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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.kernel_tests import dataset_serialization_test_base
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 ZipDatasetTest(test.TestCase):
def testZipDataset(self):
component_placeholders = [
array_ops.placeholder(dtypes.int64),
array_ops.placeholder(dtypes.int64),
array_ops.placeholder(dtypes.float64)
]
datasets = tuple([
dataset_ops.Dataset.from_tensor_slices(component_placeholder)
for component_placeholder in component_placeholders
])
zipped = dataset_ops.Dataset.zip(datasets)
iterator = zipped.make_initializable_iterator()
init_op = iterator.initializer
get_next = iterator.get_next()
with self.test_session() as sess:
equal_length_components = [
np.tile(np.array([[1], [2], [3], [4]]), 20),
np.tile(np.array([[12], [13], [14], [15]]), 22),
np.array([37.0, 38.0, 39.0, 40.0])
]
sess.run(init_op, feed_dict={ph: value for ph, value in zip(
component_placeholders, equal_length_components)})
for i in range(4):
results = sess.run(get_next)
for component, result_component in zip(
equal_length_components, results):
self.assertAllEqual(component[i], result_component)
with self.assertRaises(errors.OutOfRangeError):
sess.run(get_next)
variable_length_components = [[1, 2, 3, 4], [1, 2, 3, 4, 5], [1.0, 2.0]]
sess.run(init_op, feed_dict={ph: value for ph, value in zip(
component_placeholders, variable_length_components)})
for i in range(2):
results = sess.run(get_next)
for component, result_component in zip(
variable_length_components, results):
self.assertAllEqual(component[i], result_component)
with self.assertRaises(errors.OutOfRangeError):
sess.run(get_next)
def testNestedZipDataset(self):
component_placeholders = [
array_ops.placeholder(dtypes.int64, shape=[4, 20]),
array_ops.placeholder(dtypes.int64, shape=[4, 22]),
array_ops.placeholder(dtypes.float64, shape=[4])
]
datasets = [
dataset_ops.Dataset.from_tensor_slices(component_placeholder)
for component_placeholder in component_placeholders
]
zipped = dataset_ops.Dataset.zip((datasets[0], (datasets[1], datasets[2])))
iterator = zipped.make_initializable_iterator()
init_op = iterator.initializer
get_next = iterator.get_next()
self.assertEqual([20], get_next[0].shape)
self.assertEqual([22], get_next[1][0].shape)
self.assertEqual([], get_next[1][1].shape)
with self.test_session() as sess:
equal_length_components = [
np.tile(np.array([[1], [2], [3], [4]]), 20),
np.tile(np.array([[12], [13], [14], [15]]), 22),
np.array([37.0, 38.0, 39.0, 40.0])
]
sess.run(init_op, feed_dict={ph: value for ph, value in zip(
component_placeholders, equal_length_components)})
for i in range(4):
result1, (result2, result3) = sess.run(get_next)
self.assertAllEqual(equal_length_components[0][i], result1)
self.assertAllEqual(equal_length_components[1][i], result2)
self.assertAllEqual(equal_length_components[2][i], result3)
with self.assertRaises(errors.OutOfRangeError):
sess.run(get_next)
class ZipDatasetSerializationTest(
dataset_serialization_test_base.DatasetSerializationTestBase):
def _build_dataset(self, arr):
components = [
np.tile(np.array([[1], [2], [3], [4]]), 20),
np.tile(np.array([[12], [13], [14], [15]]), 22),
np.array(arr)
]
datasets = [
dataset_ops.Dataset.from_tensor_slices(component)
for component in components
]
return dataset_ops.Dataset.zip((datasets[0], (datasets[1], datasets[2])))
def testCore(self):
# Equal length components
arr = [37.0, 38.0, 39.0, 40.0]
num_outputs = len(arr)
self.run_core_tests(lambda: self._build_dataset(arr), None, num_outputs)
# Variable length components
diff_size_arr = [1.0, 2.0]
self.run_core_tests(lambda: self._build_dataset(diff_size_arr),
lambda: self._build_dataset(arr), 2)
if __name__ == "__main__":
test.main()
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