56 lines
2.2 KiB
Python
56 lines
2.2 KiB
Python
# coding=utf-8
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# Copyright 2021 HuggingFace Inc.
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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 json
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import os
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import tempfile
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from transformers.testing_utils import check_json_file_has_correct_format
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class FeatureExtractionSavingTestMixin:
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test_cast_dtype = None
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def test_feat_extract_to_json_string(self):
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feat_extract = self.feature_extraction_class(**self.feat_extract_dict)
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obj = json.loads(feat_extract.to_json_string())
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for key, value in self.feat_extract_dict.items():
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self.assertEqual(obj[key], value)
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def test_feat_extract_to_json_file(self):
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feat_extract_first = self.feature_extraction_class(**self.feat_extract_dict)
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with tempfile.TemporaryDirectory() as tmpdirname:
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json_file_path = os.path.join(tmpdirname, "feat_extract.json")
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feat_extract_first.to_json_file(json_file_path)
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feat_extract_second = self.feature_extraction_class.from_json_file(json_file_path)
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self.assertEqual(feat_extract_second.to_dict(), feat_extract_first.to_dict())
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def test_feat_extract_from_and_save_pretrained(self):
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feat_extract_first = self.feature_extraction_class(**self.feat_extract_dict)
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with tempfile.TemporaryDirectory() as tmpdirname:
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saved_file = feat_extract_first.save_pretrained(tmpdirname)[0]
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check_json_file_has_correct_format(saved_file)
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feat_extract_second = self.feature_extraction_class.from_pretrained(tmpdirname)
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self.assertEqual(feat_extract_second.to_dict(), feat_extract_first.to_dict())
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def test_init_without_params(self):
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feat_extract = self.feature_extraction_class()
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self.assertIsNotNone(feat_extract)
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