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Changing model default for TableQuestionAnsweringPipeline. (#9729)

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* Changing model default for TableQuestionAnsweringPipeline.

- Discussion: https://discuss.huggingface.co/t/table-question-answering-is-not-an-available-task-under-pipeline/3284/6

* Updating slow tests that were out of sync.
This commit is contained in:
Nicolas Patry
2021-01-21 14:31:51 +01:00
committed by GitHub
parent 3f290e6c84
commit 23e5a36ee6
2 changed files with 14 additions and 11 deletions
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6
src/transformers/pipelines/__init__.py
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@@ -136,9 +136,9 @@ SUPPORTED_TASKS = {
"tf": None, "tf": None,
"default": { "default": {
"model": { "model": {
"pt": "nielsr/tapas-base-finetuned-wtq", "pt": "google/tapas-base-finetuned-wtq",
"tokenizer": "nielsr/tapas-base-finetuned-wtq", "tokenizer": "google/tapas-base-finetuned-wtq",
"tf": "nielsr/tapas-base-finetuned-wtq", "tf": "google/tapas-base-finetuned-wtq",
}, },
}, },
}, },

19
tests/test_pipelines_table_question_answering.py
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@@ -32,7 +32,7 @@ class TQAPipelineTests(CustomInputPipelineCommonMixin, unittest.TestCase):
"lysandre/tiny-tapas-random-wtq", "lysandre/tiny-tapas-random-wtq",
"lysandre/tiny-tapas-random-sqa", "lysandre/tiny-tapas-random-sqa",
] ]
large_models = ["nielsr/tapas-base-finetuned-wtq"] # Models tested with the @slow decorator large_models = ["google/tapas-base-finetuned-wtq"] # Models tested with the @slow decorator
valid_inputs = [ valid_inputs = [
{ {
"table": { "table": {
@@ -190,22 +190,25 @@ class TQAPipelineTests(CustomInputPipelineCommonMixin, unittest.TestCase):
results = tqa_pipeline(data, queries) results = tqa_pipeline(data, queries)
expected_results = [ expected_results = [
{"answer": "Transformers", "coordinates": [(0, 0)], "cells": ["Transformers"]}, {"answer": "Transformers", "coordinates": [(0, 0)], "cells": ["Transformers"], "aggregator": "NONE"},
{"answer": "Transformers", "coordinates": [(0, 0)], "cells": ["Transformers"]}, {"answer": "Transformers", "coordinates": [(0, 0)], "cells": ["Transformers"], "aggregator": "NONE"},
{ {
"answer": "Transformers, Datasets, Tokenizers", "answer": "COUNT > Transformers, Datasets, Tokenizers",
"coordinates": [(0, 0), (1, 0), (2, 0)], "coordinates": [(0, 0), (1, 0), (2, 0)],
"cells": ["Transformers", "Datasets", "Tokenizers"], "cells": ["Transformers", "Datasets", "Tokenizers"],
"aggregator": "COUNT",
}, },
{ {
"answer": "36542, 4512, 3934", "answer": "AVERAGE > 36542, 4512, 3934",
"coordinates": [(0, 1), (1, 1), (2, 1)], "coordinates": [(0, 1), (1, 1), (2, 1)],
"cells": ["36542", "4512", "3934"], "cells": ["36542", "4512", "3934"],
"aggregator": "AVERAGE",
}, },
{ {
"answer": "36542, 4512, 3934", "answer": "SUM > 36542, 4512, 3934",
"coordinates": [(0, 1), (1, 1), (2, 1)], "coordinates": [(0, 1), (1, 1), (2, 1)],
"cells": ["36542", "4512", "3934"], "cells": ["36542", "4512", "3934"],
"aggregator": "SUM",
}, },
] ]
self.assertListEqual(results, expected_results) self.assertListEqual(results, expected_results)
@@ -214,8 +217,8 @@ class TQAPipelineTests(CustomInputPipelineCommonMixin, unittest.TestCase):
def test_integration_sqa(self): def test_integration_sqa(self):
tqa_pipeline = pipeline( tqa_pipeline = pipeline(
"table-question-answering", "table-question-answering",
model="nielsr/tapas-base-finetuned-sqa", model="google/tapas-base-finetuned-sqa",
tokenizer="nielsr/tapas-base-finetuned-sqa", tokenizer="google/tapas-base-finetuned-sqa",
) )
data = { data = {
"Actors": ["Brad Pitt", "Leonardo Di Caprio", "George Clooney"], "Actors": ["Brad Pitt", "Leonardo Di Caprio", "George Clooney"],