code: def assert_param_count(model_1, model_2):
      count_1 = sum(
          p[1].numel()
          for p in model_1.named_parameters()
          if "final_proj" not in p[0]
      )
      count_2 = sum(
          p[1].numel()
          for p in model_2.named_parameters()
          if "final_proj" not in p[0]
      )
      assert (
          count_1 == count_2
      ), f"{model_1.__class__}: {count_1} != {model_2.__class__}: {count_2}"
  
file_path: transformers/src/transformers/models/seamless_m4t/convert_fairseq2_to_hf.py
imports: import argparse
  import os
  from pathlib import Path
  import torch
  from accelerate.utils.modeling import find_tied_parameters
  from seamless_communication.models.inference.translator import Translator
  from transformers import SeamlessM4TConfig, SeamlessM4TFeatureExtractor, SeamlessM4TModel, SeamlessM4TProcessor, SeamlessM4TTokenizer
  from transformers.utils import logging
label_desc: Use image node_id 1 for calling a global function with example usage: assert_param_count(model_1, model_2) without return types