Fixed broken PCBA example

from deepchem.metrics import to_one_hot

from deepchem.utils.evaluate import Evaluator

from deepchem.models.tensorflow_models.fcnet import TensorflowMultiTaskClassifier

from deepchem.models.tensorflow_models import TensorflowModel

np.random.seed(123)

pcba_tasks, pcba_datasets, transformers = load_pcba()

(train_dataset, valid_dataset) = pcba_datasets

(train_dataset, valid_dataset, test_dataset) = pcba_datasets

metric = Metric(metrics.roc_auc_score, np.mean, mode="classification")

metric = Metric(metrics.roc_auc_score, np.mean,

                               mode="classification")

n_features = train_dataset.get_data_shape()[0]

model_dir = None

model = TensorflowMultiTaskClassifier(

    len(pcba_tasks), n_features, model_dir, dropouts=[.25],

    learning_rate=0.001, weight_init_stddevs=[.1],

    batch_size=64, verbosity="high")

    len(pcba_tasks),

    n_features,

    model_dir,

    dropouts=[.25],

    learning_rate=0.001,

    weight_init_stddevs=[.1],

    batch_size=64,

    verbosity="high")

# Fit trained model

model.fit(train_dataset)

model.save()

train_evaluator = Evaluator(model, train_dataset, transformers, verbosity=verbosity)

train_evaluator = Evaluator(

    model, train_dataset, transformers, verbosity=verbosity)

train_scores = train_evaluator.compute_model_performance([metric])

print("Train scores")

print(train_scores)

valid_evaluator = Evaluator(model, valid_dataset, transformers, verbosity=verbosity)

valid_evaluator = Evaluator(

    model, valid_dataset, transformers, verbosity=verbosity)

valid_scores = valid_evaluator.compute_model_performance([metric])

print("Validation scores")