- class returnn.tf.layers.basic.DropoutLayer(in_dim=None, out_dim=None, extra_deps=(), **kwargs)#
Just the same as
CopyLayer, because that one already supports dropout.
in_dim (Dim|None) – just for checking. but also, if this is provided, it will set the feature_dim to this.
out_dim (Dim|None) – alternative to in_dim. see in_dim doc.
extra_deps (list[LayerBase]) – Just add as an additional dependency, without really using it. This can have an effect though on the search beam, via
SelectSearchSourcesLayer. We only have this here for the
get_out_data_from_opts()must know about it and define the right beam. Also see the option
collocate_with, which is different in that it does not add a dependency. Note that this will not be real TF control dependencies, but it simply sets the dependency on the layer. If you want to have a real TF control dependency, use
- layer_class: Optional[str] = 'dropout'#
- kwargs: Optional[Dict[str]]#
- output_loss: Optional[tf.Tensor]#
- rec_vars_outputs: Dict[str, tf.Tensor]#
- params: Dict[str, tf.Variable]#
- saveable_param_replace: Dict[tf.Variable, Union['tensorflow.python.training.saver.BaseSaverBuilder.SaveableObject', None]]#
- stats: Dict[str, tf.Tensor]#
- input_data: Optional[Data]#