class Conv1d(in_channels: int, out_channels: int, kernel_size: int, stride: int = 1, padding: int = 0, dilation: int = 1, bias: bool = True)#

Applies a 1-dimensional convolution over the multi-channel input sequence.

The channels are expected to be last i.e. the input shape should be NLC where:
  • N is the batch dimension

  • L is the sequence length

  • C is the number of input channels

  • in_channels (int) – The number of input channels

  • out_channels (int) – The number of output channels

  • kernel_size (int) – The size of the convolution filters

  • stride (int, optional) – The stride when applying the filter. Default: 1.

  • padding (int, optional) – How many positions to 0-pad the input with. Default: 0.

  • dilation (int, optional) – The dilation of the convolution.

  • bias (bool, optional) – If True add a learnable bias to the output. Default: True