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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 the experimental input pipeline ops."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from tensorflow.contrib.data.python.ops import get_single_element
from tensorflow.python.data.ops import dataset_ops
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors
from tensorflow.python.framework import sparse_tensor
from tensorflow.python.ops import array_ops
from tensorflow.python.platform import test
class GetSingleElementTest(test.TestCase):
def testGetSingleElement(self):
skip_value = array_ops.placeholder(dtypes.int64, shape=[])
take_value = array_ops.placeholder_with_default(
constant_op.constant(1, dtype=dtypes.int64), shape=[])
def make_sparse(x):
x_1d = array_ops.reshape(x, [1])
x_2d = array_ops.reshape(x, [1, 1])
return sparse_tensor.SparseTensor(x_2d, x_1d, x_1d)
dataset = (dataset_ops.Dataset.range(100)
.skip(skip_value)
.map(lambda x: (x * x, make_sparse(x)))
.take(take_value))
element = get_single_element.get_single_element(dataset)
with self.test_session() as sess:
for x in [0, 5, 10]:
dense_val, sparse_val = sess.run(element, feed_dict={skip_value: x})
self.assertEqual(x * x, dense_val)
self.assertAllEqual([[x]], sparse_val.indices)
self.assertAllEqual([x], sparse_val.values)
self.assertAllEqual([x], sparse_val.dense_shape)
with self.assertRaisesRegexp(errors.InvalidArgumentError,
"Dataset was empty."):
sess.run(element, feed_dict={skip_value: 100})
with self.assertRaisesRegexp(errors.InvalidArgumentError,
"Dataset had more than one element."):
sess.run(element, feed_dict={skip_value: 0, take_value: 2})
if __name__ == "__main__":
test.main()
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