Method __init__

stream/modules/convolution.py:17–38

(self,
                in_channels: int,
                out_channels: int,
                kernel_size: int,
                stride: int=1,
                padding: int=0,
                dilation: int=1,
                groups: int=1,
                bias: bool=True,
                *args, **kargs)

class StreamConv1d(nn.Module):
    def __init__(self,
                in_channels: int,
                out_channels: int,
                kernel_size: int,
                stride: int=1,
                padding: int=0,
                dilation: int=1,
                groups: int=1,
                bias: bool=True,
                *args, **kargs):
        super(StreamConv1d, self).__init__(*args, *kargs)
        
        assert padding == 0, "To meet the demands of causal streaming requirements"
        
        self.Conv1d = nn.Conv1d(in_channels = in_channels,
                                out_channels = out_channels,
                                kernel_size = kernel_size,
                                stride = stride,
                                padding = padding,
                                dilation = dilation,
                                groups = groups,
                                bias = bias)
    
    def forward(self, x, cache):
        """