code: def conv1d(ni:int, no:int, ks:int=1, stride:int=1, padding:int=0, bias:bool=False):
      "Create and initialize a `nn.Conv1d` layer with spectral normalization."
      conv = nn.Conv1d(ni, no, ks, stride=stride, padding=padding, bias=bias)
      nn.init.kaiming_normal_(conv.weight)
      if bias: conv.bias.data.zero_()
      return spectral_norm(convf conv1d(ni:int, no:int, ks:int=1, stride:int=1, padding:int=0, bias:bool=False):
      "Create and initialize a `nn.Conv1d` layer with spectral normalization."
      conv = nn.Conv1d(ni, no, ks, stride=stride, padding=padding, bias=bias)
      nn.init.kaiming_normal_(conv.weight)
      if bias: conv.bias.data.zero_()
      return spectral_norm(conv)
docs: Create and initialize a `nn.Conv1d` layer with spectral normalization.