class_docstr: Construct Inception module. Concatenation after four branches (1x1x1 conv; 1x1x1 + 3x3x3 convs; 1x1x1 + 3x3x3
  convs; 3x3x3 max-pool + 1x1x1 conv). In `forward`, we check if SELayers are used, which are
  channel-wise (SELayerC), temporal-wise (SELayerT), channel-temporal-wise (SELayerTC & SELayerCT).
class_docstr_tok: ["Construct","Inception","module",".","Concatenation","after","four","branches","(","1x1x1","conv",";","1x1x1","+","3x3x3","convs",";","1x1x1","+","3x3x3","convs",";","3x3x3","max-pool","+","1x1x1","conv",")",".","In","`","forward","`",",","we","check","if","SELayers","are","used",",","which","are","channel-wise","(","SELayerC",")",",","temporal-wise","(","SELayerT",")",",","channel-temporal-wise","(","SELayerTC","&","SELayerCT",")","."]
code: def _forward(self, x):
      b0 = self.b0(x)
      b1 = self.b1b(self.b1a(x))
      b2 = self.b2b(self.b2a(x))
      b3 = self.b3b(self.b3a(x))
  
      output = [b0, b1, b2, b3]
      return output
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from torch.hub import load_state_dict_from_url
label_desc: Use image node_id 2 for calling the InceptionModule obj's underlying member method code with example usage: obj._forward(x) and returns: output