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65 lines
2.7 KiB
Python
65 lines
2.7 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 json
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import os
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import tempfile
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import unittest
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from transformers import AutoFeatureExtractor, Wav2Vec2Config, 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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SAMPLE_CONFIG = os.path.join(os.path.dirname(os.path.abspath(__file__)), "fixtures/dummy-config.json")
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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_from_key(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_directory_from_config(self):
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with tempfile.TemporaryDirectory() as tmpdirname:
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model_config = Wav2Vec2Config()
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# remove feature_extractor_type to make sure config.json alone is enough to load feature processor locally
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config_dict = AutoFeatureExtractor.from_pretrained(SAMPLE_FEATURE_EXTRACTION_CONFIG_DIR).to_dict()
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config_dict.pop("feature_extractor_type")
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config = Wav2Vec2FeatureExtractor(**config_dict)
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# save in new folder
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model_config.save_pretrained(tmpdirname)
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config.save_pretrained(tmpdirname)
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config = AutoFeatureExtractor.from_pretrained(tmpdirname)
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# make sure private variable is not incorrectly saved
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dict_as_saved = json.loads(config.to_json_string())
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self.assertTrue("_processor_class" not in dict_as_saved)
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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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