fixed all optional dependency tests

# Requirements - transformers, tokenizers

import os

import unittest

from unittest import TestCase

from deepchem.feat.smiles_tokenizer import SmilesTokenizer

try:

  from transformers import RobertaForMaskedLM

  from deepchem.feat.smiles_tokenizer import SmilesTokenizer

  has_transformers = True

except:

  has_transformers = False

class TestSmilesTokenizer(TestCase):

  """Tests the SmilesTokenizer to load the USPTO vocab file and a ChemBERTa Masked LM model with pre-trained weights.."""

  @unittest.skipIf(not has_transformers, 'transformers are not installed')

  def test_tokenize(self):

    current_dir = os.path.dirname(os.path.realpath(__file__))

    vocab_path = os.path.join(current_dir, 'data', 'vocab.txt')

import numpy as np

import deepchem as dc

from deepchem.models import GATModel

from deepchem.feat import MolGraphConvFeaturizer

from deepchem.models.tests.test_graph_models import get_dataset

try:

  import dgl

  import dgllife

  import torch

  from deepchem.feat import MolGraphConvFeaturizer

  from deepchem.models import GATModel

  has_torch_and_dgl = True

except:

  has_torch_and_dgl = False