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