code: def compute_symmetric_kl(noised_logits, input_logits):
      """
      Computes symmetric KL loss by taking the KL for both the input logits
      and the noised logits and comparing the two
      """
      return F.kl_div(
          F.log_softmax(noised_logits, dim=-1, dtype=torch.float32),
          F.softmax(input_logits, dim=-1, dtype=torch.float32),
          None,
          None,
          "sum",
      ) + F.kl_div(
          F.log_softmax(input_logits, dim=-1, dtype=torch.float32),
          F.softmax(noised_logits, dim=-1, dtype=torch.float32),
          None,
          None,
          "sum",
      )
  
imports: from contextlib import AbstractContextManager
  from enum import Enum
  from typing import Dict
  import torch
  import torch.nn.functional
  from pytext.common.constants import Stage
  from pytext.config import ConfigBase
  from pytext.utils.precision import maybe_float
label_desc: Use image node_id 2 for calling a global function with example usage: compute_symmetric_kl(noised_logits, input_logits) and returns: unknown