text: 
  import torch
  import torch.nn as nn
  
  class Classifier(nn.Sequential):
      def __init__(self, in_channels, out_channels, hidden_channels = 1280):
          super().__init__()
          self.add_module('pointwise',nn.Conv2d(in_channels = in_channels, out_channels = hidden_channels, kernel_size = 1, stride = 1, padding = 0, bias = False))
          self.add_module('pw_bn',nn.BatchNorm2d(hidden_channels))
          self.add_module('pw_relu', nn.ReLU6(inplace = True))
          self.add_module('avg_pool', nn.AdaptiveAvgPool2d((1,1)))
          self.add_module('view', out_view())
          self.add_module('linear', nn.Linear(hidden_channels, out_channels))    
      def forward(self, input):
          return super().forward(input)
  
  
  class out_view(nn.Sequential):
      def __init__(self, dim = -1):
          super().__init__()
          self.dim = dim
      def forward(self,input):
          return input.view(input.size(0),self.dim) 
  
  