TensorFlow

Wraps the TensorFlow Python library in Julia, via the PyCall package.

This is done in two stages:

• The low-level interface in the modules underneath TensorFlow.API aims to provide a faithful, direct mapping to the original Python functions, merely adding some Julia type annotations to the function declarations.

• The TensorFlow.Idiomatic module then implements methods for standard Julia base functions using the API interface, so that manipulating Tensor objects and others can be done in the same way as working with ordinary Array objects.

Note that functions which are passed Tensor objects will not directly return the results, but will instead return TensorFlow graphs that can be run later in a Session. See the examples directory, especially examples/polymorphism.jl.

Additional notes for package developers

The TensorFlowBuilder package contains code to generate the Julia source in the TensorFlow.API module by introspecting the Python package. It is not necessary to use this package, but could be helpful to correct bugs in the wrapper, or to extend it further.