(self):
with self.test_session(use_gpu=False):
for _ in range(5): # To test various random permutations
input_val = self._SparseTensorValue_5x6(np.random.permutation(6))
sp_input = sparse_tensor.SparseTensor(input_val.indices,
input_val.values,
input_val.dense_shape)
sp_output = sparse_ops.sparse_reorder(sp_input)
err = gradient_checker.compute_gradient_error(
sp_input.values,
input_val.values.shape,
sp_output.values,
input_val.values.shape,
x_init_value=input_val.values)
self.assertLess(err, 1e-11)
if __name__ == "__main__":
test.main()
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