docstr: Used for forward pass through head network.
  
  :param F: backend api, either `mxnet.nd` or `mxnet.sym` (if block has been hybridized).
  :param x: middleware state representation, of shape (batch_size, in_channels).
  :return: final output of network, that will be used in loss calculations.
docstr_tok: ["Used","for","forward","pass","through","head","network",".",":","param","F",":","backend","api",",","either","`","mxnet.nd","`","or","`","mxnet.sym","`","(","if","block","has","been","hybridized",")",".",":","param","x",":","middleware","state","representation",",","of","shape","(","batch_size",",","in_channels",")",".",":","return",":","final","output","of","network",",","that","will","be","used","in","loss","calculations","."]
code: def hybrid_forward(self, F, x, *args, **kwargs):
      """
      Used for forward pass through head network.
  
      :param F: backend api, either `mxnet.nd` or `mxnet.sym` (if block has been hybridized).
      :param x: middleware state representation, of shape (batch_size, in_channels).
      :return: final output of network, that will be used in loss calculations.
      """
      raise NotImplementedError()
  
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 5 for calling the Head obj's underlying member method code with example usage: obj.hybrid_forward(F, x) without return types