Skip to content

Releases: NVIDIA/DALI

DALI v1.1.0

15 Apr 13:43
@banasraf banasraf
v1.1.0
25b99fa
Compare
Choose a tag to compare
DALI v1.1.0

Key Features and Enhancements

This DALI release includes the following key features and enhancements.

  • Documentation improvements (#2834, #2824, #2831, #2758, #2820, and #2822).
  • The following operators were added:
    • The experimental numba_func operator that allows the use of Numba functions in the DALI pipeline (#2804).
    • The expand_dims and squeeze operators for shape manipulation (GPU and CPU) (#2800, #2791, #2792).
    • The multi_paste operator (GPU) (#2681).
  • The following kernels were added:
    • JPEG compression distortion (GPU) (#2801, #2830, and #2839).
    • JPEG color conversion and chroma subsampling (GPU) (#2771).
  • Enabled CUDA kernels compression to decrease the DALI binaries size (#2833).
  • Added the src_dims argument to the reshape operator (#2788).

Fixed issues

This DALI release includes the following fixes:

  • Fixed a race condition in readers.nemo_asr when pad_last_batch is set to True (#2828).
  • Fixed the optical flow initialization issue (#2816).
  • Fixed a race condition in the data loader (#2773).

Improvements

  • Remove 0 default value from mean/std arguments of normalize. (#2834)
  • Add JpegCompressionDistortionGPU kernel (#2830)
  • Updates the pipeline docs page (#2824)
  • Enable CUDA kernels compression in the final binary (#2833)
  • Updates build documentation (#2831)
  • Update key visual (#2822)
  • Add NumbaFunc operator (#2804)
  • Add JPEG distortion kernel (#2801)
  • Add AddArg overloads for enum types (#2819)
  • Update third party dependencies to latest release versions (#2811)
  • Add an ability to provide a custom DALI_extra sha via env variable (#2810)
  • Move all deps into subrepos (#2756)
  • Reshape, Reinterpret, Squeeze and ExpandDims tutorial. (#2791)
  • Separate creation of dependency creation and CUDA installation (#2786)
  • Remove intermediate stage from CUDA toolkit dockerfile (#2803)
  • Add Expand dims operator (#2800)
  • Update TensorFlow ResNet50 example to the latest horovod 21.03 (#2793)
  • Add squeeze operator (#2792)
  • Add JPEG color conversion and chroma subsampling kernel (#2771)
  • Add src_dims to reshape operator (#2788)
  • GPU MultiPaste (#2681)
  • Add --upgrade to pip install commands in documentation (#2758)
  • Use flattened view of the array for copying to shared memory. (#2783)

Bug fixes

  • Fix JPEG distortion kernel quality parameter handling (#2839)
  • Fix typo "funcions" <- "funcions" in math doc (#2820)
  • Update DALI_deps to include FLAC security patch (#2826)
  • Fix coverity issues (#2812)
  • Fix optical flow parameter initialization. (#2816)
  • Add host fallback when nvjpegDecodeJpegDevice and nvjpegDecodeJpegHost fail (#2805)
  • ExternalSource - discard data from all callbacks when one raises StopIteration (#2784)
  • Exclude PyTorch-lighting test with MNIST (#2785)
  • Fix iteration number tracking with pipeline.reset (#2777)
  • Fix a race when loader starts reading even the metadata is not ready yet (#2773)
  • Fix race condition in NemoAsrReader when pad_last_batch is set to True (#2828)

Breaking API changes

There are no breaking changes in this DALI release.

Deprecated features

There are no deprecated features in this DALI release.

Known issues:

  • The video loader operator requires that the key frames occur at a minimum every 10 to 15 frames of the video stream. If the key frames occur at a lesser frequency, then the returned frames may be out of sync.
  • The DALI TensorFlow plugin might not be compatible with TensorFlow versions 1.15.0 and later.
    To use DALI with the TensorFlow version that does not have a prebuilt plugin binary shipped with DALI, make sure that the compiler that is used to build TensorFlow exists on the system during the plugin installation. (Depending on the particular version, use GCC 4.8.4, GCC 4.8.5, or GCC 5.4.)
  • Due to some known issues with meltdown/spectra mitigations and DALI, DALI shows best performance when run in Docker with escalated privileges, for example:
    • privileged=yes in Extra Settings for AWS data points
    • --privileged or --security-opt seccomp=unconfined for bare Docker

Binary builds

Install via pip for CUDA 10:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda100==1.1.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda100==1.1.0

or for CUDA 11:

CUDA 11.0 build uses CUDA toolkit enhanced compatibility. It is built with the latest CUDA 11.x toolkit
while it can run on the latest, stable CUDA 11.0 capable drivers (450.80 or later). 
Using the latest driver may enable additional functionality. 
More details can be found in enhanced CUDA compatibility guide.

pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda110==1.1.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda110==1.1.0

Or use direct download links (CUDA 10.0):

Or use direct download links (CUDA 11.0):

FFmpeg source code:

  • This software uses code of FFmpeg licensed under the LGPLv2.1 and its source can be downloaded here

Libsndfile source code:

Loading

DALI v1.0.0

24 Mar 15:26
@banasraf banasraf
v1.0.0
808b1f8
Compare
Choose a tag to compare
DALI v1.0.0

Key Features and Enhancements

This DALI release includes the following key features and enhancements.

  • The API documentation has been improved:
  • New operators:
    • A GridMask GPU operator for GridMask data augmentation (#2652).
    • A RandomObjectBBox operator with caching to randomly select a bounding box (#2718, #2696, #2677, and #2657).
    • A MultiPaste operator, is required to implement Mosaic augmentation (#2583).
  • External Source can now run the per-sample callbacks in parallel (#2543).
  • Added pipeline_def decorator, which is an easier to define a pipeline with the functional API (#2757 and #2629).
  • Moved all decoders to a dedicated Python module (#2741, #2743, and #2725).
  • Moved all readers to a dedicated Python module (#2720, #2721, #2717, #2715, and #2722).
  • Exposed the pipeline output names in the C API (#2665).
  • Introduced the following named Slice operator arguments (#2625):
    • start/rel_start
    • end/rel_end
    • shape/rel_shape
  • Enabled additional codecs and demuxers in FFmpeg (#2651).
  • Added an option to disable the first batch preparation during the iterator construction (#2664).

Fixed issues

This DALI release includes the following fixes:

  • Fixed the JPEG 2000 ROI decoding (#2692).
  • Fixed the layout length check in Transpose (#2693).
  • Fixed the .gpu() usage detection and error for CPU-only pipelines (#2682).

Improvements

  • Rework frameworks notebooks to fn API (#2761)
  • Bump up OpenCV-python version in tests (#2749)
  • Enhance deprecated argument documentation (#2755)
  • Convert notebooks to fn API: audio_processing, custom_operator, serialization (#2744)
  • Expose all pipeline constructor arguments as properties. (#2757)
  • Convert notebooks to fn API: sequence_processing (#2748)
  • Gridmask Gpu (#2652)
  • Run external source callback in parallel (#2543)
  • Bump up nvidia-tensorflow version to 1.15.5 21.02 (#2738)
  • Rewrite image processing examples to fn api. (#2745)
  • Update augmentation gallery (#2716)
  • Remove dynlink CUDA libs from the build image (#2739)
  • Rework getting started (#2729)
  • Adjust Python decoders tests to decoders module (#2741)
  • Adjust notebooks to new decoder module (#2743)
  • Update memory resource interfaces. (#2742)
  • Move decoders to decoders module (#2725)
  • Add Examples and Tutorials metadata title (#2730)
  • Adjust test to new readers module (#2720)
  • Adjust examples to new readers module (#2721)
  • Documentation home update (#2713)
  • Move tfrecord reader to readers module (#2722)
  • Move readers to dedicated submodule (#2717)
  • Add hash-based caching to RandomObjectBBox. (#2718)
  • Add break of VideoReader loop when keyframe past requested has been reached (#2706)
  • Improve set_outputs to accept list or tuple of data nodes as well (#2698)
  • Documentation: New layout of Examples and Tutorials section (#2710)
  • Rename test files for readers (#2715)
  • Add error checking if provided shape to tfrecord can house underlying data (#2705)
  • Documentation editorial changes: Init caps for all headings, Copyright update (#2703)
  • Add documentation to functional API (all fn.*) + New documentation layout (#2653)
  • Parallel random object BBox (#2677)
  • Rework ThreadPool and spinlock (#2696)
  • Improvements in Dockerfile.deps so that RUN commands are easily run in a non-docker environment (#2686)
  • Fix formatting of Resnet-N with Tensorflow example (#2694)
  • Operator RandomObjectBBox (#2657)
  • MultiPaste operator (#2583)
  • Add better exception granurality to memory::alloc_shared and memory::alloc_unique (#2683)
  • Make DALI pipeline use default seed (-1) when None is set to seed (#2676)
  • Make preparation of the first batch during the iterator construction optional (#2664)
  • Parallelize commands in bundle-wheel.sh (#2672)
  • Pipeline decorator (#2629)
  • Move to CUDA 11.2 update 1 (#2668)
  • Make sure that OpenCV decoding fallback follows EXIF information handling (#2666)
  • Expose names of Pipeline outputs in C API (#2665)
  • Enable named Slice arguments: start/rel_start, end/rel_end, shape/rel_shape (#2625)
  • Update nvidia-tensorflow in qa scripts to 20.12 (#2654)
  • Enable more codecs and demuxers in FFmpeg (#2651)

