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CNTK_2_0_RC_2_Release_Notes
Mark Hillebrand edited this page Apr 21, 2017
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The Microsoft Cognitive Toolkit is in the final set of enhancements before release of the production version of CNTK 2.0. We expect no breaking changes before the release of the production version, but we are eager to hear your feedback!
- Support for new operators: pow, sequence.reduce_max, and sequence.softmax.
- New feature for Linux source builds:
- GPU Direct RDMA support in distributed gradients aggregation (enabled through
./configure --gdr=yes). - NCCL support for Python in V2 gradients aggregation
- GPU Direct RDMA support in distributed gradients aggregation (enabled through
- Additional bug fixes and improvements, including:
- Added API to set and get global tracing verbosity level.
- Added a mechanism to preserve the local state of a distributed worker in the checkpoint.
- Initial random seed can now be specified for the dropout and random sample nodes, the auto-generated seed value for these nodes is now worker-specific.
- Progress writers now log changes in learning rates and momentum values.
- Support for Python 3.6 for source and binary installation; see setup instructions.
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UserMinibatchSourcenow allows to write custom minibatch sources and pass them to the CNTK core. See here for documentation. - CNTK deterministic mode (
cntk.cntk_py.force_deterministic_algorithms()) is working except for overlapped max pooling. - Training session switched to distributed test evaluation and cross validation.
- New APIs:
class NDArrayViewand methods,SetMaxNumCPUThreads(),GetMaxNumCPUThreads(),SetTraceLevel(),GetTraceLevel() - Memory and performance optimization.
The updated APIs are described in this Wiki page.
A new set of NuGet Packages is provided with this Release.
IMPORTANT! In Visual Studio Manage Nuget Packages Window change the default option Stable Only to Include Prerelease. Otherwise the packages will not be visible. The Package version should be 2.0.0-rc2.