def __init__()

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

• 10 lines of code
• 1 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(DeCoAR, self).__init__()

        self.embed = 80
        d = 1024
        self.encoder_layers = 4
        self.post_extract_proj = nn.Linear(self.embed, d)

        self.forward_lstm = nn.LSTM(input_size=d, hidden_size=d, num_layers=self.encoder_layers,
                            batch_first=True, bidirectional=False)
        self.backward_lstm = nn.LSTM(input_size=d, hidden_size=d, num_layers=self.encoder_layers,
                            batch_first=True, bidirectional=False)