TensorFlow for Scala is currently available for Scala 2.11.x and for 2.12.x. The main line of development is version 2.12.3. Binary release artifacts are published to the Sonatype OSS Repository Hosting service and synced to Maven Central. Currently, given the beta status of this project, only snapshot releases are published.
Using with SBT
To include the Sonatype repositories in your SBT build and use TensorFlow for Scala, you
should add the following to your
resolvers += Resolver.sonatypeRepo("snapshots") libraryDependencies += "org.platanios" %% "tensorflow" % "0.1.0-SNAPSHOT"
NOTE: This requires that you have installed the TensorFlow dynamic library in your system. If you haven’t, please continue reading into the following section.
TensorFlow Dynamic Library
TensorFlow for Scala is an API for TensorFlow. In order for it work, it requires that you have the main TensorFlow dynamic library installed. You have two options for dealing with this requirement:
libraryDependencies += "org.platanios" %% "tensorflow" % "0.1.0-SNAPSHOT" classifier "linux-cpu-x86_64"
instead of the line above, for your
build.sbtfile. Make sure to replace
linux-cpu-x86_64with the string that corresponds to your platform. Currently supported platforms are:
darwin-cpu-x86_64. I hope to support Windows soon.
Compile the TensorFlow dynamic library yourself and install it in your system. This is the recommended approach if you care about performance, but it is also significantly more complicated and time consuming. It consists of the following steps:
Clone the TensorFlow repository:
git clone https://github.com/tensorflow/tensorflow.git <repository_directory> cd <repository_directory>
Compile the library using the following commands:
./configure bazel build --config=opt //tensorflow:libtensorflow.so
For details regarding the configuration options (e.g., GPU support), please refer to the relevant main TensorFlow documentation page.
bazel-bin/tensorflow/libtensorflow.so(possibly having a different extension, depending on the platform you’re using) file in a directory that is in
LD_LIBRARY_PATH, or set
NOTE: If you want to compile TensorFlow for Scala yourself and the
libtensorflow.so file is not placed in one of
the default system libraries directories, then set
<directory> with the
directory containing the
libtensorflow.so file) in the
.jvmopts file at the root of the TensorFlow for Scala
Protocol Buffers Compiler
TensorFlow for Scala also requires
protoc, the Protocol Buffers compiler, to be installed. You also have two options
for dealing with this requirement:
- Install it using a package manager:
- Download pre-built binaries from
https://github.com/google/protobuf/releases/ (choose the
protocvariant appropriate for your platform) and make sure that
protocis in the
PATH(either by installing it in a location in the
PATH, or by adding its location to the
NOTE: You need to install
protoc with version at least 3.