code: def verify_datatype(model):
      dtypes = {}
      for _, p in model.named_parameters():
          dtype = p.dtype
          if dtype not in dtypes:
              dtypes[dtype] = 0
          dtypes[dtype] += p.numel()
      total = 0
      for k, v in dtypes.items():
          total += v
      for k, v in dtypes.items():
          print(k, v, v / total)
  
file_path: DeepKE/example/llm/InstructKGC/src/finetune.py
imports: import os
  import sys
  import logging
  import argparse
  from datasets import Dataset
  import torch
  from transformers import HfArgumentParser, DataCollatorForSeq2Seq, GenerationConfig, BitsAndBytesConfig
  from peft import LoraConfig, get_peft_model, prepare_model_for_kbit_training, set_peft_model_state_dict
  from peft.tuners.lora import LoraLayer
  from utils.general_utils import LORA_TARGET_MODULES_DICT, seed_torch, get_model_tokenizer, get_model_name, get_format_time
  from utils.prompter import Prompter
  from utils.args import DataArguments, ModelArguments, TrainingArguments, GenerationArguments
  from datamodule import COLL_FN_DICT, DataCollatorForCPMBEE
label_desc: Use image node_id 3 for calling a global function with example usage: verify_datatype(model) without return types