automatic import of python-asteroidopeneuler20.03

3 files changed, 587 insertions, 0 deletions

diff --git a/.gitignore b/.gitignore
index e69de29..3d524d4 100644
--- a/.gitignore
+++ b/.gitignore
@@ -0,0 +1 @@
+/asteroid-0.6.0.tar.gz
diff --git a/python-asteroid.spec b/python-asteroid.spec
new file mode 100644
index 0000000..47b8b3f
--- /dev/null
+++ b/python-asteroid.spec
@@ -0,0 +1,585 @@
+%global _empty_manifest_terminate_build 0
+Name:		python-asteroid
+Version:	0.6.0
+Release:	1
+Summary:	PyTorch-based audio source separation toolkit
+License:	MIT
+URL:		https://github.com/asteroid-team/asteroid
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/7b/1b/0b679ae8c58038d06f4d48eb2391f53205c89a5063941d0cdc4f12c79cd0/asteroid-0.6.0.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-numpy
+Requires:	python3-scipy
+Requires:	python3-torch
+Requires:	python3-asteroid-filterbanks
+Requires:	python3-SoundFile
+Requires:	python3-huggingface-hub
+Requires:	python3-PyYAML
+Requires:	python3-pandas
+Requires:	python3-pytorch-lightning
+Requires:	python3-torchaudio
+Requires:	python3-pb-bss-eval
+Requires:	python3-torch-stoi
+Requires:	python3-torch-optimizer
+Requires:	python3-julius
+Requires:	python3-torchmetrics
+
+%description
+Asteroid is a Pytorch-based audio source separation toolkit
+that enables fast experimentation on common datasets.
+It comes with a source code that supports a large range
+of datasets and architectures, and a set of
+ recipes to reproduce some important papers.
+### You use Asteroid or you want to?
+Please, if you have found a bug, [open an issue][issue],
+if you solved it, [open a pull request][pr]!
+Same goes for new features, tell us what you want or help us building it!
+Don't hesitate to [join the slack][slack-invite]
+and ask questions / suggest new features there as well!
+Asteroid is intended to be a __community-based project__
+so hop on and help us!
+## Contents
+- [Installation](#installation)
+- [Tutorials](#tutorials)
+- [Running a recipe](#running-a-recipe)
+- [Available recipes](#available-recipes)
+- [Supported datasets](#supported-datasets)
+- [Pretrained models](#pretrained-models)
+- [Calls for contributions](#contributing)
+- [Citing us](#citing)
+## Installation
+([↑up to contents](#contents))
+To install Asteroid, clone the repo and install it using
+conda, pip or python :
+```bash
+# First clone and enter the repo
+git clone https://github.com/asteroid-team/asteroid
+cd asteroid
+```
+- With `pip`
+```bash
+# Install with pip in editable mode
+pip install -e .
+# Or, install with python in dev mode
+# python setup.py develop
+```
+- With conda (if you don't already have conda, see [here][miniconda].)
+```bash
+conda env create -f environment.yml
+conda activate asteroid
+```
+- Asteroid is also on PyPI, you can install the latest release with
+```bash
+pip install asteroid
+```
+## Tutorials
+([↑up to contents](#contents))
+Here is a list of notebooks showing example usage of Asteroid's features.
+- [Getting started with Asteroid](./notebooks/00_GettingStarted.ipynb)
+- [Introduction and Overview](./notebooks/01_APIOverview.ipynb)
+- [Filterbank API](./notebooks/02_Filterbank.ipynb)
+- [Permutation invariant training wrapper `PITLossWrapper`](./notebooks/03_PITLossWrapper.ipynb)
+- [Process large wav files](./notebooks/04_ProcessLargeAudioFiles.ipynb)
+## Running a recipe
+([↑up to contents](#contents))
+Running the recipes requires additional packages in most cases,
+we recommend running :
+```bash
+# from asteroid/
+pip install -r requirements.txt
+```
+Then choose the recipe you want to run and run it!
+```bash
+cd egs/wham/ConvTasNet
+. ./run.sh
+```
+More information in [egs/README.md](./egs).
