class_docstr: ### Cross entropy loss
class_docstr_tok: ["#","#","#","Cross","entropy","loss"]
code: def forward(self, outputs, targets):
      return self.loss(
          outputs.view(-1, outputs.shape[-1]), targets.view(-1)
      )
  
imports: from typing import Callable
  import torch
  import torch.nn
  from torch.utils.data import DataLoader, RandomSampler
  from labml import lab, monit, logger, tracker
  from labml.configs import option
  from labml.logger import Text
  from labml_helpers.datasets.text import TextDataset, SequentialDataLoader, SequentialUnBatchedDataset, TextFileDataset
  from labml_helpers.device import DeviceConfigs
  from labml_helpers.metrics.accuracy import Accuracy
  from labml_helpers.module import Module
  from labml_helpers.train_valid import TrainValidConfigs, hook_model_outputs, BatchIndex
  from labml_nn.optimizers.configs import OptimizerConfigs
label_desc: Use image node_id 2 for calling the CrossEntropyLoss obj's underlying member method code with example usage: obj.forward(outputs, targets) and returns: self