per-node timing creates items in profiler details when profiler is enabled.
usage in Python:
import cntk as C
C.debugging.start_profiler() # optional
C.debugging.enable_profiler() # optional
CPU inference performance improvements using MKL
Accelerates some common tensor ops in Intel CPU inference for float32, especially for fully connected networks
Can be turned on/off by cntk.cntk_py.enable_cpueval_optimization()/cntk.cntk_py.disable_cpueval_optimization()
1BitSGD incorporated into CNTK
1BitSGD source code is now available with CNTK license (MIT license) under Source/1BitSGD/
1bitsgd build target was merged into existing gpu target
New loss function: hierarchical softmax (Thanks @yaochengji for the contribution!)
Distributed Training with Mulitple Learners
Trainer now accepts multiple parameter learners for distributed training. With this change, different parameters of a network can be learned by different learners in a single training session. This also facilitates distributed training for GANs. For more information, please refer to the Basic_GAN_Distributed.py and the cntk.learners.distributed_multi_learner_test.py
Added MeanVarianceNormalization operator.
Fixed convergence issue in Tutorial 201B
Fixed pooling/unpooling to support free dimension for sequences
Fixed crash in CNTKBinaryFormat deserializer when crossing sweep boundary
Fixed shape inference bug in RNN step function for scalar broadcasting
Fixed a build bug when mpi=no
Improved distributed training aggregation speed by increasing packing threshold, and expose the knob in V2
Fixed a memory leak in MKL layout
Fixed a bug in cntk.convert API in misc.converter.py, which prevents converting complex networks.
CNTK exported ONNX models are now ONNX.checker compliant.
Added ONNX support for CNTK’s OptimizedRNNStack operator (LSTM only).
Added support for LSTM and GRU operators
Added support for experimental ONNX op MeanVarianceNormalization.
Added support for experimental ONNX op Identity.
Added support for exporting CNTK’s LayerNormalization layer using ONNX MeanVarianceNormalization op.
Bug or minor fixes:
Axis attribute is optional in CNTK’s ONNX Concat operator.
Bug fix in ONNX broadcasting for scalars.
Bug fix in ONNX ConvTranspose operator.
Backward compatibility bug fix in LeakyReLu (argument ‘alpha’ reverted to type double).
Added a new API find_by_uid() under cntk.logging.graph.