-
Notifications
You must be signed in to change notification settings - Fork 4.3k
CNTK_2_0_Beta_6_Release_Notes
This is a summary of new features delivered with the Beta 6 release of CNTK V.2.0.
This release adds support of CUDA 8 on Linux (support on Windows was introduced in Beta 5). Binary packages for both Linux and Windows are built using NVIDIA CUDA 8.0. If you are a developer and building CNTK on your own system you can still continue using CUDA 7.5. However note, that this will change soon. See more details here.
CNTK now supports Sparse Data using the Python API. See its usage in “Build Neural Character Language Models with CNTK” Example (see "New Examples and Tutorials" section below).
Linux version of CNTK is now shipped with the support of Python 3.5. (Support for Windows version will be added soon). To enable Python 3.5 for your CNTK environment you need to pass the following parameter to the installation script:
./install-cntk.sh --py-version 35
If the script is called without any parameters (or with the parameter --py-version 34) then Python 3.4 will be enabled.
See the full installation instructions for binary package on Linux here.
We have prepared the following Examples and Tutorials:
- Video action recognition
- Sequence-to-Sequence (new tutorial)
- Finance Timeseries Basic with Pandas / Numpy
- Build Neural Character Language Models with CNTK
We have introduce the following change to maintain backwards compatibility:
cntk.graph.find_nodes_by_name() was renamed to find_all_with_name(). In addition, there is now find_by_name(name) method, which returns a single function or throws an error if there was not found exactly one match of that name. Both methods are also available directly from the function object, e.g.
input1 = z.find_by_name('input1')
We also continue fine tuning new features and fixing different bugs - thank you once again for the constant feedback. You are not required to adopt your code or models to take an advantage of these improvements.