code: def __init__(self, hidden_dim=512):
      super(CPCEncoder, self).__init__()
      self.conv0 = nn.Conv1d(1, hidden_dim, 10, stride=5, padding=3)
      self.batchNorm0 = ChannelNorm(hidden_dim)
      self.conv1 = nn.Conv1d(
          hidden_dim, hidden_dim, 8, stride=4, padding=2
      )
      self.batchNorm1 = ChannelNorm(hidden_dim)
      self.conv2 = nn.Conv1d(
          hidden_dim, hidden_dim, 4, stride=2, padding=1
      )
      self.batchNorm2 = ChannelNorm(hidden_dim)
      self.conv3 = nn.Conv1d(
          hidden_dim, hidden_dim, 4, stride=2, padding=1
      )
      self.batchNorm3 = ChannelNorm(hidden_dim)
      self.conv4 = nn.Conv1d(
          hidden_dim, hidden_dim, 4, stride=2, padding=1
      )
      self.batchNorm4 = ChannelNorm(hidden_dim)
      self.DOWNSAMPLING = 160
  
imports: import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 1 to create a new CPCEncoder object from inherited base classes: nn with example: obj = CPCEncoder(hidden_dim)