+## Available recipes
+([↑up to contents](#contents))
+* [x] [ConvTasnet](./egs/wham/ConvTasNet) ([Luo et al.](https://arxiv.org/abs/1809.07454))
+* [x] [Tasnet](./egs/whamr/TasNet) ([Luo et al.](https://arxiv.org/abs/1711.00541))
+* [x] [Deep clustering](./egs/wsj0-mix/DeepClustering) ([Hershey et al.](https://arxiv.org/abs/1508.04306) and [Isik et al.](https://arxiv.org/abs/1607.02173))
+* [x] [Chimera ++](./egs/wsj0-mix/DeepClustering) ([Luo et al.](https://arxiv.org/abs/1611.06265) and [Wang et al.](https://ieeexplore.ieee.org/document/8462507))
+* [x] [DualPathRNN](./egs/wham/DPRNN) ([Luo et al.](https://arxiv.org/abs/1910.06379))
+* [x] [Two step learning](./egs/wham/TwoStep)([Tzinis et al.](https://arxiv.org/abs/1910.09804))
+* [x] [SudoRMRFNet](./asteroid/models/sudormrf.py) ([Tzinis et al.](https://arxiv.org/abs/2007.06833))
+* [x] [DPTNet](./asteroid/models/dptnet.py) ([Chen et al.](https://arxiv.org/abs/2007.13975))
+* [x] [DCCRNet](./asteroid/models/dccrnet.py) ([Hu et al.](https://arxiv.org/abs/2008.00264))
+* [x] [DCUNet](./asteroid/models/dcunet.py) ([Choi et al.](https://arxiv.org/abs/1903.03107))
+* [x] [CrossNet-Open-Unmix](./asteroid/models/x_umx.py) ([Sawata et al.](https://arxiv.org/abs/2010.04228))
+* [ ] Open-Unmix (coming) ([Stöter et al.](https://sigsep.github.io/open-unmix/))
+* [ ] Wavesplit (coming) ([Zeghidour et al.](https://arxiv.org/abs/2002.08933))
+## Supported datasets
+([↑up to contents](#contents))
+* [x] [WSJ0-2mix](./egs/wsj0-mix) / WSJ03mix ([Hershey et al.](https://arxiv.org/abs/1508.04306))
+* [x] [WHAM](./egs/wham) ([Wichern et al.](https://arxiv.org/abs/1907.01160))
+* [x] [WHAMR](./egs/whamr) ([Maciejewski et al.](https://arxiv.org/abs/1910.10279))
+* [x] [LibriMix](./egs/librimix) ([Cosentino et al.](https://arxiv.org/abs/2005.11262))
+* [x] [Microsoft DNS Challenge](./egs/dns_challenge) ([Chandan et al.](https://arxiv.org/abs/2001.08662))
+* [x] [SMS_WSJ](./egs/sms_wsj) ([Drude et al.](https://arxiv.org/abs/1910.13934))
+* [x] [MUSDB18](./asteroid/data/musdb18_dataset.py) ([Raffi et al.](https://hal.inria.fr/hal-02190845))
+* [x] [FUSS](./asteroid/data/fuss_dataset.py) ([Wisdom et al.](https://zenodo.org/record/3694384#.XmUAM-lw3g4))
+* [x] [AVSpeech](./asteroid/data/avspeech_dataset.py) ([Ephrat et al.](https://arxiv.org/abs/1804.03619))
+* [x] [Kinect-WSJ](./asteroid/data/kinect_wsj.py) ([Sivasankaran et al.](https://github.com/sunits/Reverberated_WSJ_2MIX))
+## Pretrained models
+([↑up to contents](#contents))
+See [here](./docs/source/readmes/pretrained_models.md)
+## Contributing
+([↑up to contents](#contents))
+We are always looking to expand our coverage of the source separation
+and speech enhancement research, the following is a list of
+things we're missing.
+You want to contribute? This is a great place to start!
