flink-tensorflow
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FlinkML
flink-tensorflow - TensorFlow support for Apache Flink
- Flink to 1.2.1 - Tensorflow to 1.2.0-rc1 - Added Installation instructions in SBT and Maven in readme.
Add saved model for MNIST_dense that includes a prediction signature. Create a PredictionMethod to use the prediction signature. Create a test for the saved model and prediction signature.
Implement out-of-box interoperability with TF Serving models. Given a model that works in TF Serving, make it easy to use directly in a Flink program, e.g.: - implementations of "predict"...
Make it possible to define TF graphs from scratch, in addition to existing support for using externally-developed models. Because the object model of TensorFlow graphs is extensive and ever-growing, we...
The library today has numerous layers of functionality that could benefit from refactoring, to reduce dependencies and clarify concepts. The conceptual layering (from bottom up): 1. Scala language bindings a....
Make it possible to use TensorFlow models as elements of a FlinkML pipeline (as described [here](https://ci.apache.org/projects/flink/flink-docs-release-1.3/dev/libs/ml/pipelines.html)). Possible features include: - Use TF models as FlinkML transformers and predictors - Support...
Let's prove that serving TF models in-process has a performance advantage over making RPC calls to TF Serving.
- Integrate graph state into Flink operator state - Support checkpointing - Support keyed streams