code: def infer(self, img):
      img = self.norm(img)
      logits = self.encoder(img).permute(
          (0, 2, 3, 1) if len(img.shape) == 4 else (0, 2, 1)
      )
      sampled, codes, commitment_loss = self.codebook(logits)
      return self.decode(codes)
  
imports: import functools
  from math import sqrt
  import torch
  import torch.distributed
  import torch.nn
  import torch.nn.functional
  import torchaudio
  from einops import rearrange
label_desc: Use image node_id 6 for calling the DiscreteVAE obj's underlying member method code with example usage: obj.infer(img) and returns: self