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# Oneflow **OneFlow is a performance-centered and open-source platform for machine learning.**
### Install OneFlow - [Install OneFlow](#install-oneflow)
- [System Requirements](#system-requirements)
#### System Requirements to Run OneFlow - [Install with Pip Package](#install-with-pip-package)
- [Build from Source](#build-from-source)
- [Troubleshooting](#troubleshooting)
- [Advanced features](#advanced-features)
- [Getting Started](#getting-started)
- [Documentation](#documentation)
- [Usage & Design Docs](#usage--design-docs)
- [API Reference](#api-reference)
- [Model Zoo and Benchmark](#model-zoo-and-benchmark)
- [CNNs(ResNet-50, VGG-16, Inception-V3, AlexNet)](#cnnsresnet-50-vgg-16-inception-v3-alexnet)
- [Wide&Deep](#widedeep)
- [BERT](#bert)
- [Communication](#communication)
- [Contributing](#contributing)
- [The Team](#the-team)
- [License](#license)
## Install OneFlow
### System Requirements
- Python >= 3.5 - Python >= 3.5
- Nvidia Linux x86_64 driver version >= 440.33 - Nvidia Linux x86_64 driver version >= 440.33
#### Install Pip package ### Install with Pip Package
- To install latest release of OneFlow with CUDA support: - To install latest release of OneFlow with CUDA support:
...@@ -36,7 +55,7 @@ ...@@ -36,7 +55,7 @@
- Releases are built with G++/GCC 4.8.5, cuDNN 7 and MKL 2020.0-088. - Releases are built with G++/GCC 4.8.5, cuDNN 7 and MKL 2020.0-088.
### Build OneFlow from Source ### Build from Source
1. #### System Requirements to Build OneFlow 1. #### System Requirements to Build OneFlow
...@@ -94,8 +113,60 @@ ...@@ -94,8 +113,60 @@
Please refer to [troubleshooting](docs/source/troubleshooting.md) for common issues you might encounter when compiling and running OneFlow. Please refer to [troubleshooting](docs/source/troubleshooting.md) for common issues you might encounter when compiling and running OneFlow.
### Advanced Features ### Advanced features
- #### XRT - #### XRT
You can check this [doc](oneflow/xrt/README.md) to obtain more details about how to use XLA and TensorRT with OneFlow. You can check this [doc](oneflow/xrt/README.md) to obtain more details about how to use XLA and TensorRT with OneFlow.
## Getting Started
3 minutes to run MNIST.
1. Clone the demo code from OneFlow documentation
```
git clone https://github.com/Oneflow-Inc/oneflow-documentation.git
cd oneflow-documentation/cn/docs/code/quick_start/
```
2. Run it in Python
```
python mlp_mnist.py
```
3. Oneflow is running and you got the training loss
```
2.7290366
0.81281316
0.50629824
0.35949975
0.35245502
...
```
More info on this demo, please refer to [doc on quick start](http://docs.oneflow.org/quick_start/quickstart_in_3_min.html).
## Documentation
#### Usage & Design Docs
* [link](http://docs.oneflow.org/)
#### API Reference
* [link](https://oneflow-api.readthedocs.io/en/latest/)
## Model Zoo and Benchmark
* [link](https://github.com/Oneflow-Inc/OneFlow-Benchmark)
### CNNs(ResNet-50, VGG-16, Inception-V3, AlexNet)
* [CNNs](https://github.com/Oneflow-Inc/OneFlow-Benchmark/tree/of_develop_py3/Classification/cnns)
### Wide&Deep
* [OneFlow-WDL](https://github.com/Oneflow-Inc/OneFlow-Benchmark/tree/of_develop_py3/ClickThroughRate/WideDeepLearning)
### BERT
* [Bert](https://github.com/Oneflow-Inc/OneFlow-Benchmark/tree/of_develop_py3/LanguageModeling/BERT)
## Communication
* Github issues : any install, bug, feature issues.
* [www.oneflow.org](http://www.oneflow.org) : brand related information.
## Contributing
* [link](http://docs.oneflow.org/contribute/intro.html)
## The Team
OneFlow was originally developed by [OneFlow Inc](http://www.oneflow.org) and [Zhejiang Lab](http://www.zhejianglab.com/).
## License
[Apache License 2.0](LICENSE)
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