code: from torch import nn
  
  
  class ConvolutionalBlock(nn.Module):
  
      def __init__(self, in_channels=128, out_channels=256, kernel_size=3, padding=1, stride=1, padding_mode='zeros'):
          super().__init__()
          self.conv1 = nn.Conv1d(in_channels, out_channels, kernel_size=kernel_size, padding=padding, stride=stride,
                                 padding_mode=padding_mode)
          self.bn1 = nn.BatchNorm1d(out_channels)
          self.relu1 = nn.ReLU()
  
      def forward(self, x):
          out = self.conv1(x)
          out = self.bn1(out)
          out = self.relu1(out)
          return out
  
apis: torch.nn.Conv1d torch.nn.ReLU torch.nn.BatchNorm1d