def __init__()

in src/speech_reps/models/decoar2.py [0:0]

• 8 lines of code
• 2 McCabe index (conditional complexity)

    def __init__(self):
        """
            input_size: an int indicating the input feature size, e.g., 80 for Mel.
            hidden_size: an int indicating the RNN hidden size.
            num_layers: an int indicating the number of RNN layers.
            dropout: a float indicating the RNN dropout rate.
            residual: a bool indicating whether to apply residual connections.
        """
        super(DeCoAR2, self).__init__()
        config = Config()
        for arg_name, arg_val in args.items():
            setattr(config, arg_name, arg_val)

        self.post_extract_proj = nn.Linear(config.input_feat, config.encoder_embed_dim)
        self.dropout_input = nn.Dropout(config.dropout_input)
        self.encoder = TransformerEncoder(config)