Add ResNet-RS to keras.applications - code refactor 6
@@ -156,8 +156,7 @@ BASE_DOCSTRING = """Instantiates the {name} architecture.
se_ratio: Squeeze and Excitation layer ratio.
dropout_rate: dropout rate before final classifier layer.
drop_connect_rate: dropout rate at skip connections.
- include_top: whether to include the fully-connected layer at the top of
- the network.
+ include_top: whether to include the fully-connected layer at the top of the network.
block_args: list of dicts, parameters to construct block modules.
model_name: name of the model.
pooling: optional pooling mode for feature extraction when `include_top`
@@ -533,8 +532,7 @@ def ResNetRS(
se_ratio: Squeeze and Excitation layer ratio.
dropout_rate: dropout rate before final classifier layer.
drop_connect_rate: dropout rate at skip connections.
- include_top: whether to include the fully-connected layer at the top of
- the network.
+ include_top: whether to include the fully-connected layer at the top of the network.
block_args: list of dicts, parameters to construct block modules.
model_name: name of the model.
pooling: optional pooling mode for feature extraction when `include_top`
