STT-tensorflow/tensorflow/lite/testing/op_tests/reverse_sequence.py
Nupur Garg 2fb71ff8cf Make generate_examples run in 2.0.
PiperOrigin-RevId: 298616596
Change-Id: Ib0be0a8929e75634924c28165f6fcd998b77add9
2020-03-03 08:59:39 -08:00

70 lines
2.5 KiB
Python

# 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.compat.v1 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)