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# 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.
import dataclasses
import tensorflow as tf, tf_keras
from official.modeling.hyperparams import base_config
from official.modeling.hyperparams import oneof
@dataclasses.dataclass
class ResNet(base_config.Config):
model_depth: int = 50
@dataclasses.dataclass
class Backbone(oneof.OneOfConfig):
type: str = 'resnet'
resnet: ResNet = dataclasses.field(default_factory=ResNet)
not_resnet: int = 2
@dataclasses.dataclass
class OutputLayer(oneof.OneOfConfig):
type: str = 'single'
single: int = 1
multi_head: int = 2
@dataclasses.dataclass
class Network(base_config.Config):
backbone: Backbone = dataclasses.field(default_factory=Backbone)
output_layer: OutputLayer = dataclasses.field(default_factory=OutputLayer)
class OneOfTest(tf.test.TestCase):
def test_to_dict(self):
network_params = {
'backbone': {
'type': 'resnet',
'resnet': {
'model_depth': 50
}
},
'output_layer': {
'type': 'single',
'single': 1000
}
}
network_config = Network(network_params)
self.assertEqual(network_config.as_dict(), network_params)
def test_get_oneof(self):
backbone = Backbone()
self.assertIsInstance(backbone.get(), ResNet)
self.assertEqual(backbone.get().as_dict(), {'model_depth': 50})
if __name__ == '__main__':
tf.test.main()
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