code: def transfer_and_check_weights(original_module, our_module):
      status = our_module.load_state_dict(original_module.state_dict())
      if status.missing_keys:
          raise ValueError(f"Missing keys: {status.missing_keys}")
      if status.unexpected_keys:
          raise ValueError(f"Unexpected keys: {status.unexpected_keys}")
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/src/transformers/models/esm/convert_esm.py
imports: import argparse
  import pathlib
  from pathlib import Path
  from tempfile import TemporaryDirectory
  import torch
  import esm
  from esm.esmfold.v1.pretrained import esmfold_v1
  from transformers.models.esm.configuration_esm import EsmConfig, EsmFoldConfig
  from transformers.models.esm.modeling_esm import EsmForMaskedLM, EsmForSequenceClassification, EsmIntermediate, EsmLayer, EsmOutput, EsmSelfAttention, EsmSelfOutput
  from transformers.models.esm.modeling_esmfold import EsmForProteinFolding
  from transformers.models.esm.tokenization_esm import EsmTokenizer
  from transformers.utils import logging
label_desc: Use image node_id 1 for calling a global function with example usage: transfer_and_check_weights(original_module, our_module) without return types