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Haskell bindings for TensorFlow
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fkm3 630850c2d2 Add TensorFlow.Core module to start formalizing the exposed API (#17)
* Add TensorFlow.Core module to start formalizing the exposed API

* Refer to ops packages instead of modules
2016-11-10 09:47:41 -08:00
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 Add TensorFlow.Core module to start formalizing the exposed API (#17) 2016-11-10 09:47:41 -08:00
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 Fixed CI and added indicator. (#15) 2016-10-28 18:08:32 -07:00
tensorflow-opgen Support ResourceHandle. (#18) 2016-11-08 16:48:41 -08:00
tensorflow-ops genericLength is too generic. 2016-11-09 14:20:26 -08:00
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 Support ResourceHandle. (#18) 2016-11-08 16:48:41 -08:00
tools Haddock (#3) 2016-10-25 12:43:06 -07:00
.gitignore Initial commit 2016-10-24 19:26:42 +00:00
.gitmodules Initial commit 2016-10-24 19:26:42 +00:00
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

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.