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Add README to examples directory (#4086)
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examples/README.md

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The examples in this directory demonstrate applied use of the torchaudio library. They are included only for reference purposes.
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> [!NOTE]
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> **We have transitioned TorchAudio into a
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> maintenance phase. Our main goals were to reduce redundancies with the rest of the
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> PyTorch ecosystem, make it easier to maintain, and create a version of
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> TorchAudio that is more tightly scoped to its strengths: processing audio
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> data for ML. Because of this transition, the examples included here will no longer be maintained
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> going forward. The scripts may not work properly as is. For hands on examples of features in the
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> library that *are* still supported, see the "tutorials" subdirectory. Please see
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> [our community message](https://github.com/pytorch/audio/issues/3902)
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> for more details.**

examples/libtorchaudio/CMakeLists.txt

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project(libtorchaudio-cpp-example)
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SET(BUILD_SOX ON CACHE BOOL "Build libsox into libtorchaudio")
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SET(BUILD_KALDI OFF CACHE BOOL "Build Kaldi into libtorchaudio")
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SET(BUILD_RNNT ON CACHE BOOL "Build RNN transducer into libtorchaudio")
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SET(BUILD_TORCHAUDIO_PYTHON_EXTENSION OFF CACHE BOOL "Build Python binding")
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examples/libtorchaudio/README.md

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# Libtorchaudio Examples
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* [Augmentation](./augmentation)
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* [Speech Recognition with wav2vec2.0](./speech_recognition)
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## Build
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cd build
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cmake -GNinja \
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-DCMAKE_PREFIX_PATH="$(python -c 'import torch;print(torch.utils.cmake_prefix_path)')" \
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-DBUILD_SOX=ON \
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-DBUILD_KALDI=OFF \
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-DBUILD_RNNT=ON \
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..
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cmake --build .

examples/libtorchaudio/build.sh

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git submodule update
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cmake -GNinja \
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-DCMAKE_PREFIX_PATH="$(python -c 'import torch;print(torch.utils.cmake_prefix_path)')" \
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-DBUILD_SOX=ON \
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-DBUILD_KALDI=OFF \
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..
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cmake --build .

examples/libtorchaudio/speech_recognition/README.md

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# Speech Recognition with wav2vec2.0
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This example demonstarates how you can use torchaudio's I/O features and models to run speech recognition in C++ application.
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**NOTE**
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This example uses `"sox_io"` backend for loading audio, which does not work on Windows. To make it work on
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Windows, you need to replace the part of loading audio and converting it to Tensor object.
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This example demonstrates how you can use torchaudio's models to run speech recognition in a C++ application.
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## 1. Create a transcription pipeline TorchScript file
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examples/self_supervised_learning/data_modules/__init__.py

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from ._hubert_datamodule import HuBERTDataModule
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from ._wav2vec2_datamodule import Wav2Vec2DataModule
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__all__ = [
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"HuBERTDataModule",

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