def __init__()

in torchaudio/models/wav2letter.py [0:0]

• 35 lines of code
• 4 McCabe index (conditional complexity)

    def __init__(self, num_classes: int = 40, input_type: str = "waveform", num_features: int = 1) -> None:
        super(Wav2Letter, self).__init__()

        acoustic_num_features = 250 if input_type == "waveform" else num_features
        acoustic_model = nn.Sequential(
            nn.Conv1d(in_channels=acoustic_num_features, out_channels=250, kernel_size=48, stride=2, padding=23),
            nn.ReLU(inplace=True),
            nn.Conv1d(in_channels=250, out_channels=250, kernel_size=7, stride=1, padding=3),
            nn.ReLU(inplace=True),
            nn.Conv1d(in_channels=250, out_channels=250, kernel_size=7, stride=1, padding=3),
            nn.ReLU(inplace=True),
            nn.Conv1d(in_channels=250, out_channels=250, kernel_size=7, stride=1, padding=3),
            nn.ReLU(inplace=True),
            nn.Conv1d(in_channels=250, out_channels=250, kernel_size=7, stride=1, padding=3),
            nn.ReLU(inplace=True),
            nn.Conv1d(in_channels=250, out_channels=250, kernel_size=7, stride=1, padding=3),
            nn.ReLU(inplace=True),
            nn.Conv1d(in_channels=250, out_channels=250, kernel_size=7, stride=1, padding=3),
            nn.ReLU(inplace=True),
            nn.Conv1d(in_channels=250, out_channels=250, kernel_size=7, stride=1, padding=3),
            nn.ReLU(inplace=True),
            nn.Conv1d(in_channels=250, out_channels=2000, kernel_size=32, stride=1, padding=16),
            nn.ReLU(inplace=True),
            nn.Conv1d(in_channels=2000, out_channels=2000, kernel_size=1, stride=1, padding=0),
            nn.ReLU(inplace=True),
            nn.Conv1d(in_channels=2000, out_channels=num_classes, kernel_size=1, stride=1, padding=0),
            nn.ReLU(inplace=True),
        )

        if input_type == "waveform":
            waveform_model = nn.Sequential(
                nn.Conv1d(in_channels=num_features, out_channels=250, kernel_size=250, stride=160, padding=45),
                nn.ReLU(inplace=True),
            )
            self.acoustic_model = nn.Sequential(waveform_model, acoustic_model)

        if input_type in ["power_spectrum", "mfcc"]:
            self.acoustic_model = acoustic_model