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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
import numpy as np
from tensorflow.contrib.data.python.ops import dataset_ops
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors
from tensorflow.python.ops import array_ops
from tensorflow.python.platform import test
class SequenceDatasetTest(test.TestCase):
def testRepeatTensorDataset(self):
"""Test a dataset that repeats its input multiple times."""
components = (np.array(1), np.array([1, 2, 3]), np.array(37.0))
# This placeholder can be fed when dataset-definition subgraph
# runs (i.e. `init_op` below) to configure the number of
# repetitions used in a particular iterator.
count_placeholder = array_ops.placeholder(dtypes.int64, shape=[])
iterator = (dataset_ops.Dataset.from_tensors(components)
.repeat(count_placeholder).make_initializable_iterator())
init_op = iterator.initializer
get_next = iterator.get_next()
self.assertEqual([c.shape for c in components],
[t.shape for t in get_next])
with self.test_session() as sess:
# Test a finite repetition.
sess.run(init_op, feed_dict={count_placeholder: 3})
for _ in range(3):
results = sess.run(get_next)
for component, result_component in zip(components, results):
self.assertAllEqual(component, result_component)
with self.assertRaises(errors.OutOfRangeError):
sess.run(get_next)
# Test a different finite repetition.
sess.run(init_op, feed_dict={count_placeholder: 7})
for _ in range(7):
results = sess.run(get_next)
for component, result_component in zip(components, results):
self.assertAllEqual(component, result_component)
with self.assertRaises(errors.OutOfRangeError):
sess.run(get_next)
# Test an empty repetition.
sess.run(init_op, feed_dict={count_placeholder: 0})
with self.assertRaises(errors.OutOfRangeError):
sess.run(get_next)
# Test an infinite repetition.
# NOTE(mrry): There's not a good way to test that the sequence
# actually is infinite.
sess.run(init_op, feed_dict={count_placeholder: -1})
for _ in range(17):
results = sess.run(get_next)
for component, result_component in zip(components, results):
self.assertAllEqual(component, result_component)
def testTakeTensorDataset(self):
components = (np.arange(10),)
count_placeholder = array_ops.placeholder(dtypes.int64, shape=[])
iterator = (dataset_ops.Dataset.from_tensor_slices(components)
.take(count_placeholder).make_initializable_iterator())
init_op = iterator.initializer
get_next = iterator.get_next()
self.assertEqual([c.shape[1:] for c in components],
[t.shape for t in get_next])
with self.test_session() as sess:
# Take fewer than input size
sess.run(init_op, feed_dict={count_placeholder: 4})
for i in range(4):
results = sess.run(get_next)
self.assertAllEqual(results, components[0][i:i+1])
with self.assertRaises(errors.OutOfRangeError):
sess.run(get_next)
# Take more than input size
sess.run(init_op, feed_dict={count_placeholder: 25})
for i in range(10):
results = sess.run(get_next)
self.assertAllEqual(results, components[0][i:i+1])
with self.assertRaises(errors.OutOfRangeError):
sess.run(get_next)
# Take all of input
sess.run(init_op, feed_dict={count_placeholder: -1})
for i in range(10):
results = sess.run(get_next)
self.assertAllEqual(results, components[0][i:i+1])
with self.assertRaises(errors.OutOfRangeError):
sess.run(get_next)
# Take nothing
sess.run(init_op, feed_dict={count_placeholder: 0})
with self.assertRaises(errors.OutOfRangeError):
sess.run(get_next)
def testSkipTensorDataset(self):
components = (np.arange(10),)
count_placeholder = array_ops.placeholder(dtypes.int64, shape=[])
iterator = (dataset_ops.Dataset.from_tensor_slices(components)
.skip(count_placeholder).make_initializable_iterator())
init_op = iterator.initializer
get_next = iterator.get_next()
self.assertEqual([c.shape[1:] for c in components],
[t.shape for t in get_next])
with self.test_session() as sess:
# Skip fewer than input size, we should skip
# the first 4 elements and then read the rest.
sess.run(init_op, feed_dict={count_placeholder: 4})
for i in range(4, 10):
results = sess.run(get_next)
self.assertAllEqual(results, components[0][i:i+1])
with self.assertRaises(errors.OutOfRangeError):
sess.run(get_next)
# Skip more than input size: get nothing.
sess.run(init_op, feed_dict={count_placeholder: 25})
with self.assertRaises(errors.OutOfRangeError):
sess.run(get_next)
# Skip exactly input size.
sess.run(init_op, feed_dict={count_placeholder: 10})
with self.assertRaises(errors.OutOfRangeError):
sess.run(get_next)
# Set -1 for 'count': skip the entire dataset.
sess.run(init_op, feed_dict={count_placeholder: -1})
with self.assertRaises(errors.OutOfRangeError):
sess.run(get_next)
# Skip nothing
sess.run(init_op, feed_dict={count_placeholder: 0})
for i in range(0, 10):
results = sess.run(get_next)
self.assertAllEqual(results, components[0][i:i+1])
with self.assertRaises(errors.OutOfRangeError):
sess.run(get_next)
def testRepeatRepeatTensorDataset(self):
"""Test the composition of repeat datasets."""
components = (np.array(1), np.array([1, 2, 3]), np.array(37.0))
inner_count = array_ops.placeholder(dtypes.int64, shape=[])
outer_count = array_ops.placeholder(dtypes.int64, shape=[])
iterator = (dataset_ops.Dataset.from_tensors(components).repeat(inner_count)
.repeat(outer_count).make_initializable_iterator())
init_op = iterator.initializer
get_next = iterator.get_next()
self.assertEqual([c.shape for c in components],
[t.shape for t in get_next])
with self.test_session() as sess:
sess.run(init_op, feed_dict={inner_count: 7, outer_count: 14})
for _ in range(7 * 14):
results = sess.run(get_next)
for component, result_component in zip(components, results):
self.assertAllEqual(component, result_component)
with self.assertRaises(errors.OutOfRangeError):
sess.run(get_next)
def testRepeatEmptyDataset(self):
"""Test that repeating an empty dataset does not hang."""
iterator = (dataset_ops.Dataset.from_tensors(0).repeat(10).skip(10)
.repeat(-1).make_initializable_iterator())
init_op = iterator.initializer
get_next = iterator.get_next()
with self.test_session() as sess:
sess.run(init_op)
with self.assertRaisesRegexp(
errors.OutOfRangeError,
"Attempted to repeat an empty dataset infinitely."):
sess.run(get_next)
if __name__ == "__main__":
test.main()
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