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DALI v0.4.0

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@JanuszL JanuszL released this 31 Oct 22:14

Bug fixes

  • Fixed ability to use the same output from the support operator by CPU and GPU stage
  • Removed inconsistent-missing-override Clang warning (#197)
  • Fixed clang warnings in half.hpp and tests (#194)
  • Resolved conflicting build dirs (#189)
  • Removed the redundant imports and spaces in pytorch example (#190)
  • Fixed table in README.rst
  • Fixed reporting of the end of epoch in MXNet and pyTorch plugins (#180)
  • Fixed parsing of JPEG headers (#175)
  • Maked assigning of the classes to discovered dirs by file reader base on alphabetic order.
  • Fixed BMP size reading
  • Moved wait in multiple input sets case to the common place to guard against problem reoccurring in newly added ops
  • Removed batch_size_ from CoinFlip operator (#152)
  • Fixed corruption in MXNet reader when image is split between multiple records (#216)

Improvements

  • Added bounding box mirror operator (#188)
  • Added random crop for SSD (#176)
  • Added COCO dataset reader (#110)
  • Removed visibility of all non DALI symbols and test if ABI is clean (#191)
  • Added support for pad in MXNet plugin (#186)
  • Reduced memory usage (#195)
  • Made libprotobuf internal to DALI only (#179)
  • Added CUDA 10 based build (#178)
  • Made use epoch_size instead of hardcoded values (#174)
  • Added random paste operator (#105)
  • Added clang build (#163)
  • Added png in testing pipeline, add some of tiff routines
  • Made files to be copied after build not only when libdali is rebuild
  • Put common test code into one file
  • Upgraded OpenCV to 3.4.3 (#168)
  • Added color-twist operator (#164)
  • Changed MxNet to 1.3.0 no-beta (#183)
  • Added better sharding when number of shards does not divide the dataset size evenly (#181)
  • Updated google benchmark to v1.4.1 + several fixes (#182)
  • Added CPU versions of Crop/CropCastPermute operators (#148)
  • Added info about posting questions and problems
  • Updated PyTorch example to be alligned with the reent APEX release (#206)
  • Improved load balancing nvJPEG work (#217)
  • Updated nvJPEG to 0.2.0 version (#227)
  • Added fine grained control over output buffers in the pipeline (#212)

Binary builds

Install via pip:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist nvidia-dali==0.4.0

Or use direct download links: