def test_length_limit_works(self):
# We're making sure the length of the text is correct if length limit is provided.
reader = SquadReader.squad2(passage_length_limit=30,
question_length_limit=10,
skip_impossible_questions=True)
instances = ensure_list(
reader.read(FIXTURES_ROOT / "rc" / "squad2.json"))
assert len(instances[0].fields["question"].tokens) == 6
assert len(instances[0].fields["passage"].tokens) == 30
# invalid examples where all the answers exceed the passage length should be skipped.
assert len(instances) == 4
# Length limit still works if we do not skip the invalid examples
reader = SquadReader.squad2(passage_length_limit=30,
question_length_limit=10,
skip_impossible_questions=False)
instances = ensure_list(
reader.read(FIXTURES_ROOT / "rc" / "squad2.json"))
assert len(instances[0].fields["question"].tokens) == 6
assert len(instances[0].fields["passage"].tokens) == 30
# invalid examples should not be skipped.
assert len(instances) == 6
# Make sure the answer texts does not change, so that the evaluation will not be affected
reader_unlimited = SquadReader.squad2(passage_length_limit=30,
question_length_limit=10,
skip_impossible_questions=False)
instances_unlimited = ensure_list(
reader_unlimited.read(FIXTURES_ROOT / "rc" / "squad2.json"))
for instance_x, instance_y in zip(instances, instances_unlimited):
print(instance_x.fields["metadata"]["answer_texts"])
assert set(instance_x.fields["metadata"]["answer_texts"]) == set(
instance_y.fields["metadata"]["answer_texts"])
def test_read_from_file(self):
reader = SquadReader()
instances = ensure_list(
reader.read(FIXTURES_ROOT / "rc" / "squad.json"))
assert len(instances) == 5
assert [t.text for t in instances[0].fields["question"].tokens[:3]
] == ["To", "whom", "did"]
assert [t.text for t in instances[0].fields["passage"].tokens[:3]] == [
"Architecturally",
",",
"the",
]
assert [t.text for t in instances[0].fields["passage"].tokens[-3:]
] == ["of", "Mary", "."]
assert instances[0].fields["span_start"].sequence_index == 102
assert instances[0].fields["span_end"].sequence_index == 104
assert [t.text
for t in instances[1].fields["question"].tokens[:3]] == [
"What",
"sits",
"on",
]
assert [t.text for t in instances[1].fields["passage"].tokens[:3]] == [
"Architecturally",
",",
"the",
]
assert [t.text for t in instances[1].fields["passage"].tokens[-3:]
] == ["of", "Mary", "."]
assert instances[1].fields["span_start"].sequence_index == 17
assert instances[1].fields["span_end"].sequence_index == 23
# We're checking this case because I changed the answer text to only have a partial
# annotation for the last token, which happens occasionally in the training data. We're
# making sure we get a reasonable output in that case here.
assert [t.text
for t in instances[3].fields["question"].tokens[:3]] == [
"Which",
"individual",
"worked",
]
assert [t.text for t in instances[3].fields["passage"].tokens[:3]
] == ["In", "1882", ","]
assert [t.text
for t in instances[3].fields["passage"].tokens[-3:]] == [
"Nuclear",
"Astrophysics",
".",
]
span_start = instances[3].fields["span_start"].sequence_index
span_end = instances[3].fields["span_end"].sequence_index
answer_tokens = instances[3].fields["passage"].tokens[span_start:(
span_end + 1)]
expected_answer_tokens = ["Father", "Julius", "Nieuwland"]
assert [t.text for t in answer_tokens] == expected_answer_tokens
def test_can_build_from_params(self):
reader = SquadReader.from_params(Params({}))
assert reader._tokenizer.__class__.__name__ == "SpacyTokenizer"
assert reader._token_indexers[
"tokens"].__class__.__name__ == "SingleIdTokenIndexer"