class_docstr: Bootstrap Your Own Latent A New Approach to Self-Supervised Learning
  Details can be found in:
  https://arxiv.org/pdf/2006.07733.pdf
docstr: Update the momentum. This function can be used to perform momentum annealing.
  Args:
      mmt (float): update the momentum.
docstr_tok: ["Update","the","momentum",".","This","function","can","be","used","to","perform","momentum","annealing",".","Args",":","mmt","(","float",")",":","update","the","momentum","."]
code: def update_mmt(self, mmt: float):
      """
      Update the momentum. This function can be used to perform momentum annealing.
      Args:
          mmt (float): update the momentum.
      """
      self.mmt = mmt
  
file_path: pytorchvideo/pytorchvideo/models/byol.py
imports: import copy
  from typing import Callable, Optional
  import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 3 for calling the BYOL obj's underlying member method code with example usage: obj.update_mmt(mmt) without return types