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39084ca663
* Add the ImageClassificationPipeline * Code review Co-authored-by: patrickvonplaten <patrick.v.platen@gmail.com> * Have `load_image` at the module level Co-authored-by: patrickvonplaten <patrick.v.platen@gmail.com>
40 lines
1.6 KiB
Python
40 lines
1.6 KiB
Python
# coding=utf-8
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# Copyright 2021 the HuggingFace Inc. team.
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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 os
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import unittest
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from transformers import AutoFeatureExtractor, Wav2Vec2FeatureExtractor
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SAMPLE_FEATURE_EXTRACTION_CONFIG_DIR = os.path.join(os.path.dirname(os.path.abspath(__file__)), "fixtures")
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SAMPLE_FEATURE_EXTRACTION_CONFIG = os.path.join(
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os.path.dirname(os.path.abspath(__file__)), "fixtures/dummy_feature_extractor_config.json"
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)
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class AutoFeatureExtractorTest(unittest.TestCase):
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def test_feature_extractor_from_model_shortcut(self):
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config = AutoFeatureExtractor.from_pretrained("facebook/wav2vec2-base-960h")
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self.assertIsInstance(config, Wav2Vec2FeatureExtractor)
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def test_feature_extractor_from_local_directory(self):
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config = AutoFeatureExtractor.from_pretrained(SAMPLE_FEATURE_EXTRACTION_CONFIG_DIR)
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self.assertIsInstance(config, Wav2Vec2FeatureExtractor)
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def test_feature_extractor_from_local_file(self):
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config = AutoFeatureExtractor.from_pretrained(SAMPLE_FEATURE_EXTRACTION_CONFIG)
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self.assertIsInstance(config, Wav2Vec2FeatureExtractor)
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