@parameterized.parameters(('resnet', (224, 224), 5e-05), ('resnet', (224, 224), None), ('resnet', (None, None), 5e-05), ('resnet', (None, None), None))
def test_builder(self, backbone_type, input_size, weight_decay):
    num_classes = 2
    input_specs = tf.keras.layers.InputSpec(shape=[None, input_size[0], input_size[1], 3])
    model_config = classification_cfg.ImageClassificationModel(num_classes=num_classes, backbone=backbones.Backbone(type=backbone_type))
    l2_regularizer = (tf.keras.regularizers.l2(weight_decay) if weight_decay else None)
    _ = factory.build_classification_model(input_specs=input_specs, model_config=model_config, l2_regularizer=l2_regularizer)
@parameterized.parameters(('resnet', (224, 224), 5e-05), ('resnet', (224, 224), None), ('resnet', (None, None), 5e-05), ('resnet', (None, None), None))
def test_builder(self, backbone_type, input_size, weight_decay):
    num_classes = 2
    input_specs = tf.keras.layers.InputSpec(shape=[None, input_size[0], input_size[1], 3])
    model_config = classification_cfg.ImageClassificationModel(num_classes=num_classes, backbone=backbones.Backbone(type=backbone_type))
    l2_regularizer = (tf.keras.regularizers.l2(weight_decay) if weight_decay else None)
    _ = factory.build_classification_model(input_specs=input_specs, model_config=model_config, l2_regularizer=l2_regularizer)