+* Wavesplit ([Zeghidour and Grangier](https://arxiv.org/abs/2002.08933))
+* FurcaNeXt ([Shi et al.](https://arxiv.org/abs/1902.04891))
+* DeepCASA ([Liu and Want](https://arxiv.org/abs/1904.11148))
+* VCTK Test sets from [Kadioglu et al.](https://arxiv.org/pdf/2002.08688.pdf)
+* Interrupted and cascaded PIT ([Yang et al.](https://arxiv.org/abs/1910.12706))
+* ~Consistency contraints ([Wisdom et al.](https://ieeexplore.ieee.org/abstract/document/8682783))~
+* ~Backpropagable STOI and PESQ.~
+* Parametrized filterbanks from [Tukuljac et al.](https://openreview.net/forum?id=HyewT1BKvr)
+* ~End-to-End MISI ([Wang et al.](https://arxiv.org/abs/1804.10204))~
+Don't forget to read our [contributing guidelines](./CONTRIBUTING.md).
+You can also open an issue or make a PR to add something we missed in this list.
+## TensorBoard visualization
+The default logger is TensorBoard in all the recipes. From the recipe folder,
+you can run the following to visualize the logs of all your runs. You can
+also compare different systems on the same dataset by running a similar command
+from the dataset directiories.
+```bash
+# Launch tensorboard (default port is 6006)
+tensorboard --logdir exp/ --port tf_port
+```
+If your launching tensorboard remotely, you should open an ssh tunnel
+```bash
+# Open port-forwarding connection. Add -Nf option not to open remote.
+ssh -L local_port:localhost:tf_port user@ip
+```
+Then open `http://localhost:local_port/`. If both ports are the same, you can
+click on the tensorboard URL given on the remote, it's just more practical.
+## Guiding principles
+([↑up to contents](#contents))
+* __Modularity.__ Building blocks are thought and designed to be seamlessly
+plugged together. Filterbanks, encoders, maskers, decoders and losses are
+all common building blocks that can be combined in a
+flexible way to create new systems.
+* __Extensibility.__ Extending Asteroid with new features is simple.
+Add a new filterbank, separator architecture, dataset or even recipe very
+easily.
+* __Reproducibility.__ Recipes provide an easy way to reproduce
+results with data preparation, system design, training and evaluation in a
+single script. This is an essential tool for the community!
+## Citing Asteroid
+([↑up to contents](#contents))
+If you loved using Asteroid and you want to cite us, use this :
+```BibTex
+@inproceedings{Pariente2020Asteroid,
+    title={Asteroid: the {PyTorch}-based audio source separation toolkit for researchers},
+    author={Manuel Pariente and Samuele Cornell and Joris Cosentino and Sunit Sivasankaran and
+            Efthymios Tzinis and Jens Heitkaemper and Michel Olvera and Fabian-Robert Stöter and
+            Mathieu Hu and Juan M. Martín-Doñas and David Ditter and Ariel Frank and Antoine Deleforge
+            and Emmanuel Vincent},
+    year={2020},
+    booktitle={Proc. Interspeech},
+}
+```
+[comment]: <> (Badge)
+[miniconda]: https://conda.io/miniconda.html
+[codecov-badge]: https://codecov.io/gh/asteroid-team/asteroid/branch/master/graph/badge.svg
+[codecov]: https://codecov.io/gh/asteroid-team/asteroid
+[slack-badge]: https://img.shields.io/badge/slack-chat-green.svg?logo=slack
+[slack-invite]: https://join.slack.com/t/asteroid-dev/shared_invite/zt-cn9y85t3-QNHXKD1Et7qoyzu1Ji5bcA
+[comment]: <> (Others)
+[issue]: https://github.com/asteroid-team/asteroid/issues/new
+[pr]: https://github.com/asteroid-team/asteroid/compare
+
+%package -n python3-asteroid
+Summary:	PyTorch-based audio source separation toolkit
+Provides:	python-asteroid
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-asteroid
+Asteroid is a Pytorch-based audio source separation toolkit
+that enables fast experimentation on common datasets.
+It comes with a source code that supports a large range
+of datasets and architectures, and a set of
+ recipes to reproduce some important papers.
+### You use Asteroid or you want to?
+Please, if you have found a bug, [open an issue][issue],
+if you solved it, [open a pull request][pr]!
+Same goes for new features, tell us what you want or help us building it!
+Don't hesitate to [join the slack][slack-invite]
+and ask questions / suggest new features there as well!
+Asteroid is intended to be a __community-based project__
+so hop on and help us!
