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ee4fa2e465
* [AutoProcessor] Add Wav2Vec2WithLM & small fix * revert line removal * Update src/transformers/__init__.py * add test * up * up * small fix
58 lines
2.2 KiB
Python
58 lines
2.2 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 tempfile
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import unittest
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from shutil import copyfile
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from transformers import AutoProcessor, Wav2Vec2Config, Wav2Vec2Processor
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from transformers.file_utils import FEATURE_EXTRACTOR_NAME
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SAMPLE_PROCESSOR_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_VOCAB = os.path.join(os.path.dirname(os.path.abspath(__file__)), "fixtures/vocab.json")
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class AutoFeatureExtractorTest(unittest.TestCase):
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def test_processor_from_model_shortcut(self):
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processor = AutoProcessor.from_pretrained("facebook/wav2vec2-base-960h")
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self.assertIsInstance(processor, Wav2Vec2Processor)
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def test_processor_from_local_directory_from_repo(self):
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with tempfile.TemporaryDirectory() as tmpdirname:
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model_config = Wav2Vec2Config()
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processor = AutoProcessor.from_pretrained("facebook/wav2vec2-base-960h")
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# save in new folder
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model_config.save_pretrained(tmpdirname)
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processor.save_pretrained(tmpdirname)
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processor = AutoProcessor.from_pretrained(tmpdirname)
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self.assertIsInstance(processor, Wav2Vec2Processor)
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def test_processor_from_local_directory_from_extractor_config(self):
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with tempfile.TemporaryDirectory() as tmpdirname:
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# copy relevant files
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copyfile(SAMPLE_PROCESSOR_CONFIG, os.path.join(tmpdirname, FEATURE_EXTRACTOR_NAME))
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copyfile(SAMPLE_VOCAB, os.path.join(tmpdirname, "vocab.json"))
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processor = AutoProcessor.from_pretrained(tmpdirname)
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self.assertIsInstance(processor, Wav2Vec2Processor)
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