- Support for Julia 1.0 has been added. Support for all prior versions of Julia (except 0.7, which is functionally identical to 1.0) has been dropped.
- Support for Julia 0.5 has been dropped.
- Enhanced support for visualization with TensorBoard.
- Operations defined in C are now accessed by
import_op(<op name>)
instead ofOps.<op name>
.
The API has changed to resemble the finalized TensorFlow 1.0 API. See the TensorFlow release notes for a list of the changes.
In particular for TensorFlow.jl:
- The summary operations, like
train.scalary_summary
, have moved tosummary.scalar
. train.SummaryWriter
has moved tosummary.FileWriter
.- The
reduction_indices
keyword argument have changed toaxis
in every function which used to take areduction_indices
argument. mul
has changed tomultiply
, and likewise forsub
andneg
.pack
is nowstack
andunpack
is nowunstack
.- The
*_cross_entropy_with_logits
family of functions has changed to only accept keyword arguments instead of positional arguments. - The order of arguments to
concat
has switched (tensors to concatenate come first, followed by the concetenation axis).
dynamic_rnn
has been addedwhile_loop
has been added, with a convenient@tf while ... end
syntax- Support for Docker via official Docker images
Operations which take indices as arguments now expect the arguments to be 1-based instead of 0-based, which was a hold-over of TensorFlow's Python legacy. This affects the following functions:
- The
axis
parameter for any operation which takes anaxis
parameter - The
begin_
argument ofslice
Every operation defined by TensorFlow is now automatically wrapped in a
Julia function available in the Ops
module.