def test_preprocessed_splitter():
class DemeanPreproc():
"""Just for tests :)"""
def apply(self, dataset, can_fit=False):
topo_view = dataset.get_topological_view()
if can_fit:
self.mean = np.mean(topo_view)
dataset.set_topological_view(topo_view - self.mean)
data = np.arange(10)
dataset = DenseDesignMatrixWrapper(topo_view=to_4d_array(data),
y=np.zeros(10))
splitter = SingleFoldSplitter(n_folds=10, i_test_fold=9)
preproc_splitter = PreprocessedSplitter(dataset_splitter=splitter,
preprocessor=DemeanPreproc())
first_round_sets = preproc_splitter.get_train_valid_test(dataset)
train_topo = first_round_sets['train'].get_topological_view()
valid_topo = first_round_sets['valid'].get_topological_view()
test_topo = first_round_sets['test'].get_topological_view()
assert np.array_equal(
train_topo, to_4d_array([-3.5, -2.5, -1.5, -0.5, 0.5, 1.5, 2.5, 3.5]))
assert np.array_equal(valid_topo, to_4d_array([4.5]))
assert np.array_equal(test_topo, to_4d_array([5.5]))
second_round_set = preproc_splitter.get_train_merged_valid_test(dataset)
train_topo = second_round_set['train'].get_topological_view()
valid_topo = second_round_set['valid'].get_topological_view()
test_topo = second_round_set['test'].get_topological_view()
assert np.array_equal(train_topo,
to_4d_array([-4, -3, -2, -1, 0, 1, 2, 3, 4]))
assert np.array_equal(valid_topo, to_4d_array([4]))
assert np.array_equal(test_topo, to_4d_array([5]))
def __init__(self,
final_layer,
dataset,
splitter,
preprocessor,
iterator,
loss_expression,
updates_expression,
updates_modifier,
monitors,
stop_criterion,
remember_best_chan,
run_after_early_stop,
batch_modifier=None):
self.final_layer = final_layer
self.dataset = dataset
self.dataset_provider = PreprocessedSplitter(splitter, preprocessor)
self.preprocessor = preprocessor
self.iterator = iterator
self.loss_expression = loss_expression
self.updates_expression = updates_expression
self.updates_modifier = updates_modifier
self.monitors = monitors
self.stop_criterion = stop_criterion
self.monitor_manager = MonitorManager(monitors)
self.remember_extension = RememberBest(remember_best_chan)
self.run_after_early_stop = run_after_early_stop
self.batch_modifier = batch_modifier
