Highlights from this release include: 

  • Faster RCNN model
  • Sequence to Sequence container and char_rae recurrent autoencoder model
  • Reshape Layer that reshapes the input
  • Pip requirements in requirements.txt updated to latest versions [#289]
  • Remove deprecated data loaders and update docs
  • Use NEON_DATA_CACHE_DIR envvar as archive dir to store DataLoader ingested data
  • Eliminate type conversion for FP16 for CUDA compute capability >= 5.2
  • Use GEMV kernels for batch size 1
  • Alter delta buffers for nesting of merge-broadcast layers
  • Support for ncloud real-time logging
  • Add fast_style Makefile target
  • Fix Python 3 builds on Ubuntu 16.04
  • Run setup.py for sysinstall to generate version.py [#282]
  • Fix broken link in mnist docs
  • Fix conv/deconv tests for CPU execution and fix i32 data type
  • Fix for average pooling with batch size 1
  • Change default scale_min to allow random cropping if omitted
  • Fix yaml loading
  • Fix bug with image resize during injest
  • Update references to the ModelZoo and neon examples to their new locations

fast-rcnn-example-1_1024 fast-rcnn-example-2_1024

As always, you can grab this release from github at: https://github.com/NervanaSystems/neon