use os to get vocab path

# Requriments - transformers, tokenizers

# Requirements - transformers, tokenizers

import os

from unittest import TestCase

from deepchem.feat.smiles_tokenizer import SmilesTokenizer

from transformers import RobertaForMaskedLM

  def test_tokenize(self):

      vocab_path = os.path.join(os.path.dirname(__file__), "data", "vocab.txt")

      model = RobertaForMaskedLM.from_pretrained('seyonec/SMILES_tokenized_PubChem_shard00_50k')

      model.num_parameters()

      tokenizer = SmilesTokenizer('deepchem/feat/tests/data/vocab.txt', max_len=model.config.max_position_embeddings)

      tokenizer = SmilesTokenizer(vocab_path, max_len=model.config.max_position_embeddings)

      print(tokenizer.encode("CCC(CC)COC(=O)[C@H](C)N[P@](=O)(OC[C@H]1O[C@](C#N)([C@H](O)[C@@H]1O)C1=CC=C2N1N=CN=C2N)OC1=CC=CC=C1"))