code: def _forward_fn(
      self, input: torch.Tensor, target: torch.Tensor
  ) -> Tuple[torch.Tensor, torch.Tensor]:
      with torch.no_grad(), autocast(enabled=self.amp):
          output = self.model(input)
          loss = (
              None if self.loss is None else self.loss(output, target)
          )
  
      return output if loss is None else loss, output
  
imports: import time
  from copy import deepcopy
  from functools import wraps
  from typing import Callable, Dict, Optional, Tuple
  import torch
  import torch.nn
  from torch.cuda.amp import autocast
  from torch.nn.parallel import DistributedDataParallel
  from .None import logger
  from .None import utils
  from .logger import TrainingMetrics, ValidationMetrics
  from .models.common import EMA
label_desc: Use image node_id 4 for calling the Executor obj's underlying member method code with example usage: obj._forward_fn(input, target) and returns: unknown,  output