code: def get_loss(self, guesses: Floats2d, truths: Floats2d) -> float:
      if guesses.shape != truths.shape:  # pragma: no cover
          err = f"Cannot calculate L2 distance: mismatched shapes: {guesses.shape} vs {truths.shape}."
          raise ValueError(err)
      d_truth = self.get_grad(guesses, truths)
      # 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 4 for calling the L2Distance obj's underlying member method code with example usage: obj.get_loss(guesses, truths) and returns: unknown