Add SpeechEncoderDecoder & Speech2Text2 (#13186)
* fix_torch_device_generate_test * remove @ * up * correct some bugs * correct model * finish speech2text extension * up * up * up * up * Update utils/custom_init_isort.py * up * up * update with tokenizer * correct old tok * correct old tok * fix bug * up * up * add more tests * up * fix docs * up * fix some more tests * add better config * correct some more things " * fix tests * improve docs * Apply suggestions from code review * Apply suggestions from code review * final fixes * finalize * Apply suggestions from code review Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> Co-authored-by: Lysandre Debut <lysandre@huggingface.co> * apply suggestions Lysandre and Sylvain * apply nicos suggestions * upload everything * finish Co-authored-by: Patrick von Platen <patrick@huggingface.co> Co-authored-by: your_github_username <your_github_email> Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
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docs/source/model_doc/speech_to_text_2.rst
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docs/source/model_doc/speech_to_text_2.rst
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..
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Copyright 2021 The HuggingFace Team. All rights reserved.
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Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
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the License. You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
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an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
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specific language governing permissions and limitations under the License.
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Speech2Text2
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-----------------------------------------------------------------------------------------------------------------------
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Overview
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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The Speech2Text2 model is used together with :doc:`Wav2Vec2 <wav2vec2>` for Speech Translation models proposed in
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`Large-Scale Self- and Semi-Supervised Learning for Speech Translation <https://arxiv.org/abs/2104.06678>`__ by
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Changhan Wang, Anne Wu, Juan Pino, Alexei Baevski, Michael Auli, Alexis Conneau.
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Speech2Text2 is a *decoder-only* transformer model that can be used with any speech *encoder-only*, such as
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:doc:`Wav2Vec2 <wav2vec2>` or :doc:`HuBERT <hubert>` for Speech-to-Text tasks. Please refer to the
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:doc:`SpeechEncoderDecoder <speechencoderdecoder>` class on how to combine Speech2Text2 with any speech *encoder-only*
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model.
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This model was contributed by `Patrick von Platen <https://huggingface.co/patrickvonplaten>`__.
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The original code can be found `here
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<https://github.com/pytorch/fairseq/blob/1f7ef9ed1e1061f8c7f88f8b94c7186834398690/fairseq/models/wav2vec/wav2vec2_asr.py#L266>`__.
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Tips:
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- Speech2Text2 achieves state-of-the-art results on the CoVoST Speech Translation dataset. For more information, see
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the `official models <https://huggingface.co/models?other=speech2text2>`__ .
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- Speech2Text2 is always used within the :doc:`SpeechEncoderDecoder <speechencoderdecoder>` framework.
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- Speech2Text2's tokenizer currently only supports inference, but not training.
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Inference
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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Speech2Text2's :class:`~transformers.SpeechEncoderDecoderModel` model accepts raw waveform input values from speech and
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makes use of :func:`~transformers.generation_utils.GenerationMixin.generate` to translate the input speech
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autoregressively to the target language.
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The :class:`~transformers.Wav2Vec2FeatureExtractor` class is responsible for preprocessing the input speech and
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:class:`~transformers.Speech2Text2Tokenizer` decodes the generated target tokens to the target string. The
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:class:`~transformers.Speech2Text2Processor` wraps :class:`~transformers.Wav2Vec2FeatureExtractor` and
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:class:`~transformers.Speech2Text2Tokenizer` into a single instance to both extract the input features and decode the
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predicted token ids.
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- Step-by-step Speech Translation
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.. code-block::
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>>> import torch
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>>> from transformers import Speech2Text2Processor, SpeechEncoderDecoderModel
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>>> from datasets import load_dataset
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>>> import soundfile as sf
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>>> model = SpeechEncoderDecoderModel.from_pretrained("facebook/s2t-wav2vec2-large-en-de")
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>>> processor = Speech2Text2Processor.from_pretrained("facebook/s2t-wav2vec2-large-en-de")
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>>> def map_to_array(batch):
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... speech, _ = sf.read(batch["file"])
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... batch["speech"] = speech
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... return batch
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>>> ds = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean", split="validation")
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>>> ds = ds.map(map_to_array)
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>>> inputs = processor(ds["speech"][0], sampling_rate=16_000, return_tensors="pt")
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>>> generated_ids = model.generate(input_ids=inputs["input_values"], attention_mask=inputs["attention_mask"])
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>>> transcription = processor.batch_decode(generated_ids)
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- Speech Translation via Pipelines
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The automatic speech recognition pipeline can also be used to translate speech in just a couple lines of code
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.. code-block::
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>>> from datasets import load_dataset
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>>> from transformers import pipeline
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>>> librispeech_en = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean", split="validation")
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>>> asr = pipeline("automatic-speech-recognition", model="facebook/s2t-wav2vec2-large-en-de", feature_extractor="facebook/s2t-wav2vec2-large-en-de")
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>>> translation_de = asr(librispeech_en[0]["file"])
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See `model hub <https://huggingface.co/models?filter=speech2text2>`__ to look for Speech2Text2 checkpoints.
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Speech2Text2Config
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.Speech2Text2Config
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:members:
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Speech2TextTokenizer
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.Speech2Text2Tokenizer
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:members: batch_decode, decode, save_vocabulary
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Speech2Text2Processor
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.Speech2Text2Processor
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:members: __call__, from_pretrained, save_pretrained, batch_decode, decode, as_target_processor
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Speech2Text2ForCausalLM
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.Speech2Text2ForCausalLM
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:members: forward
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40
docs/source/model_doc/speechencoderdecoder.rst
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docs/source/model_doc/speechencoderdecoder.rst
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..
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Copyright 2021 The HuggingFace Team. All rights reserved.
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Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
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the License. You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
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an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
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specific language governing permissions and limitations under the License.
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Speech Encoder Decoder Models
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-----------------------------------------------------------------------------------------------------------------------
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The :class:`~transformers.SpeechEncoderDecoderModel` can be used to initialize a speech-sequence-to-text-sequence model
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with any pretrained speech autoencoding model as the encoder (*e.g.* :doc:`Wav2Vec2 <wav2vec2>`, :doc:`Hubert
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<hubert>`) and any pretrained autoregressive model as the decoder.
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The effectiveness of initializing speech-sequence-to-text-sequence models with pretrained checkpoints for speech
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recognition and speech translation has *e.g.* been shown in `Large-Scale Self- and Semi-Supervised Learning for Speech
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Translation <https://arxiv.org/abs/2104.06678>`__ by Changhan Wang, Anne Wu, Juan Pino, Alexei Baevski, Michael Auli,
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Alexis Conneau.
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An example of how to use a :class:`~transformers.SpeechEncoderDecoderModel` for inference can be seen in
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:doc:`Speech2Text2 <speech_to_text_2>`.
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SpeechEncoderDecoderConfig
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.SpeechEncoderDecoderConfig
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:members:
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SpeechEncoderDecoderModel
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.SpeechEncoderDecoderModel
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:members: forward, from_encoder_decoder_pretrained
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