+## Contents
+- [Installation](#installation)
+- [Tutorials](#tutorials)
+- [Running a recipe](#running-a-recipe)
+- [Available recipes](#available-recipes)
+- [Supported datasets](#supported-datasets)
+- [Pretrained models](#pretrained-models)
+- [Calls for contributions](#contributing)
+- [Citing us](#citing)
+## Installation
+([↑up to contents](#contents))
+To install Asteroid, clone the repo and install it using
+conda, pip or python :
+```bash
+# First clone and enter the repo
+git clone https://github.com/asteroid-team/asteroid
+cd asteroid
+```
+- With `pip`
+```bash
+# Install with pip in editable mode
+pip install -e .
+# Or, install with python in dev mode
+# python setup.py develop
+```
+- With conda (if you don't already have conda, see [here][miniconda].)
+```bash
+conda env create -f environment.yml
+conda activate asteroid
+```
+- Asteroid is also on PyPI, you can install the latest release with
+```bash
+pip install asteroid
+```
+## Tutorials
+([↑up to contents](#contents))
+Here is a list of notebooks showing example usage of Asteroid's features.
+- [Getting started with Asteroid](./notebooks/00_GettingStarted.ipynb)
+- [Introduction and Overview](./notebooks/01_APIOverview.ipynb)
+- [Filterbank API](./notebooks/02_Filterbank.ipynb)
+- [Permutation invariant training wrapper `PITLossWrapper`](./notebooks/03_PITLossWrapper.ipynb)
+- [Process large wav files](./notebooks/04_ProcessLargeAudioFiles.ipynb)
+## Running a recipe
+([↑up to contents](#contents))
+Running the recipes requires additional packages in most cases,
+we recommend running :
+```bash
+# from asteroid/
+pip install -r requirements.txt
+```
+Then choose the recipe you want to run and run it!
+```bash
+cd egs/wham/ConvTasNet
+. ./run.sh
+```
+More information in [egs/README.md](./egs).
+## Available recipes
+([↑up to contents](#contents))
+* [x] [ConvTasnet](./egs/wham/ConvTasNet) ([Luo et al.](https://arxiv.org/abs/1809.07454))
+* [x] [Tasnet](./egs/whamr/TasNet) ([Luo et al.](https://arxiv.org/abs/1711.00541))
+* [x] [Deep clustering](./egs/wsj0-mix/DeepClustering) ([Hershey et al.](https://arxiv.org/abs/1508.04306) and [Isik et al.](https://arxiv.org/abs/1607.02173))
+* [x] [Chimera ++](./egs/wsj0-mix/DeepClustering) ([Luo et al.](https://arxiv.org/abs/1611.06265) and [Wang et al.](https://ieeexplore.ieee.org/document/8462507))
+* [x] [DualPathRNN](./egs/wham/DPRNN) ([Luo et al.](https://arxiv.org/abs/1910.06379))
+* [x] [Two step learning](./egs/wham/TwoStep)([Tzinis et al.](https://arxiv.org/abs/1910.09804))
+* [x] [SudoRMRFNet](./asteroid/models/sudormrf.py) ([Tzinis et al.](https://arxiv.org/abs/2007.06833))
+* [x] [DPTNet](./asteroid/models/dptnet.py) ([Chen et al.](https://arxiv.org/abs/2007.13975))
+* [x] [DCCRNet](./asteroid/models/dccrnet.py) ([Hu et al.](https://arxiv.org/abs/2008.00264))
+* [x] [DCUNet](./asteroid/models/dcunet.py) ([Choi et al.](https://arxiv.org/abs/1903.03107))
+* [x] [CrossNet-Open-Unmix](./asteroid/models/x_umx.py) ([Sawata et al.](https://arxiv.org/abs/2010.04228))
+* [ ] Open-Unmix (coming) ([Stöter et al.](https://sigsep.github.io/open-unmix/))
+* [ ] Wavesplit (coming) ([Zeghidour et al.](https://arxiv.org/abs/2002.08933))
+## Supported datasets
+([↑up to contents](#contents))
+* [x] [WSJ0-2mix](./egs/wsj0-mix) / WSJ03mix ([Hershey et al.](https://arxiv.org/abs/1508.04306))
+* [x] [WHAM](./egs/wham) ([Wichern et al.](https://arxiv.org/abs/1907.01160))
