code: def forward(self, logits, labels):
      shift_logits = logits[..., :-1, :].contiguous()
      shift_labels = labels[..., 1:].contiguous()
      # Flatten the tokens
      return self.loss_fn(
          shift_logits.view(-1, shift_logits.size(-1)),
          shift_labels.view(-1),
      )
  
imports: from typing import Optional, Tuple, Union
  import torch
  import torch.nn
  from transformers.activations import ACT2FN
  from transformers.models.gpt2.modeling_gpt2 import BaseModelOutputWithPastAndCrossAttentions, GPT2PreTrainedModel
  from transformers.pytorch_utils import Conv1D
label_desc: Use image node_id 2 for calling the GPTLMLoss obj's underlying member method code with example usage: obj.forward(logits, labels) and returns: self