mirror of
https://github.com/wassname/alignment-handbook.git
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Lewis Tunstall
80 lines
3.1 KiB
Python
80 lines
3.1 KiB
Python
# coding=utf-8
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# Copyright 2023 The HuggingFace Team. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import unittest
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import pytest
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from alignment import DataArguments, get_datasets
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class GetDatasetsTest(unittest.TestCase):
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"""Each of these test datasets has 100 examples"""
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def test_loading_data_args(self):
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dataset_mixer = {
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"HuggingFaceH4/testing_alpaca_small": 0.5,
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"HuggingFaceH4/testing_self_instruct_small": 0.3,
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"HuggingFaceH4/testing_codealpaca_small": 0.2,
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}
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data_args = DataArguments(dataset_mixer=dataset_mixer)
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datasets = get_datasets(data_args)
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self.assertEqual(len(datasets["train"]), 100)
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self.assertEqual(len(datasets["test"]), 300)
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def test_loading_data_dict(self):
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dataset_mixer = {
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"HuggingFaceH4/testing_alpaca_small": 0.5,
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"HuggingFaceH4/testing_self_instruct_small": 0.3,
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"HuggingFaceH4/testing_codealpaca_small": 0.2,
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}
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datasets = get_datasets(dataset_mixer)
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self.assertEqual(len(datasets["train"]), 100)
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self.assertEqual(len(datasets["test"]), 300)
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def test_loading_with_unit_fractions(self):
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dataset_mixer = {
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"HuggingFaceH4/testing_alpaca_small": 1.0,
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"HuggingFaceH4/testing_self_instruct_small": 1.0,
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"HuggingFaceH4/testing_codealpaca_small": 1.0,
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}
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datasets = get_datasets(dataset_mixer)
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self.assertEqual(len(datasets["train"]), 300)
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self.assertEqual(len(datasets["test"]), 300)
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def test_loading_with_fractions_greater_than_unity(self):
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dataset_mixer = {
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"HuggingFaceH4/testing_alpaca_small": 0.7,
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"HuggingFaceH4/testing_self_instruct_small": 0.4,
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}
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datasets = get_datasets(dataset_mixer)
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self.assertEqual(len(datasets["train"]), 70 + 40)
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self.assertEqual(len(datasets["test"]), 200)
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def test_loading_fails_with_negative_fractions(self):
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dataset_mixer = {
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"HuggingFaceH4/testing_alpaca_small": 0.7,
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"HuggingFaceH4/testing_self_instruct_small": -0.3,
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}
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with pytest.raises(ValueError, match=r"Dataset fractions cannot be negative."):
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get_datasets(dataset_mixer)
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def test_loading_single_split_with_unit_fractions(self):
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dataset_mixer = {
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"HuggingFaceH4/testing_alpaca_small": 1.0,
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}
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datasets = get_datasets(dataset_mixer, splits=["test"])
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self.assertEqual(len(datasets["test"]), 100)
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self.assertRaises(KeyError, lambda: datasets["train"])
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