class_docstr: ResNet (ResNet18, ResNet34, ResNet50, ResNet101, ResNet152)
  Models: 224 x 224
  ResNet18: 11,689,512 Params
  ResNet34: 21,797,672 Params
  ResNet50: 25,557,032 Params
  ResNet101: 44,549,160 Params
  Resnet152: 60,192,808 Params
  Reference: "Deep Residual Learning for Image Recognition" by He et al.
  https://arxiv.org/abs/1512.03385
code: def forward(self, x):
      # Is Video
      if x.dim() == 5:
          is_video = True
          batch_size = x.shape[0]
          video_frames = x.shape[2]
  
          # (B, Din, T, H, W) -> (B * T, Din, H, W)
          x = x.transpose(1, 2).flatten(start_dim=0, end_dim=1)
  
      else:
          is_video = False
  
      # (B, Din, H, W) -> (B, D0, H//4, W//4)
      x = self.stem(x)
  
      # (B, D0, H//4, W//4) -> (B, D4, H//32, W//32)
      for block in self.blocks:
          x = block(x)
  
      # (B, D4, H//32, W//32) -> (B, Dout)
      x = self.head(x)
  
      # Is Video
      if is_video:
          # (B * T, Dout) -> (B, Dout, T)
          if x.dim() == 2:
              x = x.reshape(batch_size, video_frames, -1).transpose(
                  1, 2
              )
  
          # (B * T, D4, H//32, W//32) -> (B, D4, T, H//32, W//32)
          else:
              x = x.reshape(
                  batch_size,
                  video_frames,
                  x.shape[1],
                  x.shape[2],
                  x.shape[3],
              ).transpose(1, 2)
  
      return x
  
file_path: NeMo/nemo/collections/multimodal/speech_cv/parts/submodules/resnet.py
imports: from torch import nn
  from nemo.collections.multimodal.speech_cv.parts.submodules.conv2d import Conv2d
  from nemo.collections.multimodal.speech_cv.parts.submodules.global_avg_pool2d import GlobalAvgPool2d
  from nemo.collections.multimodal.speech_cv.parts.submodules.resnet_block import ResNetBlock
  from nemo.collections.multimodal.speech_cv.parts.submodules.resnet_bottleneck_block import ResNetBottleneckBlock
label_desc: Use image node_id 2 for calling the ResNet obj's underlying member method code with example usage: obj.forward(x) and returns: x