fixed yapf version

  def hydrogen_bond(self, d):

    """Computes Autodock Vina's hydrogen bond interaction term."""

    out_tensor = tf.where(d < -0.7, tf.ones_like(d),

                          tf.where(d < 0, (1.0 / 0.7) * (0 - d),

                                   tf.zeros_like(d)))

    out_tensor = tf.where(

        d < -0.7, tf.ones_like(d),

        tf.where(d < 0, (1.0 / 0.7) * (0 - d), tf.zeros_like(d)))

    return out_tensor

  def gaussian_first(self, d):

    distance_membership_j = inputs[3]

    distance_hidden = tf.matmul(distance, self.W_df) + self.b_df

    atom_features_hidden = tf.matmul(atom_features, self.W_cf) + self.b_cf

    outputs = tf.multiply(distance_hidden,

                          tf.gather(atom_features_hidden,

                                    distance_membership_j))

    outputs = tf.multiply(

        distance_hidden, tf.gather(atom_features_hidden, distance_membership_j))

    # for atom i in a molecule m, this step multiplies together distance info of atom pair(i,j)

    # and embeddings of atom j(both gone through a hidden layer)