Bug fixes

  • Fix paddle ssd (#2765)
  • Fix Gluon example (#2764)
  • Remove redundant dimension from Optical Flow example. (#2762)
  • Fix 403 error when downloading Mnist dataset in Pytorch Lighting example (#2759)
  • Fix documentation instances of deprecated fn.image_decoder (#2754)
  • Shutdown executor when an error occurs in the executor itself, not in one of operators. (#2750)
  • Fix libcufile.so name to have *.0 sufix (#2735)
  • Fix test exclude pattern for Xavier (#2731)
  • Fix auto replacement of deprecated args for schema inheritance (#2733)
  • Fix constant input promotion for mixed backend. (#2726)
  • Fix type of slice's rel_shape argument (#2714)
  • Fix a regression in RandomObjectBBox: weights not set to default. (#2719)
  • Update TensorFlow ReseNet50 example to work with the latest TF 2.4.x version (#2704)
  • Add auto generated docs files to .gitignore (#2711)
  • Update DALI PyTorch ligthing example to work with the newest lighting (#2697)
  • Fix JPEG2K fused decoding (with ROI), add native tests for JP2k decoding (#2692)
  • Fix TL1_tensorflow-dali_test (#2687)
  • Remove unnecessary cuda runtime dependency from alloc.h (#2691)
  • Fix layout length check in Transpose. (#2693)
  • Replace eval with safer ast.literal_eval (#2690)
  • Fix .gpu usage detection and error for CPU only pipelines (#2682)
  • Add support for TensorFlow 2.4.1 in tests and for TF plugin (#2679)
  • Fix wrong early exit in function inside bundle-wheel.sh (#2675)
  • Fix apex compilation on Ubuntu 20.04 in TL1_ssd_training (#2671)
  • Fix cmake installation in TL1 for Ubuntu 20.04 (#2669)
  • Remove the split stages implementation of the hybrid image decoder (#2753)

Breaking API changes

There are no breaking changes in this DALI release.

Deprecated features

  • fn.audio_decoder / ops.AudioDecoder has been renamed to fn.decoders.audio / ops.decoders.Audio.
  • fn.image_decoder / ops.ImageDecoder has been renamed to fn.decoders.image / ops.decoders.Image.
  • fn.image_decoder_crop / ops.ImageDecoderCrop has been renamed to fn.decoders.image_crop / ops.decoders.ImageCrop.
  • fn.image_decoder_random_crop / ops.ImageDecoderRandomCrop has been renamed to fn.decoders.image_random_crop / ops.decoders.ImageRandomCrop.
  • fn.image_decoder_slice / ops.ImageDecoderSlice has been renamed to fn.decoders.image_slice / ops.decoders.ImageSlice.
  • fn.caffe2_reader / ops.Caffe2Reader has been renamed to fn.readers.caffe2 / ops.readers.Caffe2.
  • fn.caffe_reader / ops.CaffeReader has been renamed to fn.readers.caffe / ops.readers.Caffe.
  • fn.coco_reader / ops.CocoReader has been renamed to fn.readers.coco / ops.readers.Coco.
  • fn.file_reader / ops.FileReader has been renamed to fn.readers.file / ops.readers.File.
  • fn.mxnet_reader / ops.MXNetReader has been renamed to fn.readers.mxnet / ops.readers.MXNet.
  • fn.nemo_asr_reader / ops.NemoAsrReader has been renamed to fn.readers.nemo_asr / ops.readers.NemoAsr.
  • fn.numpy_reader / ops.NumpyReader has been renamed to fn.readers.numpy / ops.readers.Numpy.
  • fn.sequence_reader / ops.SequenceReader has been renamed to fn.readers.sequence / ops.readers.Sequence.
  • fn.tfrecord_reader / ops.TFRecordReader has been renamed to fn.readers.tfrecord / ops.readers.TFRecord.
  • fn.video_reader / ops.VideoReader has been renamed to fn.readers.video / ops.readers.Video.
  • fn.video_reader_resize/ops.VideoReaderResize has been renamed to fn.readers.video_resize / ops.readers.VideoResize.

