| # Copyright 2019 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 abs.""" |
| import tensorflow.compat.v1 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_abs_tests(options): |
| """Make a set of tests to do abs.""" |
| |
| # Chose a set of parameters |
| test_parameters = [{ |
| "input_shape": [[], [1], [2, 3], [1, 1, 1, 1], [1, 3, 4, 3], |
| [3, 15, 14, 3], [3, 1, 2, 4, 6], [2, 2, 3, 4, 5, 6]], |
| "dtype": [tf.float32], |
| "dynamic_range_quantize": [False, True], |
| "fully_quantize": [False], |
| "input_range": [(-10, 10), (-10, 0)], |
| }, { |
| "input_shape": [[], [1], [2, 3], [1, 1, 1, 1], [1, 3, 4, 3], |
| [3, 15, 14, 3], [3, 1, 2, 4, 6], [2, 2, 3, 4, 5, 6]], |
| "dtype": [tf.float32], |
| "dynamic_range_quantize": [False], |
| "fully_quantize": [True], |
| "input_range": [(-10, 10)], |
| }] |
| if options.use_experimental_converter: |
| test_parameters = test_parameters + [{ |
| "input_shape": [[], [1], [2, 3], [1, 1, 1, 1], [1, 3, 4, 3], |
| [3, 15, 14, 3], [3, 1, 2, 4, 6], [2, 2, 3, 4, 5, 6]], |
| "dtype": [tf.int16], |
| }] |
| |
| def build_graph(parameters): |
| input_tensor = tf.compat.v1.placeholder( |
| dtype=parameters["dtype"], |
| name="input", |
| shape=parameters["input_shape"]) |
| out = tf.abs(input_tensor) |
| return [input_tensor], [out] |
| |
| def build_inputs(parameters, sess, inputs, outputs): |
| min_value, max_value = (-10, 10) |
| if "input_range" in parameters: |
| min_value, max_value = parameters["input_range"] |
| input_values = create_tensor_data( |
| parameters["dtype"], |
| parameters["input_shape"], |
| min_value=min_value, |
| max_value=max_value) |
| return [input_values], sess.run( |
| outputs, feed_dict=dict(zip(inputs, [input_values]))) |
| |
| make_zip_of_tests(options, test_parameters, build_graph, build_inputs) |