code: def _reorder_cache(past_key_values, beam_idx):
      reordered_past = ()
      for layer_past in past_key_values:
          reordered_past += (
              tuple(
                  past_state.index_select(0, beam_idx)
                  for past_state in layer_past
              ),
          )
      return reordered_past
  
imports: import random
  from typing import List, Optional, Tuple, Union
  import torch
  import torch.utils.checkpoint
  from torch import nn
  from transformers.activations import ACT2FN
  from transformers.modeling_outputs import BaseModelOutputWithPast, CausalLMOutputWithPast
  from transformers.modeling_utils import PreTrainedModel
  from transformers import OPTConfig
  from text_generation_server.utils.layers import FastLinear, TensorParallelColumnLinear, TensorParallelEmbedding, TensorParallelRowLinear, TensorParallelHead
label_desc: Use image node_id 4 for calling the OPTForCausalLM obj's underlying member method code with example usage: obj._reorder_cache(past_key_values, beam_idx) and returns: reordered_past