<filename>moses/dataset/dataset.py
import os
import numpy as np
import pandas as pd


AVAILABLE_SPLITS = ['train', 'test', 'test_scaffolds']


def get_dataset(split='train'):
    """
    Loads MOSES dataset

    Arguments:
        split (str or list): split to load. If str, must be
            one of: 'train', 'test', 'test_scaffolds'. If
            list, will load all splits from the list.
            None by default---loads all splits

    Returns:
        dict with splits. Keys---split names, values---lists
        of SMILES strings.
    """
    if split not in AVAILABLE_SPLITS:
        raise ValueError(
            f"Unknown split {split}. "
            f"Available splits: {AVAILABLE_SPLITS}"
        )
    base_path = os.path.dirname(__file__)
    if split not in AVAILABLE_SPLITS:
        raise ValueError(
            f"Unknown split {split}. "
            f"Available splits: {AVAILABLE_SPLITS}")
    path = os.path.join(base_path, 'data', split+'.csv.gz')
    smiles = pd.read_csv(path, compression='gzip')['SMILES'].values
    return smiles


def get_statistics(split='test'):
    base_path = os.path.dirname(__file__)
    path = os.path.join(base_path, 'data', split+'_stats.npz')
    return np.load(path, allow_pickle=True)['stats'].item()

<filename>moses/dataset/dataset.py
import os
import numpy as np
import pandas as pd


AVAILABLE_SPLITS = ['train', 'test', 'test_scaffolds']


def get_dataset(split='train'):
    """
    Loads MOSES dataset

    Arguments:
        split (str or list): split to load. If str, must be
            one of: 'train', 'test', 'test_scaffolds'. If
            list, will load all splits from the list.
            None by default---loads all splits

    Returns:
        dict with splits. Keys---split names, values---lists
        of SMILES strings.
    """
    if split not in AVAILABLE_SPLITS:
        raise ValueError(
            f"Unknown split {split}. "
            f"Available splits: {AVAILABLE_SPLITS}"
        )
    base_path = os.path.dirname(__file__)
    if split not in AVAILABLE_SPLITS:
        raise ValueError(
            f"Unknown split {split}. "
            f"Available splits: {AVAILABLE_SPLITS}")
    path = os.path.join(base_path, 'data', split+'.csv.gz')
    smiles = pd.read_csv(path, compression='gzip')['SMILES'].values
    return smiles


def get_statistics(split='test'):
    base_path = os.path.dirname(__file__)
    path = os.path.join(base_path, 'data', split+'_stats.npz')
    return np.load(path, allow_pickle=True)['stats'].item()

Loads MOSES dataset      Arguments:         split (str or list): split to load. If str, must be             one of: 'train', 'test', 'test_scaffolds'. If             list, will load all splits from the list.             None by default---loads all splits      Returns:         dict with splits. Keys---split names, values---lists         of SMILES strings.