class_docstr: Applies the provided loss to the list of outputs (or single output) and sums
  up the losses.
docstr: Instantiates a MultiOutputSumLoss from a configuration.
  
  Args:
      config: A configuration for a MultiOutpuSumLoss.
          See :func:`__init__` for parameters expected in the config.
  
  Returns:
      A MultiOutputSumLoss instance.
docstr_tok: ["Instantiates","a","MultiOutputSumLoss","from","a","configuration",".","Args",":","config",":","A","configuration","for","a","MultiOutpuSumLoss",".","See",":","func",":","`","__init__","`","for","parameters","expected","in","the","config",".","Returns",":","A","MultiOutputSumLoss","instance","."]
code: def from_config(cls, config: Dict[str, Any]) -> "MultiOutputSumLoss":
      """Instantiates a MultiOutputSumLoss from a configuration.
  
      Args:
          config: A configuration for a MultiOutpuSumLoss.
              See :func:`__init__` for parameters expected in the config.
  
      Returns:
          A MultiOutputSumLoss instance.
      """
      assert (
          type(config["loss"]) == dict
      ), "loss must be a dict containing a configuration for a registered loss"
      return cls(loss=build_loss(config["loss"]))
  
file_path: ClassyVision/classy_vision/losses/multi_output_sum_loss.py
imports: from typing import Any, Dict
  import torch
  from .None import build_loss, ClassyLoss, register_loss
label_desc: Use image node_id 2 for calling the MultiOutputSumLoss obj's underlying member method code with example usage: obj.from_config(cls, config) and returns: cls