Merge remote-tracking branch 'origin/master' into new_bm_design

# TODO: Get rid of this when there is a stable release of deepchem.

RUN git clone https://github.com/deepchem/deepchem.git && \

    cd deepchem && \

    git checkout 415aebadff54175b7ba108964723c8f69438af94 && \

    git checkout tags/1.0.0 && \

    bash scripts/install_deepchem_conda.sh root && \

    pip install tensorflow-gpu==0.12.1 && \

    pip install tensorflow-gpu==1.0.1 && \

    python setup.py develop

# Clean up

  NOTE(LESWING) Not Thread Safe in initialization of charset

  """

  def __init__(self, charset, padlength=120):

  def __init__(self, charset=None, padlength=120):

    """

    Parameters

    ----------

    """

    smiles = [Chem.MolToSmiles(mol) for mol in mols]

    if self.charset is None:

      self.charset = self._create_charset(mols)

      self.charset = self._create_charset(smiles)

    return np.array([self.one_hot_encoded(smile) for smile in smiles])

  def one_hot_array(self, i):

    """

    s = set()

    for smile in smiles:

      s.union(list(smile))

    return sorted(list(s))

      for c in smile:

        s.add(c)

    return [' '] + sorted(list(s))

from scipy.stats import pearsonr

def to_one_hot(y):

def to_one_hot(y, n_classes=2):

  """Transforms label vector into one-hot encoding.

  Turns y into vector of shape [n_samples, 2] (assuming binary labels).

    A vector of shape [n_samples, 1]

  """

  n_samples = np.shape(y)[0]

  y_hot = np.zeros((n_samples, 2))

  y_hot = np.zeros((n_samples, n_classes))

  y_hot[np.arange(n_samples), y.astype(np.int64)] = 1

  return y_hot

from deepchem.models.models import Model

from deepchem.models.sklearn_models import SklearnModel

from deepchem.models.xgboost_models import XGBoostModel

from deepchem.models.tf_new_models.multitask_classifier import MultitaskGraphClassifier

from deepchem.models.tf_new_models.multitask_regressor import MultitaskGraphRegressor

from deepchem.models.tf_new_models.DTNN_regressor import DTNNGraphRegressor

from deepchem.models.tf_new_models.support_classifier import SupportGraphClassifier

from deepchem.models.multitask import SingletaskToMultitask

from deepchem.models.sequential import Sequential

from deepchem.models.tensorflow_models.progressive_multitask import ProgressiveMultitaskRegressor

from deepchem.models.tensorflow_models.progressive_joint import ProgressiveJointRegressor

from deepchem.models.tensorflow_models.IRV import TensorflowMultiTaskIRVClassifier

from deepchem.models.tensorgraph.tensor_graph import TensorGraph, MultiTaskTensorGraph

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