code: def test_chemberta_pretraining(
      smiles_regression_dataset, smiles_multitask_regression_dataset
  ):
      # Pretraining in MLM mode
      from deepchem.models.torch_models.chemberta import Chemberta
  
      tokenizer_path = "seyonec/PubChem10M_SMILES_BPE_60k"
      model = Chemberta(task="mlm", tokenizer_path=tokenizer_path)
      loss = model.fit(smiles_regression_dataset, nb_epoch=1)
  
      assert loss
  
      # Pretraining in Multitask Regression Mode
      model = Chemberta(
          task="mtr", tokenizer_path=tokenizer_path, n_tasks=2
      )
      loss = model.fit(smiles_multitask_regression_dataset, nb_epoch=1)
      assert loss
  
file_path: deepchem/deepchem/models/torch_models/tests/test_chemberta.py
imports: import os
  import deepchem
  import numpy
  import pytest
label_desc: Use image node_id 1 for calling a global function with example usage: test_chemberta_pretraining(smiles_regression_dataset, smiles_multitask_regression_dataset) without return types