Merge branch 'master' into jax

from deepchem.feat.molecule_featurizers.one_hot_featurizer import ZINC_CHARSET

class TestOneHotFeaturizert(unittest.TestCase):

class TestOneHotFeaturizer(unittest.TestCase):

  """

  Test OneHotFeaturizer.

  """

Linting

-------

.. _`Flake8`: https://github.com/google/yapf

.. _`Flake8`: https://github.com/pycqa/flake8

We use `Flake8` to check our code syntax. Lint tools basically provide these benefits.

We use `Flake8`_ to check our code syntax. Lint tools basically provide these benefits.

- Prevent things like syntax errors or typos

- Save our review time (no need to check unused codes or typos)

    "\n",

    "The idea is simple: remove a single atom from the molecule and see how the model's prediction changes.  The \"atomic contribution\" for an atom is defined as the difference in activity between the whole molecule, and the fragment remaining after atom removal.  It is a measure of how much that atom affects the prediction.\n",

    "\n",

    "Contributions are also known as \"attributions\", \"coloration\", etc. in the literature. This is a model interpretation method [1], analogous to Similarity maps [2] in the QSAR domain, or occlusion methods in other fields (image classification, etc).\n",

    "Contributions are also known as \"attributions\", \"coloration\", etc. in the literature. This is a model interpretation method [1], analogous to Similarity maps [2] in the QSAR domain, or occlusion methods in other fields (image classification, etc). Present implementation was used in [4].\n",

    "\n",

    "Mariia Matveieva, Pavel Polishchuk. Institute of Molecular and Translational Medicine, Palacky University, Olomouc, Czech Republic.\n",

    "\n",

    "\n",

    "2. Riniker, S. & G. Landrum (2013) Similarity maps - a visualization strategy for molecular fingerprints and machine-learning methods. Journal of Cheminformatics, 5, 43.\n",

    "\n",

    "3. M. Matveieva, M. T. D. Cronin, P. Polishchuk, Mol. Inf. 2019, 38, 1800084. "

    "3. M. Matveieva, M. T. D. Cronin, P. Polishchuk, Mol. Inf. 2019, 38, 1800084. \n",

    "\n",

    "4. Matveieva, M., Polishchuk, P. Benchmarks for interpretation of QSAR models. J Cheminform 13, 41 (2021). https://doi.org/10.1186/s13321-021-00519-x\n"

   ]

  },

  {