wehub-resource-sync
87 lines
2.9 KiB
Python
87 lines
2.9 KiB
Python
# Copyright 2023 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 bitcast."""
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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_bitcast_tests(options):
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"""Generate examples for bitcast."""
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test_parameters = [
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{
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"input_dtype": [tf.int32],
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"output_dtype": [tf.uint32],
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"input_shape": [[], [1], [1, 2], [3, 4, 5, 6]],
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},
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{
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"input_dtype": [tf.uint32],
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"output_dtype": [tf.int32],
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"input_shape": [[], [1], [1, 2], [3, 4, 5, 6]],
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},
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{
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"input_dtype": [tf.uint32],
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"output_dtype": [tf.int16],
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"input_shape": [[], [1], [1, 2], [3, 4, 5, 6]],
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},
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{
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"input_dtype": [tf.int16],
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"output_dtype": [tf.uint32],
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"input_shape": [[2], [1, 2], [1, 2, 2], [3, 4, 5, 6, 2]],
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},
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{
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"input_dtype": [tf.int32],
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"output_dtype": [tf.int16],
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"input_shape": [[], [1], [1, 2], [3, 4, 5, 6]],
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},
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{
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"input_dtype": [tf.uint16],
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"output_dtype": [tf.uint32],
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"input_shape": [[2], [1, 2], [1, 2, 2], [3, 4, 5, 6, 2]],
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},
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{
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"input_dtype": [tf.float32],
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"output_dtype": [tf.int16],
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"input_shape": [[], [1], [1, 2], [3, 4, 5, 6]],
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},
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{
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"input_dtype": [tf.int16],
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"output_dtype": [tf.float32],
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"input_shape": [[2], [1, 2], [1, 2, 2], [3, 4, 5, 6, 2]],
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}
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]
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def build_graph(parameters):
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"""Build the bitcast testing graph."""
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input_value = tf.compat.v1.placeholder(
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dtype=parameters["input_dtype"],
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name="input",
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shape=parameters["input_shape"],
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)
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out = tf.bitcast(input_value, parameters["output_dtype"])
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return [input_value], [out]
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def build_inputs(parameters, sess, inputs, outputs):
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input_value = create_tensor_data(
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parameters["input_dtype"], parameters["input_shape"]
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)
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return [input_value], sess.run(
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outputs, feed_dict=dict(zip(inputs, [input_value]))
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)
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make_zip_of_tests(options, test_parameters, build_graph, build_inputs)
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