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.to(past_state.device)
                  )
                  for past_state in layer_past
              ),
          )
      return reordered_past
  
imports: import math
  from typing import List, Optional, Tuple, Union
  import torch
  import torch.nn.functional
  import torch.utils.checkpoint
  from torch import nn
  from transformers.modeling_outputs import BaseModelOutputWithPast, CausalLMOutputWithPast
  from transformers.modeling_utils import PreTrainedModel
  from transformers.models.llama.modeling_llama import LlamaConfig, LlamaRMSNorm
  from transformers.utils import add_start_docstrings, add_start_docstrings_to_model_forward, logging, replace_return_docstrings
  from colossalai.kernel.cuda_native.mha.flash_attn_2 import HAS_FLASH_ATTN
  from colossalai.kernel.triton.llama_act_combine_kernel import HAS_TRITON
  from colossalai.moe.layers import SparseMLP
  from colossalai.moe.manager import MOE_MANAGER
  from colossalai.moe.utils import get_activation, set_moe_args
label_desc: Use image node_id 10 for calling the OpenMoeForCausalLM obj's underlying member method code with example usage: obj._reorder_cache(past_key_values, beam_idx) and returns: reordered_past