# Copyright 2019 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. # ============================================================================== """Test configs for reverse_sequence.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function import tensorflow as tf from tensorflow.lite.testing.zip_test_utils import create_tensor_data from tensorflow.lite.testing.zip_test_utils import make_zip_of_tests from tensorflow.lite.testing.zip_test_utils import register_make_test_function @register_make_test_function() def make_reverse_sequence_tests(options): """Make a set of tests to do reverse_sequence.""" test_parameters = [{ "input_dtype": [tf.float32, tf.int32, tf.int64], "input_shape": [[8, 4, 5, 5, 6], [4, 4, 3, 5]], "seq_lengths": [[2, 2, 2, 2], [2, 1, 1, 0]], "seq_axis": [0, 3], "batch_axis": [1] }, { "input_dtype": [tf.float32], "input_shape": [[2, 4, 5, 5, 6]], "seq_lengths": [[2, 1]], "seq_axis": [2], "batch_axis": [0] }, { "input_dtype": [tf.float32], "input_shape": [[4, 2]], "seq_lengths": [[3, 1]], "seq_axis": [0], "batch_axis": [1] }] def build_graph(parameters): """Build the graph for reverse_sequence tests.""" input_value = tf.compat.v1.placeholder( dtype=parameters["input_dtype"], name="input", shape=parameters["input_shape"]) outs = tf.reverse_sequence( input_value, seq_lengths=parameters["seq_lengths"], batch_axis=parameters["batch_axis"], seq_axis=parameters["seq_axis"]) return [input_value], [outs] def build_inputs(parameters, sess, inputs, outputs): input_value = create_tensor_data(parameters["input_dtype"], parameters["input_shape"]) return [input_value], sess.run( outputs, feed_dict=dict(zip(inputs, [input_value]))) make_zip_of_tests(options, test_parameters, build_graph, build_inputs)