wehub-resource-sync
82 lines
3.0 KiB
Python
82 lines
3.0 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 tile."""
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import tensorflow 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_tile_tests(options):
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"""Make a set of tests to do tile."""
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test_parameters = [
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{
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"input_dtype": [tf.float32, tf.int32, tf.bool, tf.string],
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"input_shape": [[3, 2, 1], [2, 2, 2]],
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"multiplier_dtype": [tf.int32, tf.int64],
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"multiplier_shape": [[3]]
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},
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{
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"input_dtype": [tf.float32, tf.int32],
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"input_shape": [[]],
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"multiplier_dtype": [tf.int32, tf.int64],
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"multiplier_shape": [[0]]
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},
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{
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"input_dtype": [tf.float32],
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"input_shape": [[3, 2, 1]],
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"multiplier_dtype": [tf.int32, tf.int64],
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"multiplier_shape": [[3]],
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"fully_quantize": [True],
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# The input range is used to create representative dataset for both
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# input and multiplier so it needs to be positive.
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"input_range": [(1, 10)],
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}
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]
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def build_graph(parameters):
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"""Build the tile op testing graph."""
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input_value = tf.compat.v1.placeholder(
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dtype=parameters["input_dtype"],
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shape=parameters["input_shape"],
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name="input")
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multiplier_value = tf.compat.v1.placeholder(
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dtype=parameters["multiplier_dtype"],
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shape=parameters["multiplier_shape"],
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name="multiplier")
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out = tf.tile(input_value, multiplier_value)
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return [input_value, multiplier_value], [out]
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def build_inputs(parameters, sess, inputs, outputs):
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min_value, max_value = parameters.get("input_range", (-10, 10))
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input_value = create_tensor_data(
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parameters["input_dtype"],
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parameters["input_shape"],
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min_value=min_value,
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max_value=max_value)
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multipliers_value = create_tensor_data(
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parameters["multiplier_dtype"],
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parameters["multiplier_shape"],
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min_value=0)
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return [input_value, multipliers_value], sess.run(
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outputs,
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feed_dict={
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inputs[0]: input_value,
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inputs[1]: multipliers_value
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})
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make_zip_of_tests(options, test_parameters, build_graph, build_inputs)
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