class_docstr: Args:
class_docstr_tok: ["Args",":"]
code: def forward(self, x):
      x = self.block(x)
  
      nt, c, h, w = x.size()
      x = x.view(
          nt // self.n_segment, self.n_segment, c, h, w
      ).transpose(
          1, 2
      )  # n, c, t, h, w
      x = self.nl(x)
      x = x.transpose(1, 2).contiguous().view(nt, c, h, w)
      return x
  
imports: import torch
  from torch import nn
  from torch.nn import functional
  import torchvision
label_desc: Use image node_id 2 for calling the NL3DWrapper obj's underlying member method code with example usage: obj.forward(x) and returns: x