def test_pad_lists_to_size():
list_x = [1, 2, 3]
list_y = ["a", "b"]
list_z = [None, None, None]
assert utils.pad_lists_to_size(list_x, list_y) == (list_x, ["a", "b", None])
assert utils.pad_lists_to_size(list_y, list_x, "c") == (["a", "b", "c"], list_x)
assert utils.pad_lists_to_size(list_z, list_x) == (list_z, list_x)
def serialise(self) -> Tuple[List[Text], List[Text]]:
"""Turn targets and predictions to lists of equal size for sklearn."""
targets = (self.action_targets + self.intent_targets + [
MarkdownWriter.generate_entity_md(gold.get("text"), gold)
for gold in self.entity_targets
])
predictions = (self.action_predictions + self.intent_predictions + [
MarkdownWriter.generate_entity_md(predicted.get("text"), predicted)
for predicted in self.entity_predictions
])
# sklearn does not cope with lists of unequal size, nor None values
return pad_lists_to_size(targets, predictions, padding_value="None")
