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CNTK_2_0_RC_2_Release_Notes
Mark Hillebrand edited this page Apr 21, 2017
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With the Release Candidate 2 we ship one of the last previews before the Microsoft Cognitive Toolkit V2 final release by the end of May. There is still time to incorporate your feedback - so keep it coming!
- New operators added: 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 functionality to set and get global tracing verbosity level.
- Added a mechanism to preserve the local state of a distributed worker in the checkpoint.
- The initial random seed can now be specified for dropout and random sample nodes, the auto-generated seed values for these nodes are now worker-specific.
- Progress writers will log changes in learning rates and momentum values.
- Support for Python 3.6 for source and binary installation; see setup instructions.
-
UserMinibatchSource
now 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()
) can be enabled in all configurations, except for overlapped max pooling. - Training session switched to distributed test evaluation and cross validation.
- New APIs:
class NDArrayView
and 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! For Visual Studio: In the Manage Nuget Packages window change the default option Stable Only to Include Prerelease. Otherwise the release candidate package of CNTK will not be visible. This Package version is 2.0.0-rc2
.