code: def _get_loss_from_grad(self, d_truth: Floats2d) -> float:
      # TODO: Add overload for axis=None case to sum
      return (d_truth**2).sum()
  
imports: from abc import abstractmethod
  from typing import Any, Dict, Generic, List, Optional, Sequence, Tuple, TypeVar, Union, cast
  from .config import registry
  from .types import Floats2d, Ints1d
  from .util import get_array_module, to_categorical
label_desc: Use image node_id 6 for calling the CategoricalCrossentropy obj's underlying member method code with example usage: obj._get_loss_from_grad(d_truth) and returns: unknown