class_docstr: SlowFast networks (SlowFast) from
  `"SlowFast Networks for Video Recognition"
  <https://arxiv.org/abs/1812.03982>`_ paper.
code: def FastPath(self, x):
      lateral = []
      x = self.fast_conv1(x)  # bx8x32x112x112, input is bx3x32x224x224
      x = self.fast_bn1(x)
      x = self.fast_relu(x)
      pool1 = self.fast_maxpool(x)  # bx8x32x56x56
      lateral_p = self.lateral_p1(pool1)  # bx16x4x56x56
      lateral.append(lateral_p)
  
      res2 = self.fast_res2(pool1)  # bx32x32x56x56
      lateral_res2 = self.lateral_res2(res2)  # bx64x4x56x56
      lateral.append(lateral_res2)
  
      res3 = self.fast_res3(res2)  # bx64x32x28x28
      lateral_res3 = self.lateral_res3(res3)  # bx128x4x28x28
      lateral.append(lateral_res3)
  
      res4 = self.fast_res4(res3)  # bx128x32x14x14
      lateral_res4 = self.lateral_res4(res4)  # bx256x4x14x14
      lateral.append(lateral_res4)
  
      res5 = self.fast_res5(res4)  # bx256x32x7x7
      out = self.avg(res5)  # bx256x1x1x1
      out = out.view(out.shape[0], out.shape[1])  # bx256
      return out, lateral
  
imports: import torch
  import torch.nn
  from torch.nn import BatchNorm3d
label_desc: Use image node_id 4 for calling the SlowFast obj's underlying member method code with example usage: obj.FastPath(x) and returns: out,  lateral