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This repository has been archived by the owner on Jan 3, 2023. It is now read-only.

Releases: NervanaSystems/neon

Skip Thought Vectors, dilated convolution support, Nesterov Accelerated Gradient

28 Dec 19:55
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  • Skip Thought Vectors (http://arxiv.org/abs/1506.06726) example
  • Dilated convolution support
  • Nesterov Accelerated Gradient option to SGD optimizer
  • MultiMetric class to allow wrapping Metric classes
  • Support for serializing and deserializing encoder-decoder models
  • Allow specifying the number of time steps to evaluate during beam search
  • A new community-contributed Docker image
  • Improved error messages when a tensor is created with an invalid shape or reshaped to an incompatible size
  • Fix bugs in MultiCost support
  • Documentation fixes [#331]

New Data Loader (aeon), Neural Machine Translation, doc updates and bug fixes

21 Nov 17:06
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  • Update Data Loader to aeon https://github.com/NervanaSystems/aeon for flexible,
    multi-threaded data loading and transformations
  • Add Neural Machine Translation model
  • Remove Fast RCNN model (use Faster RCNN model instead)
  • Remove music_genres example
  • Fix super blocking for small N with 1D conv
  • Fix update-direct conv kernel for small N
  • Add gradient clipping to Adam optimizer
  • Documentation updates and bug fixes

Faster RCNN, Sequence to Sequence, Reshape layer, updated pip requirements

21 Sep 17:50
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  • 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

Python 3 support, persistent RNN kernels, and improvements to dataloader, convolutional kernels and docs.

15 Jul 17:54
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Python 3 support, persistent RNN kernels, and improvements to dataloader, convolutional kernels and docs.

07 Jul 23:15
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  • Python2/Python3 compatibility [#191]
  • Support for Pascal GPUs
  • Persistent RNN kernels [#262]
  • Dataloader enhancements (audio loader with examples)
  • HDF5 file data iterator
  • Convolution kernel improvements
  • API documentation improvements [#234, #244, #263]
  • Cache directory cleanup
  • Reorganization of all unit tests
  • Bug fixes [#182, #183, #231, #241, #252, #253, #257, #259, #267]

Python 3 support, persistent RNN kernels, and improvements to dataloader, convolutional kernels and docs.

07 Jul 04:03
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  • Python2/Python3 compatibility [#191]
  • Support for Pascal GPUs
  • Persistent RNN kernels [#262]
  • Dataloader enhancements (audio loader with examples)
  • HDF5 file data iterator
  • Convolution kernel improvements
  • API documentation improvements [#234, #244, #263]
  • Cache directory cleanup
  • Reorganization of all unit tests
  • Bug fixes [#182, #183, #231, #241, #252, #253, #257, #259]

Python 3 support, persistent RNN kernels, and improvements to dataloader, convolutional kernels and docs.

30 Jun 23:43
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  • Python2/Python3 compatibility [#191]
  • Support for Pascal GPUs
  • Persistent RNN kernels [#262]
  • Dataloader enhancements (audio loader with examples)
  • HDF5 file data iterator
  • Convolution kernel improvements
  • API documentation improvements [#234, #244, #263]
  • Cache directory cleanup
  • Reorganization of all unit tests
  • Bug fixes [#182, #183, #231, #241, #252, #253, #257, #259]

winograd fast R-CNN, new dataloader

29 Apr 22:39
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  • VGG16 based Fast R-CNN model using winograd kernels
  • new, backward compatible, generic data loader
  • C3D video loader model trained on UCF101 dataset
  • Deep Dream example
  • make conv layer printout more informative [#222]
  • fix some examples to use new arg override capability
  • improve performance for relu for small N
  • better support for arbitrary batch norm layer placement
  • documentation updates [#210, #213, #236]

Winograd kernels

04 Mar 02:05
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  • winograd kernels and associated autotuning routines
  • benchmarking scripts
  • deprecation of deterministic argument for backend constructor
  • improve batch norm stability with fp16 backend
  • allow strided support for dimshuffle kernel
  • speed up zero momentum gradient descent

Various fixes, kernel speedups

25 Feb 04:50
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  • benchmarking enhancements
  • fast dimshuffle, transpose, other kernel speedups and refactoring
  • batch norm states fix, deterministic updates
  • example fixes for fast rcnn and conv_autoencoder
  • image decoding rescaling method fix
  • deserialization fixes for RNN's, refactoring
  • caffe compatibility fixes
  • documentation updates