1aa2ab0590edb3e6e876d44ea0aeffc1c8f6d838,rl_coach/architectures/tensorflow_components/embedders/embedder.py,InputEmbedder,__init__,#InputEmbedder#Any#Any#Any#Any#Any#Any#Any#Any#Any#,33

Before Change

        self.output = None
        self.scheme = scheme
        self.return_type = InputEmbedding
        self.layers = []
        self.input_rescaling = input_rescaling
        self.input_offset = input_offset
        self.input_clipping = input_clipping

After Change

class InputEmbedder(object):
    
    An input embedder is the first part of the network, which takes the input from the state and produces a vector
    embedding by passing it through a neural network. The embedder will mostly be input type dependent, and there
    can be multiple embedders in a single network
    
    def __init__(self, input_size: List[int], activation_function=tf.nn.relu,
                 scheme: EmbedderScheme=None, batchnorm: bool=False, dropout: bool=False,
                 name: str= "embedder", input_rescaling=1.0, input_offset=0.0, input_clipping=None, dense_layer=Dense):
        self.name = name

Instances