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Deep Learning on Flink aims to integrate Flink and deep learning frameworks (e.g. TensorFlow, PyTorch, etc) to enable distributed deep learning training and inference on a Flink cluster.
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# Deep Learning on Flink Deep Learning on Flink aims to integrate Flink and deep learning frameworks (e.g. TensorFlow, PyTorch, etc.) to enable distributed deep learning training and inference on a Flink cluster. It runs the deep learning tasks inside a Flink operator so that Flink can help establish a distributed environment, manage the resource, read/write the data with the rich connectors in Flink and handle the failures. Currently, Deep Learning on Flink supports TensorFlow. ## Supported Operating System Deep Learning on Flink is tested and supported on the following 64-bit systems: - Ubuntu 18.04 - macOS 10.15 ## Support Framework Version - TensorFlow: 1.15.x & 2.4.x - PyTorch: 1.11.x - Flink: 1.14.x ## Getting Started Deep learning on Flink currently works with Tensorflow and PyTorch. You can see the following pages for the usage and examples. - [DL on Flink with Tensorflow](doc/tensorflow-index.md) - [DL on Flink with PyTorch](doc/pytorch-index.md) ## Build From Source **Requirements** - python: 3.7 - cmake >= 3.6 - java 1.8 - maven >=3.3.0 Deep Learning on Flink requires Java and Python works together. Thus, we need to build for both Java and Python. ### Initializing Submodules before Building Deep Learning on Flink from Source Please use the following command to initialize submodules before building from source. ```bash git submodule update --init --recursive ``` ### Build Java ```shell mvn -DskipTests clean install ``` After finish, you can find the target distribution in the `dl-on-flink-dist/target` folder. ### Build Python #### Install from Source You can run the following commands to install the Python packages from source ```sh # Install dl-on-flink-framework first pip install dl-on-flink-framework/python # Note that you should only install one of the following as they require # different versions of Tensorflow # For tensorflow 1.15.x pip install dl-on-flink-tensorflow/python # For tensorflow 2.4.x pip install dl-on-flink-tensorflow-2.x/python ``` #### Build wheels We provide a script to build wheels for Python packages, you can run the following command. ```sh bash tools/build_wheel.sh ``` After finish, you can find the wheels at `tools/dist`. Then you can install the python package with the wheels. ```sh pip install tools/dist/<wheel> ``` # For More Information [Design document](doc/design.md) # License [Apache License 2.0](LICENSE)
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Hongbo Miao · Archer Aviation | www.archer.com · United States
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:ca2251530a15567b, topic:deep-learning, topic:pytorch, topic:tensorflow