class_docstr: This implements the `Barron loss <https://arxiv.org/pdf/1701.03077.pdf>`_.
docstr: Instantiates a BarronLoss from a configuration.
  
  Args:
      config: A configuration for a BarronLoss.
          See :func:`__init__` for parameters expected in the config.
  
  Returns:
      A BarronLoss instance.
docstr_tok: ["Instantiates","a","BarronLoss","from","a","configuration",".","Args",":","config",":","A","configuration","for","a","BarronLoss",".","See",":","func",":","`","__init__","`","for","parameters","expected","in","the","config",".","Returns",":","A","BarronLoss","instance","."]
code: def from_config(cls, config: Dict[str, Any]) -> "BarronLoss":
      """Instantiates a BarronLoss from a configuration.
  
      Args:
          config: A configuration for a BarronLoss.
              See :func:`__init__` for parameters expected in the config.
  
      Returns:
          A BarronLoss instance.
      """
      # Infinity is a valid alpha value but is frequently a string
      config["alpha"] = float(config["alpha"])
      # assertions:
      assert type(config["size_average"]) == bool
      assert type(config["alpha"]) == float
      assert type(config["c"]) == float and config["c"] > 0.0
  
      return cls(
          alpha=config["alpha"],
          size_average=config["size_average"],
          c=config["c"],
      )
  
file_path: ClassyVision/classy_vision/losses/barron_loss.py
imports: from typing import Any, Dict
  import torch
  from .None import ClassyLoss, register_loss
label_desc: Use image node_id 2 for calling the BarronLoss obj's underlying member method code with example usage: obj.from_config(cls, config) and returns: cls