class_docstr: 1D dilated causal convolution.
class_docstr_tok: ["1D","dilated","causal","convolution","."]
code: def __init__(
      self,
      in_channels,
      out_channels,
      kernel_size,
      dilation=1,
      bias=True,
  ):
      super(CausalConv1d, self).__init__()
      self.in_channels = in_channels
      self.out_channels = out_channels
      self.kernel_size = kernel_size
      self.dilation = dilation
      self.padding = padding = (kernel_size - 1) * dilation
      self.conv = nn.Conv1d(
          in_channels,
          out_channels,
          kernel_size,
          padding=padding,
          dilation=dilation,
          bias=bias,
      )
  
imports: import logging
  import sys
  import time
  import numpy
  import torch
  import torch.nn.functional
  from torch import nn
label_desc: Use image node_id 1 to create a new CausalConv1d object from inherited base classes: nn with example: obj = CausalConv1d(in_channels, out_channels, kernel_size, dilation, bias)