class_docstr: Momentum Contrast for unsupervised Visual Representation Learning
  Details can be found in:
  https://arxiv.org/abs/1911.05722
class_docstr_tok: ["Momentum","Contrast","for","unsupervised","Visual","Representation","Learning","Details","can","be","found","in",":","https",":","\/\/arxiv.org\/abs\/1911.05722"]
code: def _copy_weights_to_backbone_mmt(self) -> None:
      dist = {}
      for name, p in self.backbone.named_parameters():
          dist[name] = p
      for name, p in self.backbone_mmt.named_parameters():
          p.data.copy_(dist[name].data)
  
imports: import math
  from dataclasses import dataclass
  from typing import Any, Callable, List, Optional, Tuple, Union
  import pytorchvideo_trainer.module.distributed_utils
  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 2 for calling the MOCO obj's underlying member method code with example usage: obj._copy_weights_to_backbone_mmt() without return types