Added basic skeleton

from deepchem.molnet.load_function.hppb_datasets import load_hppb

from deepchem.molnet.load_function.chembl25_datasets import load_chembl25

from deepchem.molnet.load_function.zinc15_datasets import load_zinc15

from deepchem.molnet.load_function.freesolv_dataset import load_freesolv

from deepchem.molnet.load_function.material_datasets.load_bandgap import load_bandgap

from deepchem.molnet.load_function.material_datasets.load_perovskite import load_perovskite

from deepchem.molnet.load_function.material_datasets.load_Pt_NO_surface_adsorbate_energy import load_Platinum_Adsorption

"""

freesolv dataset loader.

"""

import os

import deepchem as dc

from deepchem.molnet.load_function.molnet_loader import TransformerGenerator, _MolnetLoader

from deepchem.data import Dataset

from typing import List, Optional, Tuple, Union

FREESOLV_URL = 'https://deepchemdata.s3.us-west-1.amazonaws.com/datasets/freesolv.csv.gz'

FREESOLV_TASKS = ['y']

class _FreesolvLoader(_MolnetLoader):

    def create_dataset(self) -> Dataset:

        dataset_file = os.path.join(self.data_dir, 'freesolv.csv.gz')

        if not os.path.exists(dataset_file):

            dc.utils.data_utils.download_url(url = FREESOLV_URL, dest_dir = self.data_dir)

            loader = dc.data.CSVLoader(tasks = self.tasks, feature_field = 'smiles', featurizer = self.featurizer)

            return loader.create_dataset(dataset_file)

def load_freesolv(

    featurizer: Union[dc.feat.Featurizer, str] = dc.feat.MATFeaturizer(),

    splitter: Union[dc.splits.Splitter, str, None] = None,

    transformers: List[Union[TransformerGenerator, str]] = ['normalization'],

    reload: bool = True,

    data_dir: Optional[str] = None,

    save_dir: Optional[str] = None,

    **kwargs

) -> Tuple[List[str], Tuple[Dataset, ...], List[dc.trans.Transformer]]:

    loader = _FreesolvLoader(featurizer, splitter, transformers, FREESOLV_TASKS, data_dir, save_dir, **kwargs)

    return loader.load_dataset('freesolv', reload)

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