class_docstr: Regular domain classifier network for video input.
  
  Args:
      input_size (int, optional): the dimension of the final feature vector. Defaults to 512.
      n_channel (int, optional): the number of channel for Linear and BN layers.
class_docstr_tok: ["Regular","domain","classifier","network","for","video","input",".","Args",":","input_size","(","int",",","optional",")",":","the","dimension","of","the","final","feature","vector",".","Defaults","to","512.","n_channel","(","int",",","optional",")",":","the","number","of","channel","for","Linear","and","BN","layers","."]
code: def forward(self, input):
      x = self.relu1(self.bn1(self.fc1(input)))
      x = self.fc2(x)
      return x
  
imports: import torch
  import torch.nn
  from kale.embed.video_i3d import Unit3D
label_desc: Use image node_id 2 for calling the DomainNetVideo obj's underlying member method code with example usage: obj.forward(input) and returns: x