class_docstr: SlowFast networks (SlowFast) from
  `"SlowFast Networks for Video Recognition"
  <https://arxiv.org/abs/1812.03982>`_ paper.
code: def SlowPath(self, x, lateral):
      x = self.slow_conv1(x)  # bx64x4x112x112, input is bx3x4x224x224
      x = self.slow_bn1(x)
      x = self.slow_relu(x)
      pool1 = self.slow_maxpool(x)  # bx64x4x56x56
      pool1_lat = torch.cat((pool1, lateral[0]), dim=1)  # bx80x4x56x56
  
      res2 = self.slow_res2(pool1_lat)  # bx256x4x56x56
      res2_lat = torch.cat((res2, lateral[1]), dim=1)  # bx320x4x56x56
  
      res3 = self.slow_res3(res2_lat)  # bx512x4x28x28
      res3_lat = torch.cat((res3, lateral[2]), dim=1)  # bx640x4x28x28
  
      res4 = self.slow_res4(res3_lat)  # bx1024x4x14x14
      res4_lat = torch.cat((res4, lateral[3]), dim=1)  # bx1280x4x14x14
  
      res5 = self.slow_res5(res4_lat)  # bx2048x4x7x7
      out = self.avg(res5)  # bx2048x1x1x1
      out = out.view(out.shape[0], out.shape[1])  # bx2048
      return out
  
imports: import torch
  import torch.nn
  from torch.nn import BatchNorm3d
label_desc: Use image node_id 3 for calling the SlowFast obj's underlying member method code with example usage: obj.SlowPath(x, lateral) and returns: out