# coding=utf-8 # Copyright 2021 The Deeplab2 Authors. # # 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. """Tests for model.builder.""" import os from absl.testing import parameterized import tensorflow as tf from google.protobuf import text_format from deeplab2 import config_pb2 from deeplab2.model import builder from deeplab2.model.decoder import motion_deeplab_decoder from deeplab2.model.encoder import axial_resnet_instances from deeplab2.model.encoder import mobilenet # resources dependency _CONFIG_PATH = 'deeplab2/configs/example' def _read_proto_file(filename, proto): filename = filename # OSS: removed internal filename loading. with tf.io.gfile.GFile(filename, 'r') as proto_file: return text_format.ParseLines(proto_file, proto) class BuilderTest(tf.test.TestCase, parameterized.TestCase): def test_resnet50_encoder_creation(self): backbone_options = config_pb2.ModelOptions.BackboneOptions( name='resnet50', output_stride=32) encoder = builder.create_encoder( backbone_options, tf.keras.layers.experimental.SyncBatchNormalization) self.assertIsInstance(encoder, axial_resnet_instances.ResNet50) @parameterized.parameters('mobilenet_v3_large', 'mobilenet_v3_small') def test_mobilenet_encoder_creation(self, model_name): backbone_options = config_pb2.ModelOptions.BackboneOptions( name=model_name, use_squeeze_and_excite=True, output_stride=32) encoder = builder.create_encoder( backbone_options, tf.keras.layers.experimental.SyncBatchNormalization) self.assertIsInstance(encoder, mobilenet.MobileNet) def test_resnet_encoder_creation(self): backbone_options = config_pb2.ModelOptions.BackboneOptions( name='max_deeplab_s', output_stride=32) encoder = builder.create_resnet_encoder( backbone_options, bn_layer=tf.keras.layers.experimental.SyncBatchNormalization) self.assertIsInstance(encoder, axial_resnet_instances.MaXDeepLabS) def test_decoder_creation(self): proto_filename = os.path.join( _CONFIG_PATH, 'example_kitti-step_motion_deeplab.textproto') model_options = _read_proto_file(proto_filename, config_pb2.ModelOptions()) motion_decoder = builder.create_decoder( model_options, tf.keras.layers.experimental.SyncBatchNormalization, ignore_label=255) self.assertIsInstance(motion_decoder, motion_deeplab_decoder.MotionDeepLabDecoder) if __name__ == '__main__': tf.test.main()