This repository has been archived by the owner on Jan 3, 2023. It is now read-only.
Releases: NervanaSystems/neon
Releases · NervanaSystems/neon
Skip Thought Vectors, dilated convolution support, Nesterov Accelerated Gradient
- 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
- 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
- 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.
- Python2/Python3 compatibility [#191]
- Support for Pascal GPUs
- Persistent RNN kernels [#262]
- Implement Binarized Neural Networks from http://arxiv.org/pdf/1602.02830v3.pdf (added in v1.5.4)
- 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, #268]
Python 3 support, persistent RNN kernels, and improvements to dataloader, convolutional kernels and docs.
- 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.
- 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.
- 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
- 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
- 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
- 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