# 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.python.data.kernel_tests import test_base from tensorflow.python.data.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_base.DatasetTestBase): 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.cached_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.cached_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) if __name__ == "__main__": test.main()