class_docstr: Merge tokens from a [batch_size, sequence_length, num_channels] tensor
  using a linear projection.
  
  This function also updates masks and adds padding as needed to make the
  sequence length divisible by the window size before merging tokens.
  
  Args:
      dim: Number of input channels.
      window: The size of the window to merge into a single token.
code: def extra_repr(self) -> str:
      return f"dim={self.dim}, window={self.window}"
  
file_path: ml-cvnets/cvnets/layers/token_merging.py
imports: from typing import Tuple
  import torch
  from torch import nn
  from torch.nn import functional
  from cvnets.layers import linear_layer
  from cvnets.layers.normalization import layer_norm
label_desc: Use image node_id 3 for calling the TokenMerging obj's underlying member method code with example usage: obj.extra_repr() and returns: str, self, str, self