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Change Log

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog and this project adheres to Semantic Versioning.

[0.9.22]

Bugs Fixed

  • Backwards compatibility issue with pooling layers and older models which didn't include :pool-op (this changes the behavior between [:max :avg :avg-exc-pad]

[0.9.21]

Bugs Fixed

  • (layers/convolutional 3 0 1 64 :parents [:split-1]) will work now.

[0.9.20]

Added

  • Dropout is implemented in tensors (fewer cuda kernels!!)

[0.9.19]

  • pooling layer is implemented in tensors.
  • Non-overlapping nms algorithm for yolo for cases where you know things cannot overlap.

[0.9.17]

Added

  • Metrics for rating object detection systems.
  • Special NMS algorithm used for yolo is now in and unit tested.

##[0.9.14]

Added

  • Yolo-style loss implemented with the tensor framework.
  • Many optimizations and bugfixes around the tensor system.
  • Lots of fast paths of the tensor system mapped to cudnn functions.
  • Resnet50 optimizations - Memory significantly decreased (batch size of 32 possible in well under 1G video RAM).
  • Resnet50 optimizations - Elide split when doing inference; simply reuse buffer without any copy operations.
  • Resnet50 optimizations - GPU now pegged at 100% while training; batch upload happening during compute 100% of the time.

[0.9.11]

Bugs fixed

  • Memory leak calling cuda kernels (!!)

[0.9.10]

Bugs fixed

  • Small fix to ensure compilation in clojure-1.9 works properly
  • Batch normalization could produce NAN in some cases.

[0.9.9]

Added

  • "Censor" loss to prevent propagating gradients when labels are unknown
  • model-upgrader project to upgrade models from older versions of cortex
  • orthogonal weight initialization #178
  • tensorboard view #172

Changed

  • Loss functions are moved to their individual files to be consistent with optimizer layout

[0.9.8] - 2017-05-04

Bugs fixed

  • Only save base java types in file. This avoids incompatibility issues over time and upgrades #163

[0.9.7] - 2017-05-03

Bugs fixed

  • Dependencies updated to reduce and use latest version possible of most libraries.
  • thread colorspace into experiment so the mnist framework can be used for color images #162.

[0.9.6] - 2017-04-28

Bugs fixed

  • inferring and training were subtly broken.
  • Bugfixes in the classifcation example.

[0.9.5] - 2017-04-26

Added

  • CPU-only support. Cortex can now run on the CPU without CUDA drivers being installed.
  • docker-example -- A simple example of how to run a cortex project in a docker container.
  • multi-thread -- The execution context now supports specifying the device, allowing for more advanced asynchronous computations like pipeline parallelism and using multiple devices.

Bugs fixed