class_docstr: ABC for loss functions of each head. Child class must implement input_schema() and loss_forward()
class_docstr_tok: ["ABC","for","loss","functions","of","each","head",".","Child","class","must","implement","input_schema","(",")","and","loss_forward","(",")"]
docstr: :return: schema for output of hybrid_forward. Must contain 'loss' and 'regularization' keys at least once.
      The order and total number must match that of returned values from the loss. 'loss' and 'regularization'
      are special keys. Any other string is treated as auxiliary outputs and must include match auxiliary
      fetch names returned by the head.
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code: def output_schema(self) -> List[str]:
      """
      :return: schema for output of hybrid_forward. Must contain 'loss' and 'regularization' keys at least once.
          The order and total number must match that of returned values from the loss. 'loss' and 'regularization'
          are special keys. Any other string is treated as auxiliary outputs and must include match auxiliary
          fetch names returned by the head.
      """
      return self._output_schema
  
imports: from typing import Dict, List, Union, Tuple
  import mxnet
  from mxnet.initializer import Initializer, register
  from mxnet.gluon import nn, loss
  from mxnet.ndarray import NDArray
  from mxnet.symbol import Symbol
  from rl_coach.base_parameters import AgentParameters
  from rl_coach.spaces import SpacesDefinition
label_desc: Use image node_id 3 for calling the HeadLoss obj's underlying member method code with example usage: obj.output_schema() and returns: self