86 lines
3.1 KiB
Python
86 lines
3.1 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 one_hot."""
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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_one_hot_tests(options):
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"""Make a set of tests to do one_hot."""
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test_parameters = [{
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"indices_type": [tf.int32, tf.int64],
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"indices_shape": [[3], [4, 4], [1, 5], [5, 1]],
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"axis": [0, 1],
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"dtype": [tf.int32, tf.int64, tf.float32],
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"provide_optional_inputs": [True, False],
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}]
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def build_graph(parameters):
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"""Build the one_hot op testing graph."""
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indices = tf.compat.v1.placeholder(
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dtype=parameters["indices_type"],
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name="indices",
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shape=parameters["indices_shape"])
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depth = tf.compat.v1.placeholder(dtype=tf.int32, name="depth", shape=())
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if not parameters["provide_optional_inputs"]:
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out = tf.one_hot(indices=indices, depth=depth)
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return [indices, depth], [out]
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on_value = tf.compat.v1.placeholder(
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dtype=parameters["dtype"], name="on_value", shape=())
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off_value = tf.compat.v1.placeholder(
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dtype=parameters["dtype"], name="off_value", shape=())
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out = tf.one_hot(
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indices=indices,
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depth=depth,
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on_value=on_value,
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off_value=off_value,
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axis=parameters["axis"],
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dtype=parameters["dtype"])
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return [indices, depth, on_value, off_value], [out]
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def build_inputs(parameters, sess, inputs, outputs):
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"""Build the input for one_hot op."""
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input_values = [
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create_tensor_data(
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parameters["indices_type"],
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shape=parameters["indices_shape"],
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min_value=-1,
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max_value=10),
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create_tensor_data(tf.int32, shape=None, min_value=1, max_value=10),
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]
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if parameters["provide_optional_inputs"]:
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input_values.append(
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create_tensor_data(
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parameters["dtype"], shape=None, min_value=1, max_value=10))
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input_values.append(
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create_tensor_data(
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parameters["dtype"], shape=None, min_value=-1, max_value=0))
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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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