Installing TensorFlow for Go
TensorFlow provides APIs for use in Go programs. These APIs are particularly well-suited to loading models created in Python and executing them within a Go application. This guide explains how to install and set up the TensorFlow Go package.
WARNING: The TensorFlow Go API is not covered by the TensorFlow API stability guarantees.
Supported Platforms
You may install TensorFlow for Go on the following operating systems:
- Linux
- Mac OS X
Installation
TensorFlow for Go depends on the TensorFlow C library. Take the following steps to install this library and enable TensorFlow for Go:
Decide whether you will run TensorFlow for Go on CPU(s) only or with the help of GPU(s). To help you decide, read the section entitled "Determine which TensorFlow to install" in one of the following guides:
Download and extract the TensorFlow C library into
/usr/local/lib
by invoking the following shell commands:TF_TYPE="cpu" # Change to "gpu" for GPU support TARGET_DIRECTORY='/usr/local' curl -L \ "https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-${TF_TYPE}-$(go env GOOS)-x86_64-1.3.0-rc1.tar.gz" | sudo tar -C $TARGET_DIRECTORY -xz
The
tar
command extracts the TensorFlow C library into thelib
subdirectory ofTARGET_DIRECTORY
. For example, specifying/usr/local
asTARGET_DIRECTORY
causestar
to extract the TensorFlow C library into/usr/local/lib
.If you'd prefer to extract the library into a different directory, adjust
TARGET_DIRECTORY
accordingly.In Step 2, if you specified a system directory (for example,
/usr/local
) as theTARGET_DIRECTORY
, then runldconfig
to configure the linker. For example:sudo ldconfig
If you assigned a
TARGET_DIRECTORY
other than a system directory (for example,~/mydir
), then you must append the extraction directory (for example,~/mydir/lib
) to two environment variables as follows:export LIBRARY_PATH=$LIBRARY_PATH:~/mydir/lib # For both Linux and Mac OS X export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:~/mydir/lib # For Linux only export DYLD_LIBRARY_PATH=$DYLD_LIBRARY_PATH:~/mydir/lib # For Mac OS X only
Now that the TensorFlow C library is installed, invoke
go get
as follows to download the appropriate packages and their dependencies:go get github.com/tensorflow/tensorflow/tensorflow/go
Invoke
go test
as follows to validate the TensorFlow for Go installation:go test github.com/tensorflow/tensorflow/tensorflow/go
If go get
or go test
generate error messages, search (or post to)
StackOverflow
for possible solutions.
Hello World
After installing TensorFlow for Go, enter the following code into a
file named hello_tf.go
:
package main
import (
tf "github.com/tensorflow/tensorflow/tensorflow/go"
"github.com/tensorflow/tensorflow/tensorflow/go/op"
"fmt"
)
func main() {
// Construct a graph with an operation that produces a string constant.
s := op.NewScope()
c := op.Const(s, "Hello from TensorFlow version " + tf.Version())
graph, err := s.Finalize()
if err != nil {
panic(err)
}
// Execute the graph in a session.
sess, err := tf.NewSession(graph, nil)
if err != nil {
panic(err)
}
output, err := sess.Run(nil, []tf.Output{c}, nil)
if err != nil {
panic(err)
}
fmt.Println(output[0].Value())
}
For a more advanced example of TensorFlow in Go, look at the example in the API documentation, which uses a pre-trained TensorFlow model to label contents of an image.
Running
Run hello_tf.go
by invoking the following command:
go run hello_tf.go Hello from TensorFlow version number
The program might also generate multiple warning messages of the following form, which you can ignore:
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use *Type* instructions, but these are available on your machine and could speed up CPU computations.
Building from source code
TensorFlow is open-source. You may build TensorFlow for Go from the TensorFlow source code by following the instructions in a separate document.