def evaluate(self, session):
metric_dict = {}
try:
while True:
real_label_ids, logits = session.run(
[self.labels, self.logits])
predict_label_ids = self._logits_to_label_ids(logits)
predict_labels = DatasetMaker.label_ids_to_labels(
predict_label_ids)
real_labels = DatasetMaker.label_ids_to_labels(real_label_ids)
metric_dict = metric_collect(real_labels, predict_labels,
metric_dict)
except tf.errors.OutOfRangeError:
return metric_dict
def infer(self, session, file_handler):
try:
while True:
data_ids, logits = session.run([self.ids, self.logits])
predict_label_ids = self._logits_to_label_ids(logits)
predict_labels = DatasetMaker.label_ids_to_labels(
predict_label_ids)
file_handler.write(
np.concatenate([data_ids, predict_labels], axis=1))
except tf.errors.OutOfRangeError as e:
raise e