class_docstr: https://arxiv.org/pdf/2003.13549.pdf
class_docstr_tok: ["https",":","\/\/arxiv.org\/pdf\/2003.13549.pdf"]
code: def __init__(
      self,
      channels_in: int,
      channels_out: int,
      kernel_size: int,
      padding: int,
  ):
      super().__init__()
      self.pointwise = nn.Conv1d(
          channels_in, channels_out, kernel_size=1
      )
      self.depthwise = nn.Conv1d(
          channels_out,
          channels_out,
          kernel_size=kernel_size,
          padding=padding,
          groups=channels_out,
      )
  
imports: from typing import Tuple
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.nn.utils import parametrize
  from TTS.tts.layers.delightful_tts.kernel_predictor import KernelPredictor
label_desc: Use image node_id 1 to create a new BSConv1d object from inherited base classes: nn with example: obj = BSConv1d(channels_in, channels_out, kernel_size, padding)