code: def _get_interleave(n):
      def _get_interleave_power_of_2(n):
          start = 2 ** (-(2 ** -(math.log2(n) - 3)))
          ratio = start
          return [start * ratio**i for i in range(n)]
  
      if math.log2(n).is_integer():
          return _get_interleave_power_of_2(n)
      else:
          closest_power_of_2 = 2 ** math.floor(math.log2(n))
          return (
              _get_interleave_power_of_2(closest_power_of_2)
              + _get_interleave(2 * closest_power_of_2)[0::2][
                  : n - closest_power_of_2
              ]
          )
  
file_path: BigDL/python/llm/src/bigdl/llm/transformers/models/baichuan2.py
imports: import math
  from typing import Optional, Tuple
  import torch
  import torch.utils.checkpoint
  from torch.nn import functional
  from bigdl.llm.ggml.quantize import ggml_tensor_qtype
  from bigdl.llm.transformers.models.utils import init_kv_cache, extend_kv_cache, append_kv_cache
  from bigdl.llm.transformers.models.utils import apply_rotary_pos_emb
  from bigdl.llm.transformers.models.utils import apply_rotary_pos_emb_no_cache_xpu
  from bigdl.llm.transformers.models.utils import mlp_fusion_check
  from transformers.utils import logging
label_desc: Use image node_id 5 for calling a global function with example usage: _get_interleave(n) and returns: unknown, _get_interleave_power_of_2, unknown