transformers/tests/test_pipelines_question_answering.py
Thomas Wolf f4e04cd2c6
[breaking|pipelines|tokenizers] Adding slow-fast tokenizers equivalence tests pipelines - Removing sentencepiece as a required dependency (#8073)
* Fixing roberta for slow-fast tests

* WIP getting equivalence on pipelines

* slow-to-fast equivalence - working on question-answering pipeline

* optional FAISS tests

* Pipeline Q&A

* Move pipeline tests to their own test job again

* update tokenizer to add sequence id methods

* update to tokenizers 0.9.4

* set sentencepiecce as optional

* clean up squad

* clean up pipelines to use sequence_ids

* style/quality

* wording

* Switch to use_fast = True by default

* update tests for use_fast at True by default

* fix rag tokenizer test

* removing protobuf from required dependencies

* fix NER test for use_fast = True by default

* fixing example tests (Q&A examples use slow tokenizers for now)

* protobuf in main deps extras["sentencepiece"] and example deps

* fix protobug install test

* try to fix seq2seq by switching to slow tokenizers for now

* Update src/transformers/tokenization_utils_base.py

Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Update src/transformers/tokenization_utils_base.py

Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
2020-11-15 22:50:59 +01:00

172 lines
6.8 KiB
Python

import unittest
from transformers.data.processors.squad import SquadExample
from transformers.pipelines import Pipeline, QuestionAnsweringArgumentHandler
from .test_pipelines_common import CustomInputPipelineCommonMixin
class QAPipelineTests(CustomInputPipelineCommonMixin, unittest.TestCase):
pipeline_task = "question-answering"
pipeline_running_kwargs = {
"padding": "max_length",
"max_seq_len": 25,
"doc_stride": 5,
} # Default is 'longest' but we use 'max_length' to test equivalence between slow/fast tokenizers
small_models = [
"sshleifer/tiny-distilbert-base-cased-distilled-squad"
] # Models tested without the @slow decorator
large_models = [] # Models tested with the @slow decorator
valid_inputs = [
{"question": "Where was HuggingFace founded ?", "context": "HuggingFace was founded in Paris."},
{
"question": "In what field is HuggingFace working ?",
"context": "HuggingFace is a startup based in New-York founded in Paris which is trying to solve NLP.",
},
]
def _test_pipeline(self, nlp: Pipeline):
output_keys = {"score", "answer", "start", "end"}
valid_inputs = [
{"question": "Where was HuggingFace founded ?", "context": "HuggingFace was founded in Paris."},
{
"question": "In what field is HuggingFace working ?",
"context": "HuggingFace is a startup based in New-York founded in Paris which is trying to solve NLP.",
},
]
invalid_inputs = [
{"question": "", "context": "This is a test to try empty question edge case"},
{"question": None, "context": "This is a test to try empty question edge case"},
{"question": "What is does with empty context ?", "context": ""},
{"question": "What is does with empty context ?", "context": None},
]
self.assertIsNotNone(nlp)
mono_result = nlp(valid_inputs[0])
self.assertIsInstance(mono_result, dict)
for key in output_keys:
self.assertIn(key, mono_result)
multi_result = nlp(valid_inputs)
self.assertIsInstance(multi_result, list)
self.assertIsInstance(multi_result[0], dict)
for result in multi_result:
for key in output_keys:
self.assertIn(key, result)
for bad_input in invalid_inputs:
self.assertRaises(ValueError, nlp, bad_input)
self.assertRaises(ValueError, nlp, invalid_inputs)
def test_argument_handler(self):
qa = QuestionAnsweringArgumentHandler()
Q = "Where was HuggingFace founded ?"
C = "HuggingFace was founded in Paris"
normalized = qa(Q, C)
self.assertEqual(type(normalized), list)
self.assertEqual(len(normalized), 1)
self.assertEqual({type(el) for el in normalized}, {SquadExample})
normalized = qa(question=Q, context=C)
self.assertEqual(type(normalized), list)
self.assertEqual(len(normalized), 1)
self.assertEqual({type(el) for el in normalized}, {SquadExample})
normalized = qa(question=Q, context=C)
self.assertEqual(type(normalized), list)
self.assertEqual(len(normalized), 1)
self.assertEqual({type(el) for el in normalized}, {SquadExample})
normalized = qa({"question": Q, "context": C})
self.assertEqual(type(normalized), list)
self.assertEqual(len(normalized), 1)
self.assertEqual({type(el) for el in normalized}, {SquadExample})
normalized = qa([{"question": Q, "context": C}])
self.assertEqual(type(normalized), list)
self.assertEqual(len(normalized), 1)
self.assertEqual({type(el) for el in normalized}, {SquadExample})
normalized = qa([{"question": Q, "context": C}, {"question": Q, "context": C}])
self.assertEqual(type(normalized), list)
self.assertEqual(len(normalized), 2)
self.assertEqual({type(el) for el in normalized}, {SquadExample})
normalized = qa(X={"question": Q, "context": C})
self.assertEqual(type(normalized), list)
self.assertEqual(len(normalized), 1)
self.assertEqual({type(el) for el in normalized}, {SquadExample})
normalized = qa(X=[{"question": Q, "context": C}])
self.assertEqual(type(normalized), list)
self.assertEqual(len(normalized), 1)
self.assertEqual({type(el) for el in normalized}, {SquadExample})
normalized = qa(data={"question": Q, "context": C})
self.assertEqual(type(normalized), list)
self.assertEqual(len(normalized), 1)
self.assertEqual({type(el) for el in normalized}, {SquadExample})
def test_argument_handler_error_handling(self):
qa = QuestionAnsweringArgumentHandler()
Q = "Where was HuggingFace founded ?"
C = "HuggingFace was founded in Paris"
with self.assertRaises(KeyError):
qa({"context": C})
with self.assertRaises(KeyError):
qa({"question": Q})
with self.assertRaises(KeyError):
qa([{"context": C}])
with self.assertRaises(ValueError):
qa(None, C)
with self.assertRaises(ValueError):
qa("", C)
with self.assertRaises(ValueError):
qa(Q, None)
with self.assertRaises(ValueError):
qa(Q, "")
with self.assertRaises(ValueError):
qa(question=None, context=C)
with self.assertRaises(ValueError):
qa(question="", context=C)
with self.assertRaises(ValueError):
qa(question=Q, context=None)
with self.assertRaises(ValueError):
qa(question=Q, context="")
with self.assertRaises(ValueError):
qa({"question": None, "context": C})
with self.assertRaises(ValueError):
qa({"question": "", "context": C})
with self.assertRaises(ValueError):
qa({"question": Q, "context": None})
with self.assertRaises(ValueError):
qa({"question": Q, "context": ""})
with self.assertRaises(ValueError):
qa([{"question": Q, "context": C}, {"question": None, "context": C}])
with self.assertRaises(ValueError):
qa([{"question": Q, "context": C}, {"question": "", "context": C}])
with self.assertRaises(ValueError):
qa([{"question": Q, "context": C}, {"question": Q, "context": None}])
with self.assertRaises(ValueError):
qa([{"question": Q, "context": C}, {"question": Q, "context": ""}])
def test_argument_handler_error_handling_odd(self):
qa = QuestionAnsweringArgumentHandler()
with self.assertRaises(ValueError):
qa(None)
with self.assertRaises(ValueError):
qa(Y=None)
with self.assertRaises(ValueError):
qa(1)