def _get_top_n_samples(model_predictions: List[ModelPrediction], n: int, best: bool):
top_n_samples = SortedList(key=lambda sample: -sample.true_label_probability) if best else SortedList()
for model_prediction in model_predictions:
if best == model_prediction.is_correct():
if len(top_n_samples) < n:
top_n_samples.add(model_prediction)
else:
if best != (model_prediction < top_n_samples[-1]):
top_n_samples.pop()
top_n_samples.add(model_prediction)
return [sample for sample in top_n_samples] # so that it returns a normal list instead of SortedList
def test_nlines(self):
reader, start_time = self.init_reader()
tpoints = SortedList()
time_points, jobs = reader.next(start_time)
tpoints.update(time_points)
total_jobs = len(jobs)
while True:
if not tpoints:
break
_time = tpoints.pop(0)
time_points, jobs = reader.next(_time)
total_jobs += sum([len(js) for js in jobs.values()])
tpoints.update(time_points)
self.assertEqual(total_jobs, 25)
ds = [a for a in AnmalZoo]
for uat in ds:
r = SortedList()
big128, big256 = 0, 0
automatas = atma.parse_anml_file(anml_path[uat])
automatas.remove_ors()
automatas = automatas.get_connected_components_as_automatas()
for atm in automatas:
nc = atm.nodes_count
if nc >= 128:
big128 += 1
if nc >= 256:
big256 += 1
if nc > bigest_component_size:
print "this NFA can not be fit:", uat
break
if r and nc <= r[-1]: # can be packed
cand_residual = r.pop(-1)
r.add(cand_residual - nc)
else: # new fcb
r.add(bigest_component_size - nc)
print "uat %s needs %d connected local switches each with (%d,%d) size. There are %d nodes not being assigned." \
" It has %d CCs bigger than 128 and %d CCs bigger than 256"\
%(uat, len(r), fcb_size, fcb_size, sum(r[:-1]), big128, big256)
