code: def __init__(self, channels, kernel_size=3):
      super(FinalBlazeBlock, self).__init__()
      # TFLite uses slightly different padding than PyTorch
      # on the depthwise conv layer when the stride is 2.
      self.convs = nn.Sequential(
          nn.Conv2d(
              in_channels=channels,
              out_channels=channels,
              kernel_size=kernel_size,
              stride=2,
              padding=0,
              groups=channels,
              bias=True,
          ),
          nn.Conv2d(
              in_channels=channels,
              out_channels=channels,
              kernel_size=1,
              stride=1,
              padding=0,
              bias=True,
          ),
      )
  
      self.act = nn.ReLU(inplace=True)
  
imports: import numpy
  import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 1 to create a new FinalBlazeBlock object from inherited base classes: nn with example: obj = FinalBlazeBlock(channels, kernel_size)