+* [x] [WHAMR](./egs/whamr) ([Maciejewski et al.](https://arxiv.org/abs/1910.10279))
+* [x] [LibriMix](./egs/librimix) ([Cosentino et al.](https://arxiv.org/abs/2005.11262))
+* [x] [Microsoft DNS Challenge](./egs/dns_challenge) ([Chandan et al.](https://arxiv.org/abs/2001.08662))
+* [x] [SMS_WSJ](./egs/sms_wsj) ([Drude et al.](https://arxiv.org/abs/1910.13934))
+* [x] [MUSDB18](./asteroid/data/musdb18_dataset.py) ([Raffi et al.](https://hal.inria.fr/hal-02190845))
+* [x] [FUSS](./asteroid/data/fuss_dataset.py) ([Wisdom et al.](https://zenodo.org/record/3694384#.XmUAM-lw3g4))
+* [x] [AVSpeech](./asteroid/data/avspeech_dataset.py) ([Ephrat et al.](https://arxiv.org/abs/1804.03619))
+* [x] [Kinect-WSJ](./asteroid/data/kinect_wsj.py) ([Sivasankaran et al.](https://github.com/sunits/Reverberated_WSJ_2MIX))
+## Pretrained models
+([↑up to contents](#contents))
+See [here](./docs/source/readmes/pretrained_models.md)
+## Contributing
+([↑up to contents](#contents))
+We are always looking to expand our coverage of the source separation
+and speech enhancement research, the following is a list of
+things we're missing.
+You want to contribute? This is a great place to start!
+* Wavesplit ([Zeghidour and Grangier](https://arxiv.org/abs/2002.08933))
+* FurcaNeXt ([Shi et al.](https://arxiv.org/abs/1902.04891))
+* DeepCASA ([Liu and Want](https://arxiv.org/abs/1904.11148))
+* VCTK Test sets from [Kadioglu et al.](https://arxiv.org/pdf/2002.08688.pdf)
+* Interrupted and cascaded PIT ([Yang et al.](https://arxiv.org/abs/1910.12706))
+* ~Consistency contraints ([Wisdom et al.](https://ieeexplore.ieee.org/abstract/document/8682783))~
+* ~Backpropagable STOI and PESQ.~
+* Parametrized filterbanks from [Tukuljac et al.](https://openreview.net/forum?id=HyewT1BKvr)
+* ~End-to-End MISI ([Wang et al.](https://arxiv.org/abs/1804.10204))~
+Don't forget to read our [contributing guidelines](./CONTRIBUTING.md).
+You can also open an issue or make a PR to add something we missed in this list.
+## TensorBoard visualization
+The default logger is TensorBoard in all the recipes. From the recipe folder,
+you can run the following to visualize the logs of all your runs. You can
+also compare different systems on the same dataset by running a similar command
+from the dataset directiories.
+```bash
+# Launch tensorboard (default port is 6006)
+tensorboard --logdir exp/ --port tf_port
+```
+If your launching tensorboard remotely, you should open an ssh tunnel
+```bash
+# Open port-forwarding connection. Add -Nf option not to open remote.
+ssh -L local_port:localhost:tf_port user@ip
+```
+Then open `http://localhost:local_port/`. If both ports are the same, you can
+click on the tensorboard URL given on the remote, it's just more practical.
+## Guiding principles
+([↑up to contents](#contents))
+* __Modularity.__ Building blocks are thought and designed to be seamlessly
+plugged together. Filterbanks, encoders, maskers, decoders and losses are
+all common building blocks that can be combined in a
+flexible way to create new systems.
+* __Extensibility.__ Extending Asteroid with new features is simple.
+Add a new filterbank, separator architecture, dataset or even recipe very
+easily.
+* __Reproducibility.__ Recipes provide an easy way to reproduce
+results with data preparation, system design, training and evaluation in a
+single script. This is an essential tool for the community!
