class_docstr: Base class for experiment loggers.
docstr: Record hyperparameters.
  
  Args:
      params: :class:`~argparse.Namespace` or `Dict` containing the hyperparameters
      args: Optional positional arguments, depends on the specific logger being used
      kwargs: Optional keyword arguments, depends on the specific logger being used
docstr_tok: ["Record","hyperparameters",".","Args",":","params",":",":","class",":","`","~argparse.Namespace","`","or","`","Dict","`","containing","the","hyperparameters","args",":","Optional","positional","arguments",",","depends","on","the","specific","logger","being","used","kwargs",":","Optional","keyword","arguments",",","depends","on","the","specific","logger","being","used"]
code: def log_hyperparams(
      self,
      params: Union[Dict[str, Any], Namespace],
      *args: Any,
      **kwargs: Any,
  ) -> None:
      """Record hyperparameters.
  
      Args:
          params: :class:`~argparse.Namespace` or `Dict` containing the hyperparameters
          args: Optional positional arguments, depends on the specific logger being used
          kwargs: Optional keyword arguments, depends on the specific logger being used
  
      """
  
imports: from abc import ABC, abstractmethod
  from argparse import Namespace
  from functools import wraps
  from typing import Any, Callable, Dict, Optional, Union
  from torch import Tensor
  from torch.nn import Module
  from lightning.fabric.utilities.rank_zero import rank_zero_only
label_desc: Use image node_id 7 for calling the Logger obj's underlying member method code with example usage: obj.log_hyperparams(params) without return types