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# 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()
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