Author Bio Image

Jennifer Myers

Jennifer has 20 years experience leading software engineering at both startups and large companies - spanning networking, security, video and search. She created her first neural networks at Carnegie Mellon in 1987, holds a Ph.D. in Neuroscience from Northwestern where she built recurrent neural networks for her thesis, and she is thrilled to be advancing her original field of study once again.

Highlights from this release include: 

  • Faster RCNN model
  • Sequence to Sequence container and char_rae recurrent autoencoder model
  • Reshape Layer that reshapes the input[#221]
  • 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

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