code: def hf_ppl(model, tokenizer, inputs):
      print("=========huggingface=========")
      print("huggingface calculating ppl...")
      hf_ppl, hf_time = hf_gpt2(model, inputs, tokenizer, "ppl")
      print(f"huggingface time: {hf_time}s")
      print("huggingface results:")
      print(hf_ppl)
  
imports: import time
  import torch
  from torch import nn
  from transformers import GPT2Tokenizer, GPT2LMHeadModel, GPT2Config
  import lightseq.inference
  from lightseq.training.ops.pytorch.quantization import qat_mode, QuantLinear, TensorQuantizer, weight_quant_config, emb_quant_config
  from lightseq.training.ops.pytorch.torch_transformer_layers import TransformerDecoderLayer
  from export.util import parse_args
label_desc: Use image node_id 7 for calling a global function with example usage: hf_ppl(model, tokenizer, inputs) without return types