code: def gpt_neox_config_to_gpt2_config(
      gpt_neox_config: GPTNeoXConfig,
  ) -> GPT2Config:
      assert gpt_neox_config.rotary_emb_base == 10000
      return GPT2Config(
          vocab_size=gpt_neox_config.vocab_size,
          n_positions=0,  # No absolute position embedding
          n_embd=gpt_neox_config.hidden_size,
          n_layer=gpt_neox_config.num_hidden_layers,
          n_head=gpt_neox_config.num_attention_heads,
          n_inner=gpt_neox_config.intermediate_size,
          activation_function=gpt_neox_config.hidden_act,
          resid_pdrop=0.0,  # No dropout
          embd_pdrop=0.0,
          attn_pdrop=0.0,
          layer_norm_epsilon=gpt_neox_config.layer_norm_eps,
          initializer_range=gpt_neox_config.initializer_range,
          bos_token_id=gpt_neox_config.bos_token_id,
          eos_token_id=gpt_neox_config.eos_token_id,
          # These are new arguments not in the original GPT2Config
          prenorm=True,
          parallel_block=gpt_neox_config.use_parallel_residual,
          parallel_block_tied_norm=False,
          rotary_emb_fraction=gpt_neox_config.rotary_pct,
          tie_word_embeddings=gpt_neox_config.tie_word_embeddings,
      )
  
file_path: flash-attention/flash_attn/models/gpt_neox.py
imports: import math
  import re
  from collections import OrderedDict
  import torch
  import torch.nn.functional
  from einops import rearrange
  from transformers import GPT2Config, GPTNeoXConfig
label_desc: Use image node_id 2 for calling a global function with example usage: gpt_neox_config_to_gpt2_config(gpt_neox_config) and returns: GPT2Config