+## Citing Asteroid
+([↑up to contents](#contents))
+If you loved using Asteroid and you want to cite us, use this :
+```BibTex
+@inproceedings{Pariente2020Asteroid,
+    title={Asteroid: the {PyTorch}-based audio source separation toolkit for researchers},
+    author={Manuel Pariente and Samuele Cornell and Joris Cosentino and Sunit Sivasankaran and
+            Efthymios Tzinis and Jens Heitkaemper and Michel Olvera and Fabian-Robert Stöter and
+            Mathieu Hu and Juan M. Martín-Doñas and David Ditter and Ariel Frank and Antoine Deleforge
+            and Emmanuel Vincent},
+    year={2020},
+    booktitle={Proc. Interspeech},
+}
+```
+[comment]: <> (Badge)
+[miniconda]: https://conda.io/miniconda.html
+[codecov-badge]: https://codecov.io/gh/asteroid-team/asteroid/branch/master/graph/badge.svg
+[codecov]: https://codecov.io/gh/asteroid-team/asteroid
+[slack-badge]: https://img.shields.io/badge/slack-chat-green.svg?logo=slack
+[slack-invite]: https://join.slack.com/t/asteroid-dev/shared_invite/zt-cn9y85t3-QNHXKD1Et7qoyzu1Ji5bcA
+[comment]: <> (Others)
+[issue]: https://github.com/asteroid-team/asteroid/issues/new
+[pr]: https://github.com/asteroid-team/asteroid/compare
+
+%package help
+Summary:	Development documents and examples for asteroid
+Provides:	python3-asteroid-doc
+%description help
+Asteroid is a Pytorch-based audio source separation toolkit
+that enables fast experimentation on common datasets.
+It comes with a source code that supports a large range
+of datasets and architectures, and a set of
+ recipes to reproduce some important papers.
+### You use Asteroid or you want to?
+Please, if you have found a bug, [open an issue][issue],
+if you solved it, [open a pull request][pr]!
+Same goes for new features, tell us what you want or help us building it!
+Don't hesitate to [join the slack][slack-invite]
+and ask questions / suggest new features there as well!
+Asteroid is intended to be a __community-based project__
+so hop on and help us!
+## Contents
+- [Installation](#installation)
+- [Tutorials](#tutorials)
+- [Running a recipe](#running-a-recipe)
+- [Available recipes](#available-recipes)
+- [Supported datasets](#supported-datasets)
+- [Pretrained models](#pretrained-models)
+- [Calls for contributions](#contributing)
+- [Citing us](#citing)
+## Installation
+([↑up to contents](#contents))
+To install Asteroid, clone the repo and install it using
+conda, pip or python :
+```bash
+# First clone and enter the repo
+git clone https://github.com/asteroid-team/asteroid
+cd asteroid
+```
+- With `pip`
+```bash
+# Install with pip in editable mode
+pip install -e .
+# Or, install with python in dev mode
+# python setup.py develop
+```
+- With conda (if you don't already have conda, see [here][miniconda].)
+```bash
+conda env create -f environment.yml
+conda activate asteroid
+```
+- Asteroid is also on PyPI, you can install the latest release with
+```bash
+pip install asteroid
+```
+## Tutorials
+([↑up to contents](#contents))
+Here is a list of notebooks showing example usage of Asteroid's features.
+- [Getting started with Asteroid](./notebooks/00_GettingStarted.ipynb)
+- [Introduction and Overview](./notebooks/01_APIOverview.ipynb)
+- [Filterbank API](./notebooks/02_Filterbank.ipynb)
+- [Permutation invariant training wrapper `PITLossWrapper`](./notebooks/03_PITLossWrapper.ipynb)
+- [Process large wav files](./notebooks/04_ProcessLargeAudioFiles.ipynb)
+## Running a recipe
+([↑up to contents](#contents))
+Running the recipes requires additional packages in most cases,
+we recommend running :
+```bash
+# from asteroid/
+pip install -r requirements.txt
+```
+Then choose the recipe you want to run and run it!
+```bash
+cd egs/wham/ConvTasNet
+. ./run.sh
+```
+More information in [egs/README.md](./egs).
