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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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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-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 = [
{
"table": {
@@ -190,22 +190,25 @@ class TQAPipelineTests(CustomInputPipelineCommonMixin, unittest.TestCase):
results = tqa_pipeline(data, queries)
expected_results = [
{"answer": "Transformers", "coordinates": [(0, 0)], "cells": ["Transformers"]},
{"answer": "Transformers", "coordinates": [(0, 0)], "cells": ["Transformers"]},
{"answer": "Transformers", "coordinates": [(0, 0)], "cells": ["Transformers"], "aggregator": "NONE"},
{"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)],
"cells": ["Transformers", "Datasets", "Tokenizers"],
"aggregator": "COUNT",
},
{
"answer": "36542, 4512, 3934",
"answer": "AVERAGE > 36542, 4512, 3934",
"coordinates": [(0, 1), (1, 1), (2, 1)],
"cells": ["36542", "4512", "3934"],
"aggregator": "AVERAGE",
},
{
"answer": "36542, 4512, 3934",
"answer": "SUM > 36542, 4512, 3934",
"coordinates": [(0, 1), (1, 1), (2, 1)],
"cells": ["36542", "4512", "3934"],
"aggregator": "SUM",
},
]
self.assertListEqual(results, expected_results)
@@ -214,8 +217,8 @@ class TQAPipelineTests(CustomInputPipelineCommonMixin, unittest.TestCase):
def test_integration_sqa(self):
tqa_pipeline = pipeline(
"table-question-answering",
model="nielsr/tapas-base-finetuned-sqa",
tokenizer="nielsr/tapas-base-finetuned-sqa",
model="google/tapas-base-finetuned-sqa",
tokenizer="google/tapas-base-finetuned-sqa",
)
data = {
"Actors": ["Brad Pitt", "Leonardo Di Caprio", "George Clooney"],