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A Redis module for serving tensors and executing deep learning graphs
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RedisAI

A Redis module for serving tensors and executing deep learning models. Expect changes in the API and internals.

Cloning

If you want to run examples, make sure you have git-lfs installed when you clone.

Quickstart

  1. Docker
  2. Build

Docker

To quickly tryout RedisAI, launch an instance using docker:

docker run -p 6379:6379 -it --rm redisai/redisai

Give it a try

On the client, load the model

redis-cli -x AI.MODELSET foo TF CPU INPUTS a b OUTPUTS c < examples/models/graph.pb

Then create the input tensors, run the computation graph and get the output tensor (see load_model.sh). Note the signatures:

  • AI.TENSORSET tensor_key data_type dim1..dimN [BLOB data | VALUES val1..valN]
  • AI.MODELRUN graph_key INPUTS input_key1 ... OUTPUTS output_key1 ...
redis-cli
> AI.TENSORSET bar FLOAT 2 VALUES 2 3
> AI.TENSORSET baz FLOAT 2 VALUES 2 3
> AI.MODELRUN foo INPUTS bar baz OUTPUTS jez
> AI.TENSORGET jez VALUES
1) FLOAT
2) 1) (integer) 2
3) 1) "4"
   2) "9"

Building

This will checkout and build and download the libraries for the backends (TensorFlow and PyTorch) for your platform.

bash get_deps.sh

Once the dependencies are downloaded, build the module itself. Note that CMake 3.0 or higher is required.

mkdir build
cd build
cmake -DDEPS_PATH=../deps/install ..
make
cd ..

Running the server

You will need a redis-server version 4.0.9 or greater. This should be available in most recent distributions:

redis-server --version
Redis server v=4.0.9 sha=00000000:0 malloc=libc bits=64 build=c49f4faf7c3c647a

To start redis with the RedisAI module loaded:

redis-server --loadmodule build/redisai.so

Client libraries

Some languages have client libraries that provide support for RedisAI's commands:

Project Language License Author URL
JRedisAI Java BSD-3 RedisLabs Github
redisai-py Python BSD-3 RedisLabs Github

Backend Dependancy

RedisAI currently supports PyTorch (libtorch) and Tensorflow (libtensorflow) as backends. We are also building support for ONNXRuntime backend soon. This section shows the version map between RedisAI and supported backends. This extremely important since the serialization mechanism of one version might not match with another. For making sure your model will work with a given RedisAI version, check with the backend documentation about incompatible features between the version of your backend and the version RedisAI is built with.

RedisAI PyTorch TensorFlow ONNXRuntime
0.1.0 1.0.1 1.12.0 Not Yet

Documentation

Read the docs at redisai.io.

Mailing List

RedisAI Google group

License

Redis Source Available License Agreement - see LICENSE

Copyright 2019, Orobix Srl & Redis Labs Ltd

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