code: def load_state_dict_from_url(url, map_location=None):
      """Try to load the checkopint from the given url."""
      try:
          state_dict = torch.hub.load_state_dict_from_url(
              url, map_location=map_location
          )
          return state_dict
      except Exception:
          print("Not able to load state dict from %s" % (url))
          print("Retrying with http:// prefix")
      try:
          url = url.replace("https", "http")
          state_dict = torch.hub.load_state_dict_from_url(
              url, map_location=map_location
          )
          return state_dict
      except Exception:
          print("Not able to load state dict from %s" % (url))
  
      # in this case downloading the pre-trained model was not possible
      # notify the user and return
      return {"state_dict": None}
  
imports: import os
  import hydra
  import torch
  from hydra import utils
  from torch import nn
  from lightly.cli._cli_simclr import _SimCLR
  from lightly.embedding import SelfSupervisedEmbedding
  from lightly.models import ZOO
  from lightly.models import ResNetGenerator
  from lightly.models.batchnorm import get_norm_layer
  from lightly.utils.version_compare import version_compare
label_desc: Use image node_id 6 for calling a global function with example usage: load_state_dict_from_url(url, map_location) and returns: dict, state_dict, state_dict