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Haskell bindings for TensorFlow
1539783ee5
Also removes all the ghc-8-specific logic in the .cabal files. ghc-8 has issues with deeply nested tuples of constraints. We can work around it by: - Changing TensorTypes to a regular class. This required FlexibleContexts. (But we'll probably need it anyway when we support heterogeneous tensor lists.) - Specializing NoneOf for long type lists. For more details, see: https://ghc.haskell.org/trac/ghc/ticket/12175. Also added 'directory' to tensorflow-core-ops' dependencies since it's used in the Setup script. One more step towards fixing #38. |
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ci_build | ||
docker | ||
docs/haddock | ||
google-shim | ||
tensorflow | ||
tensorflow-core-ops | ||
tensorflow-mnist | ||
tensorflow-mnist-input-data | ||
tensorflow-nn | ||
tensorflow-opgen | ||
tensorflow-ops | ||
tensorflow-proto | ||
tensorflow-queue | ||
tensorflow-test | ||
third_party | ||
tools | ||
.gitignore | ||
.gitmodules | ||
CONTRIBUTING.md | ||
LICENSE | ||
README.md | ||
stack.yaml |
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/libtensorflow_c.dylib install_name_tool -id libtensorflow_c.dylib /usr/local/lib/libtensorflow_c.dylib 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.