66 lines
2.3 KiB
Python
66 lines
2.3 KiB
Python
# Copyright 2019 The TensorFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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"""Test configs for unique."""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import tensorflow.compat.v1 as tf
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from tensorflow.lite.testing.zip_test_utils import create_tensor_data
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from tensorflow.lite.testing.zip_test_utils import make_zip_of_tests
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from tensorflow.lite.testing.zip_test_utils import register_make_test_function
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@register_make_test_function()
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def make_unique_tests(options):
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"""Make a set of tests for Unique op."""
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test_parameters = [{
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"input_shape": [[1]],
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"index_type": [tf.int32, tf.int64, None],
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"input_values": [3]
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}, {
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"input_shape": [[5]],
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"index_type": [tf.int32, tf.int64],
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"input_values": [[3, 2, 1, 2, 3]]
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}, {
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"input_shape": [[7]],
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"index_type": [tf.int32, tf.int64],
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"input_values": [[1, 1, 1, 1, 1, 1, 1]]
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}, {
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"input_shape": [[5]],
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"index_type": [tf.int32, tf.int64],
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"input_values": [[3, 2, 1, 0, -1]]
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}]
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def build_graph(parameters):
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"""Build the graph for the test case."""
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input_tensor = tf.compat.v1.placeholder(
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dtype=tf.int32, name="input", shape=parameters["input_shape"])
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if parameters["index_type"] is None:
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output = tf.unique(input_tensor)
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else:
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output = tf.unique(input_tensor, parameters["index_type"])
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return [input_tensor], output
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def build_inputs(parameters, sess, inputs, outputs):
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input_values = [create_tensor_data(tf.int32, parameters["input_shape"])]
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return input_values, sess.run(
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outputs, feed_dict=dict(zip(inputs, input_values)))
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make_zip_of_tests(options, test_parameters, build_graph, build_inputs)
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