+## Available recipes
+([↑up to contents](#contents))
+* [x] [ConvTasnet](./egs/wham/ConvTasNet) ([Luo et al.](https://arxiv.org/abs/1809.07454))
+* [x] [Tasnet](./egs/whamr/TasNet) ([Luo et al.](https://arxiv.org/abs/1711.00541))
+* [x] [Deep clustering](./egs/wsj0-mix/DeepClustering) ([Hershey et al.](https://arxiv.org/abs/1508.04306) and [Isik et al.](https://arxiv.org/abs/1607.02173))
+* [x] [Chimera ++](./egs/wsj0-mix/DeepClustering) ([Luo et al.](https://arxiv.org/abs/1611.06265) and [Wang et al.](https://ieeexplore.ieee.org/document/8462507))
+* [x] [DualPathRNN](./egs/wham/DPRNN) ([Luo et al.](https://arxiv.org/abs/1910.06379))
+* [x] [Two step learning](./egs/wham/TwoStep)([Tzinis et al.](https://arxiv.org/abs/1910.09804))
+* [x] [SudoRMRFNet](./asteroid/models/sudormrf.py) ([Tzinis et al.](https://arxiv.org/abs/2007.06833))
+* [x] [DPTNet](./asteroid/models/dptnet.py) ([Chen et al.](https://arxiv.org/abs/2007.13975))
+* [x] [DCCRNet](./asteroid/models/dccrnet.py) ([Hu et al.](https://arxiv.org/abs/2008.00264))
+* [x] [DCUNet](./asteroid/models/dcunet.py) ([Choi et al.](https://arxiv.org/abs/1903.03107))
+* [x] [CrossNet-Open-Unmix](./asteroid/models/x_umx.py) ([Sawata et al.](https://arxiv.org/abs/2010.04228))
+* [ ] Open-Unmix (coming) ([Stöter et al.](https://sigsep.github.io/open-unmix/))
+* [ ] Wavesplit (coming) ([Zeghidour et al.](https://arxiv.org/abs/2002.08933))
+## Supported datasets
+([↑up to contents](#contents))
+* [x] [WSJ0-2mix](./egs/wsj0-mix) / WSJ03mix ([Hershey et al.](https://arxiv.org/abs/1508.04306))
+* [x] [WHAM](./egs/wham) ([Wichern et al.](https://arxiv.org/abs/1907.01160))
+* [x] [WHAMR](./egs/whamr) ([Maciejewski et al.](https://arxiv.org/abs/1910.10279))
+* [x] [LibriMix](./egs/librimix) ([Cosentino et al.](https://arxiv.org/abs/2005.11262))
+* [x] [Microsoft DNS Challenge](./egs/dns_challenge) ([Chandan et al.](https://arxiv.org/abs/2001.08662))
+* [x] [SMS_WSJ](./egs/sms_wsj) ([Drude et al.](https://arxiv.org/abs/1910.13934))
+* [x] [MUSDB18](./asteroid/data/musdb18_dataset.py) ([Raffi et al.](https://hal.inria.fr/hal-02190845))
+* [x] [FUSS](./asteroid/data/fuss_dataset.py) ([Wisdom et al.](https://zenodo.org/record/3694384#.XmUAM-lw3g4))
+* [x] [AVSpeech](./asteroid/data/avspeech_dataset.py) ([Ephrat et al.](https://arxiv.org/abs/1804.03619))
+* [x] [Kinect-WSJ](./asteroid/data/kinect_wsj.py) ([Sivasankaran et al.](https://github.com/sunits/Reverberated_WSJ_2MIX))
+## Pretrained models
+([↑up to contents](#contents))
+See [here](./docs/source/readmes/pretrained_models.md)
+## Contributing
+([↑up to contents](#contents))
+We are always looking to expand our coverage of the source separation
+and speech enhancement research, the following is a list of
+things we're missing.
+You want to contribute? This is a great place to start!
