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# TensorFlow in Go
Construct and execute TensorFlow graphs in Go.
[](https://godoc.org/github.com/tensorflow/tensorflow/tensorflow/go)
> *WARNING*: The API defined in this package is not stable and can change
> without notice. The same goes for the awkward package path
> (`github.com/tensorflow/tensorflow/tensorflow/go`).
## Quickstart
1. Download and extract the TensorFlow C library, preferably into `/usr/local`.
GPU-enabled versions require CUDA 8.0 and cuDNN 5.1. For other versions, the
TensorFlow C library will have to be built from source (see below).
- Linux:
[CPU-only](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-linux-x86_64-1.0.0.tar.gz),
[GPU-enabled](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-gpu-linux-x86_64-1.0.0.tar.gz)
- OS X
[CPU-only](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-darwin-x86_64-1.0.0.tar.gz),
[GPU-enabled](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-gpu-darwin-x86_64-1.0.0.tar.gz)
The following shell snippet downloads and extracts into `/usr/local`:
```sh
TF_TYPE="cpu" # Set to "gpu" for GPU support
curl -L \
"https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-${TF_TYPE}-$(go env GOOS)-x86_64-1.0.0.tar.gz" |
sudo tar -C /usr/local -xz
```
2. `go get` this package (and run tests):
```sh
go get github.com/tensorflow/tensorflow/tensorflow/go
go test github.com/tensorflow/tensorflow/tensorflow/go
```
3. Done!
### Installing into locations other than `/usr/local`
The TensorFlow C library (`libtensorflow.so`) needs to be available at build
time (e.g., `go build`) and run time (`go test` or executing binaries). If the
library has not been extracted into `/usr/local`, then it needs to be made
available through the `LIBRARY_PATH` environment variable at build time and the
`LD_LIBRARY_PATH` environment variable (`DYLD_LIBRARY_PATH` on OS X) at run
time.
For example, if the TensorFlow C library was extracted into `/dir`, then:
```sh
export LIBRARY_PATH=/dir/lib
export LD_LIBRARY_PATH=/dir/lib # For Linux
export DYLD_LIBRARY_PATH=/dir/lib # For OS X
```
## Building the TensorFlow C library from source
If the "Quickstart" instructions above do not work (perhaps the release archives
are not available for your operating system or architecture, or you're using a
different version of CUDA/cuDNN), then the TensorFlow C library must be built
from source.
### Prerequisites
- [bazel](https://www.bazel.build/versions/master/docs/install.html)
- Environment to build TensorFlow from source code
([Linux](https://www.tensorflow.org/versions/master/get_started/os_setup.html#prepare-environment-for-linux)
or [OS
X](https://www.tensorflow.org/versions/master/get_started/os_setup.html#prepare-environment-for-mac-os-x)).
If you don't need GPU support, then try the following: `sh # Linux sudo
apt-get install python swig python-numpy # OS X with homebrew brew install
swig`
### Build
1. Download the source code
```sh
go get -d github.com/tensorflow/tensorflow/tensorflow/go
```
2. Build the TensorFlow C library:
```sh
cd ${GOPATH}/src/github.com/tensorflow/tensorflow
./configure
bazel build --config opt //tensorflow:libtensorflow.so
```
This can take a while (tens of minutes, more if also building for GPU).
3. Make `libtensorflow.so` available to the linker. This can be done by either:
a. Copying it to a system location, e.g.,
```sh
sudo cp ${GOPATH}/src/github.com/tensorflow/tensorflow/bazel-bin/tensorflow/libtensorflow.so /usr/local/lib
```
OR
b. Setting environment variables:
```sh
export LIBRARY_PATH=${GOPATH}/src/github.com/tensorflow/tensorflow/bazel-bin/tensorflow
# Linux
export LD_LIBRARY_PATH=${GOPATH}/src/github.com/tensorflow/tensorflow/bazel-bin/tensorflow
# OS X
export DYLD_LIBRARY_PATH=${GOPATH}/src/github.com/tensorflow/tensorflow/bazel-bin/tensorflow
```
4. Build and test:
```sh
go test github.com/tensorflow/tensorflow/tensorflow/go
```
## Support
Use [stackoverflow](http://stackoverflow.com/questions/tagged/tensorflow) and/or
[Github issues](https://github.com/tensorflow/tensorflow/issues).
## Contributions
Contributions are welcome. If making any signification changes, probably best to
discuss on a [Github issue](https://github.com/tensorflow/tensorflow/issues)
before investing too much time. Github pull requests are used for contributions.
|
