code: def convert_bigbird_pegasus_ckpt_to_pytorch(
      ckpt_path: str, save_dir: str, config_update: dict
  ):
      tf_weights = get_tf_weights_as_numpy(ckpt_path)
      torch_model = convert_bigbird_pegasus(tf_weights, config_update)
      torch_model.save_pretrained(save_dir)
  
file_path: transformers/src/transformers/models/bigbird_pegasus/convert_bigbird_pegasus_tf_to_pytorch.py
imports: import argparse
  from typing import Dict
  import tensorflow
  import torch
  from tqdm import tqdm
  from transformers import BigBirdPegasusConfig, BigBirdPegasusForConditionalGeneration
label_desc: Use image node_id 4 for calling a global function with example usage: convert_bigbird_pegasus_ckpt_to_pytorch(ckpt_path, save_dir, config_update) without return types