| # Copyright 2021 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 exp.""" |
| from __future__ import absolute_import |
| from __future__ import division |
| from __future__ import print_function |
| |
| 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_conv3d_tests(options): |
| """Make a set of tests to do conv3d.""" |
| |
| test_parameters = [{ |
| "input_dtype": [tf.float32], |
| "input_shape": [[2, 3, 4, 5, 3], [2, 5, 6, 8, 3]], |
| "filter_shape": [[2, 2, 2, 3, 2], [1, 2, 2, 3, 2]], |
| "strides": [(1, 1, 1, 1, 1), (1, 1, 1, 2, 1), (1, 1, 2, 2, 1), |
| (1, 2, 1, 2, 1), (1, 2, 2, 2, 1)], |
| "dilations": [(1, 1, 1, 1, 1)], |
| "padding": ["SAME", "VALID"], |
| }] |
| |
| def build_graph(parameters): |
| """Build the exp op testing graph.""" |
| input_tensor = tf.compat.v1.placeholder( |
| dtype=parameters["input_dtype"], |
| name="input", |
| shape=parameters["input_shape"]) |
| filter_tensor = tf.compat.v1.placeholder( |
| dtype=parameters["input_dtype"], |
| name="filter", |
| shape=parameters["filter_shape"]) |
| |
| out = tf.nn.conv3d( |
| input_tensor, |
| filter_tensor, |
| strides=parameters["strides"], |
| dilations=parameters["dilations"], |
| padding=parameters["padding"]) |
| return [input_tensor, filter_tensor], [out] |
| |
| def build_inputs(parameters, sess, inputs, outputs): |
| values = [ |
| create_tensor_data( |
| parameters["input_dtype"], |
| parameters["input_shape"], |
| min_value=-100, |
| max_value=9), |
| create_tensor_data( |
| parameters["input_dtype"], |
| parameters["filter_shape"], |
| min_value=-3, |
| max_value=3) |
| ] |
| return values, sess.run(outputs, feed_dict=dict(zip(inputs, values))) |
| |
| make_zip_of_tests(options, test_parameters, build_graph, build_inputs) |