class_docstr: Contains the environment for the current dataloader within the current training process.
  
  Args:
      world_size: The number of dataloader workers for the current training process
      rank: The rank of the current worker within the number of workers
class_docstr_tok: ["Contains","the","environment","for","the","current","dataloader","within","the","current","training","process",".","Args",":","world_size",":","The","number","of","dataloader","workers","for","the","current","training","process","rank",":","The","rank","of","the","current","worker","within","the","number","of","workers"]
code: def __repr__(self) -> str:
      return f"{self.__class__.__name__}(world_size: {self.world_size}, rank: {self.rank})"
  
file_path: pytorch-lightning/src/lightning/data/utilities/env.py
imports: from typing import Callable, Optional
  import torch
  from torch.utils.data import get_worker_info
label_desc: Use image node_id 3 for calling the _WorkerEnv obj's underlying member method code with example usage: obj.__repr__() and returns: self, str, self, str, self, str