+* Wavesplit ([Zeghidour and Grangier](https://arxiv.org/abs/2002.08933))
+* FurcaNeXt ([Shi et al.](https://arxiv.org/abs/1902.04891))
+* DeepCASA ([Liu and Want](https://arxiv.org/abs/1904.11148))
+* VCTK Test sets from [Kadioglu et al.](https://arxiv.org/pdf/2002.08688.pdf)
+* Interrupted and cascaded PIT ([Yang et al.](https://arxiv.org/abs/1910.12706))
+* ~Consistency contraints ([Wisdom et al.](https://ieeexplore.ieee.org/abstract/document/8682783))~
+* ~Backpropagable STOI and PESQ.~
+* Parametrized filterbanks from [Tukuljac et al.](https://openreview.net/forum?id=HyewT1BKvr)
+* ~End-to-End MISI ([Wang et al.](https://arxiv.org/abs/1804.10204))~
+Don't forget to read our [contributing guidelines](./CONTRIBUTING.md).
+You can also open an issue or make a PR to add something we missed in this list.
+## TensorBoard visualization
+The default logger is TensorBoard in all the recipes. From the recipe folder,
+you can run the following to visualize the logs of all your runs. You can
+also compare different systems on the same dataset by running a similar command
+from the dataset directiories.
+```bash
+# Launch tensorboard (default port is 6006)
+tensorboard --logdir exp/ --port tf_port
+```
+If your launching tensorboard remotely, you should open an ssh tunnel
+```bash
+# Open port-forwarding connection. Add -Nf option not to open remote.
+ssh -L local_port:localhost:tf_port user@ip
+```
+Then open `http://localhost:local_port/`. If both ports are the same, you can
+click on the tensorboard URL given on the remote, it's just more practical.
+## Guiding principles
+([↑up to contents](#contents))
+* __Modularity.__ Building blocks are thought and designed to be seamlessly
+plugged together. Filterbanks, encoders, maskers, decoders and losses are
+all common building blocks that can be combined in a
+flexible way to create new systems.
+* __Extensibility.__ Extending Asteroid with new features is simple.
+Add a new filterbank, separator architecture, dataset or even recipe very
+easily.
+* __Reproducibility.__ Recipes provide an easy way to reproduce
+results with data preparation, system design, training and evaluation in a
+single script. This is an essential tool for the community!
+## Citing Asteroid
+([↑up to contents](#contents))
+If you loved using Asteroid and you want to cite us, use this :
+```BibTex
+@inproceedings{Pariente2020Asteroid,
+    title={Asteroid: the {PyTorch}-based audio source separation toolkit for researchers},
+    author={Manuel Pariente and Samuele Cornell and Joris Cosentino and Sunit Sivasankaran and
+            Efthymios Tzinis and Jens Heitkaemper and Michel Olvera and Fabian-Robert Stöter and
+            Mathieu Hu and Juan M. Martín-Doñas and David Ditter and Ariel Frank and Antoine Deleforge
+            and Emmanuel Vincent},
+    year={2020},
+    booktitle={Proc. Interspeech},
+}
+```
+[comment]: <> (Badge)
+[miniconda]: https://conda.io/miniconda.html
+[codecov-badge]: https://codecov.io/gh/asteroid-team/asteroid/branch/master/graph/badge.svg
+[codecov]: https://codecov.io/gh/asteroid-team/asteroid
+[slack-badge]: https://img.shields.io/badge/slack-chat-green.svg?logo=slack
+[slack-invite]: https://join.slack.com/t/asteroid-dev/shared_invite/zt-cn9y85t3-QNHXKD1Et7qoyzu1Ji5bcA
+[comment]: <> (Others)
+[issue]: https://github.com/asteroid-team/asteroid/issues/new
+[pr]: https://github.com/asteroid-team/asteroid/compare
+
+%prep
+%autosetup -n asteroid-0.6.0
+
+%build
+%py3_build
+
+%install
+%py3_install
+install -d -m755 %{buildroot}/%{_pkgdocdir}
+if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
+if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
+if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
+if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
+pushd %{buildroot}
+if [ -d usr/lib ]; then
+	find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/lib64 ]; then
+	find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/bin ]; then
+	find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/sbin ]; then
+	find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+touch doclist.lst
+if [ -d usr/share/man ]; then
+	find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
+fi
+popd
+mv %{buildroot}/filelist.lst .
+mv %{buildroot}/doclist.lst .
+
+%files -n python3-asteroid -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 0.6.0-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..72ac197
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+1ea4539df59c4c17091e1ce1d9422017  asteroid-0.6.0.tar.gz