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
class_docstr_tok: ["Bootstrap","Your","Own","Latent","A","New","Approach","to","Self-Supervised","Learning","Details","can","be","found","in",":","https",":","\/\/arxiv.org\/pdf\/2006.07733.pdf"]
docstr: Momentum update on the backbone.
docstr_tok: ["Momentum","update","on","the","backbone","."]
code: def momentum_update_backbone(self) -> None:
      """
      Momentum update on the backbone.
      """
      m = self.mmt
      dist = {}
      for name, p in self.backbone.named_parameters():
          dist[name] = p
      for name, p in self.backbone_mmt.named_parameters():
          # pyre-ignore[41]
          p.data = dist[name].data * (1.0 - m) + p.data * m
  
imports: from dataclasses import dataclass
  from typing import Any, Callable, List, Optional, Tuple, Union
  import torch
  import torch.nn
  import torch.nn.functional
  from hydra.core.config_store import ConfigStore
  from omegaconf import MISSING
  from pytorchvideo.models.resnet import create_resnet
  from pytorchvideo.models.weight_init import init_net_weights
  from pytorchvideo_trainer.module.ssl_helper import create_mlp_util, SSLBaseModule
  from pytorchvideo_trainer.module.video_classification import Batch, BatchKey, EnsembleMethod
  from torchrecipes.core.conf import ModuleConf
  from torchrecipes.utils.config_utils import get_class_name_str
label_desc: Use image node_id 3 for calling the BYOL obj's underlying member method code with example usage: obj.momentum_update_backbone() without return types