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Haskell bindings for TensorFlow
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Greg Steuck e511f49828 Create a separate TensorProtoLens class. 
Only a handful of types had sensible tensorVal implementations.
This is now evident in type signatures at the expense of them
being more verbose.
 		2016-11-02 16:16:16 -07:00
ci_build Remove unnecessary submodule commands. 2016-10-31 09:25:12 -07:00
docker Integration test (#14) 2016-10-28 16:14:26 -07:00
docs/haddock Regen haddock. (#16) 2016-10-31 14:22:48 -07:00
google-shim Initial commit 2016-10-24 19:26:42 +00:00
tensorflow Create a separate TensorProtoLens class. 2016-11-02 16:16:16 -07:00
tensorflow-core-ops Blacklist the SaveV2 and RestoreV2 ops which need Tensor lists. (#7) 2016-10-25 23:19:19 -07:00
tensorflow-mnist Misc MNIST example cleanup (#9) 2016-10-26 11:14:38 -07:00
tensorflow-mnist-input-data Initial commit 2016-10-24 19:26:42 +00:00
tensorflow-nn Create a separate TensorProtoLens class. 2016-11-02 16:16:16 -07:00
tensorflow-opgen Initial commit 2016-10-24 19:26:42 +00:00
tensorflow-ops Create a separate TensorProtoLens class. 2016-11-02 16:16:16 -07:00
tensorflow-proto Initial commit 2016-10-24 19:26:42 +00:00
tensorflow-queue Initial commit 2016-10-24 19:26:42 +00:00
third_party Initial commit 2016-10-24 19:26:42 +00:00
tools Haddock (#3) 2016-10-25 12:43:06 -07:00
.gitignore Initial commit 2016-10-24 19:26:42 +00:00
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CONTRIBUTING.md Initial commit 2016-10-24 19:26:42 +00:00
LICENSE Initial commit 2016-10-24 19:26:42 +00:00
README.md Fixed CI and added indicator. (#15) 2016-10-28 18:08:32 -07:00
stack.yaml Starting NN library (#11) 2016-10-27 18:05:27 -07:00

README.md

Build Status

The tensorflow-haskell package provides Haskell bindings to TensorFlow.

This is not an official Google product.

Instructions

Build with Docker on Linux

As an expedient we use docker for building. Once you have docker working, the following commands will compile and run the tests.

git clone --recursive https://github.com/tensorflow/haskell.git tensorflow-haskell
cd tensorflow-haskell
IMAGE_NAME=tensorflow/haskell:v0
docker build -t $IMAGE_NAME docker
# TODO: move the setup step to the docker script.
stack --docker --docker-image=$IMAGE_NAME setup
stack --docker --docker-image=$IMAGE_NAME test

There is also a demo application:

cd tensorflow-mnist
stack --docker --docker-image=$IMAGE_NAME build --exec Main

Build on Mac OS X

The following instructions were verified with Mac OS X El Capitan.

  • Install dependencies via Homebrew:

      brew install swig
  brew install bazel

  • Build the TensorFlow library and install it on your machine:

      cd third_party/tensorflow
  ./configure  # Choose the defaults when prompted
  bazel build -c opt tensorflow:libtensorflow_c.so
  install bazel-bin/tensorflow/libtensorflow_c.so /usr/local/lib
  cd ../..

  • Run stack:

      stack test

Note: you may need to upgrade your version of Clang if you get an error like the following:

tensorflow/core/ops/ctc_ops.cc:60:7: error: return type 'tensorflow::Status' must match previous return type 'const ::tensorflow::Status' when lambda expression has unspecified explicit return type
    return Status::OK();

In that case you can just upgrade XCode and then run gcc --version to get the new version of the compiler.