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: Forward momentum backbone.
  Args:
      x (tensor): input to be forwarded of shape N x C x T x H x W
docstr_tok: ["Forward","momentum","backbone",".","Args",":","x","(","tensor",")",":","input","to","be","forwarded","of","shape","N","x","C","x","T","x","H","x","W"]
code: def forward_backbone_mmt(self, x: torch.Tensor) -> torch.Tensor:
      """
      Forward momentum backbone.
      Args:
          x (tensor): input to be forwarded of shape N x C x T x H x W
      """
      with torch.no_grad():
          proj = self.backbone_mmt(x)
      return F.normalize(proj, dim=1)
  
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 4 for calling the BYOL obj's underlying member method code with example usage: obj.forward_backbone_mmt(x) and returns: F