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# 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 tensor_list_resize."""
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
from tensorflow.python.ops import list_ops
@register_make_test_function()
def make_tensor_list_resize_tests(options):
"""Make a set of tests to do TensorListResize."""
test_parameters = [
{
"element_dtype": [tf.float32, tf.int32],
"num_elements": [4, 5, 6],
"element_shape": [[], [5], [3, 3]],
"new_size": [1, 3, 5, 7],
},
]
def build_graph(parameters):
"""Build the TensorListResize op testing graph."""
data = tf.placeholder(
dtype=parameters["element_dtype"],
shape=[parameters["num_elements"]] + parameters["element_shape"])
tensor_list = list_ops.tensor_list_from_tensor(data,
parameters["element_shape"])
tensor_list = list_ops.tensor_list_resize(tensor_list,
parameters["new_size"])
out = list_ops.tensor_list_stack(
tensor_list, element_dtype=parameters["element_dtype"])
return [data], [out]
def build_inputs(parameters, sess, inputs, outputs):
data = create_tensor_data(parameters["element_dtype"],
[parameters["num_elements"]] +
parameters["element_shape"])
return [data], sess.run(outputs, feed_dict=dict(zip(inputs, [data])))
make_zip_of_tests(options, test_parameters, build_graph, build_inputs)