docstr: Used for forward pass through loss computations.
  
  :param F: backend api, either `mxnet.nd` or `mxnet.sym` (if block has been hybridized).
  :param pred: state values predicted by VHead network, of shape (batch_size).
  :param target: actual state values, of shape (batch_size).
  :return: loss, of shape (batch_size).
docstr_tok: ["Used","for","forward","pass","through","loss","computations",".",":","param","F",":","backend","api",",","either","`","mxnet.nd","`","or","`","mxnet.sym","`","(","if","block","has","been","hybridized",")",".",":","param","pred",":","state","values","predicted","by","VHead","network",",","of","shape","(","batch_size",")",".",":","param","target",":","actual","state","values",",","of","shape","(","batch_size",")",".",":","return",":","loss",",","of","shape","(","batch_size",")","."]
code: def loss_forward(
      self, F: ModuleType, pred: nd_sym_type, target: nd_sym_type
  ) -> List[Tuple[nd_sym_type, str]]:
      """
      Used for forward pass through loss computations.
  
      :param F: backend api, either `mxnet.nd` or `mxnet.sym` (if block has been hybridized).
      :param pred: state values predicted by VHead network, of shape (batch_size).
      :param target: actual state values, of shape (batch_size).
      :return: loss, of shape (batch_size).
      """
      loss = self.loss_fn(pred, target).mean()
      return [(loss, LOSS_OUT_TYPE_LOSS)]
  
file_path: coach/rl_coach/architectures/mxnet_components/heads/v_head.py
imports: from typing import Union, List, Tuple
  from types import ModuleType
  import mxnet
  from mxnet.gluon.loss import Loss, HuberLoss, L2Loss
  from mxnet.gluon import nn
  from rl_coach.architectures.mxnet_components.heads.head import Head, HeadLoss, LossInputSchema, NormalizedRSSInitializer
  from rl_coach.architectures.mxnet_components.heads.head import LOSS_OUT_TYPE_LOSS
  from rl_coach.base_parameters import AgentParameters
  from rl_coach.core_types import VStateValue
  from rl_coach.spaces import SpacesDefinition
label_desc: Use image node_id 3 for calling the VHeadLoss obj's underlying member method code with example usage: obj.loss_forward(F, pred, target) and returns: list