Fix median calculation.

                                             n_trials)

# Compute accuracies

task_scores = {task: [] for task in range(len(test_dataset.get_task_names()))}

for trial_num, (task, support) in enumerate(support_generator):

  # Batch size of models

  batch_size = 50

  #graph_model = dc.nn.SequentialGraph(n_feat)

  model = GraphConvModel(len(sider_tasks), graph_conv_layers=[

  model = GraphConvModel(1, graph_conv_layers=[

                         64, 128, 64], batch_size=batch_size)

  # Fit trained model

  model.fit(support, nb_epoch=10)

print("Standard Deviations")

print(std_task_scores)

print("Median of Mean Scores")

"""

To support both python 3.x and 2.7

dict.values() returns an object of type dict_values

and np.median shouts loudly if this is the case so 

converted it to list before passing it to np.array()

"""

try:

  print(np.median(np.array(mean_task_scores.values())))

except TypeError as e:

  print(np.median(np.array(list(mean_task_scores.values()))))