Known issues:

  • The video loader operator requires that the key frames occur at a minimum every 10 to 15 frames of the video stream. If the key frames occur at a lesser frequency, then the returned frames may be out of sync.
  • The DALI TensorFlow plugin might not be compatible with TensorFlow versions 1.15.0 and later.
    To use DALI with the TensorFlow version that does not have a prebuilt plugin binary shipped with DALI, make sure that the compiler that is used to build TensorFlow exists on the system during the plugin installation. (Depending on the particular version, use GCC 4.8.4, GCC 4.8.5, or GCC 5.4.)
  • Due to some known issues with meltdown/spectra mitigations and DALI, DALI shows best performance when run in Docker with escalated privileges, for example:
    • privileged=yes in Extra Settings for AWS data points
    • --privileged or --security-opt seccomp=unconfined for bare Docker

Binary builds

Install via pip for CUDA 10:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda100==1.0.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda100==1.0.0

or for CUDA 11:

CUDA 11.0 build uses CUDA toolkit enhanced compatibility. It is built with the latest CUDA 11.x toolkit
while it can run on the latest, stable CUDA 11.0 capable drivers (450.80 or later). 
Using the latest driver may enable additional functionality. 
More details can be found in enhanced CUDA compatibility guide.

pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda110==1.0.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda110==1.0.0

Or use direct download links (CUDA 10.0):

Read more
Loading

DALI v0.31.0

25 Feb 14:29
@banasraf banasraf
v0.31.0
b6d638b
Compare
Choose a tag to compare
DALI v0.31.0

Key Features and Enhancements

This DALI release includes the following key features and enhancements.

  • New operators:
    • Gridmask CPU and GridMask Data Augmentation (https://arxiv.org/abs/2001.04086), which is useful for the EfficientNet pipeline (#2582).
    • ROIRandomCrop CPU, where an operator is required to perform the biased random crop in segmentation applications (#2638).
  • Added support for the variable batch size in ExternalSource (#2481, #2641).
  • Added support for the time-major layout in the following spectrogram processing operators:
  • Refactored and unified the following RNG operators:
  • Reworked the custom operators documentation (#2568).
  • Applied performance improvements in the JPEG decoder (#2655, #2610).

Fixed issues

  • Fixed the length that was reported by DALI FW iterators when the DROP policy is used (#2611)
  • Provided a workaround for a compiler problem that caused an Invalid device function error. (#2656)
  • Fixed RandomBBoxCrop errors while using the crop_shape argument (#2605)

Improvements

  • Use pinned memory for staging buffer for HW nvJPEG decoder (#2655)
  • Find bounding boxes of multiple labels (#2650)
  • Add ROIRandomCrop operator (#2638)
  • Add FW iterators handling of variable batch size and improve ES examples (#2641)
  • Connected components (#2640)
  • Gridmask Cpu (#2582)
  • Iter-to-iter variable batch size (#2481)
  • Enable support for different layouts in the MelFilterBank (#2620)
  • Rework ops.random.CoinFlip (#2577)
  • Enable time-major layout in Spectrogram CPU (#2619)
  • Update clang format (#2524)
  • Improve Optical Flow error verbosity (#2618)
  • TF dataset tests rework (#2539)
  • Time major Spectrogram (GPU-only) (#2617)
  • Integrate RMM (#2609)
  • Propagate scalar in transform.scale (#2581)
  • Remove redundant JPEG decoder initialization from peeking shape function (#2610)
  • Rework ops.random.Uniform (#2531)
  • Rework custom operator docs (#2568)

Bug fixes

  • Workaround a compiler problem that caused Invalid device function error. (#2656)
  • Python fixes: argument inputs, external source, docs (#2646)
  • Fix SeparateQueuePolicy handling of the CPU stage (#2636)
  • Fix variable batch size for list of tensors. Make constants constant again. (#2637)
  • Fix Uniform discrete distribution (#2635)
  • Fix a double set of preserve schema arg and uninitialized var (#2632)
  • Add handling of empty inputs and tiny outputs in Resize op and Resampling kernels. (#2634)
  • Refactor functions that extract a range of samples from TLS and TLV. (#2628)
  • Fix RandomBBoxCrop errors while using crop_shape argument (#2605)
  • Update ResNet50 example to work with TensorFlow 2.x (#2537)
  • Keep reference to owner of data in Python Tensor and TensorList (#2606)
  • Enable nvJPEG2K for CUDA 11.2 builds (#2614)
  • Disable mmap based test for Xavier (#2612)
  • Fix length reported by DALI FW iterators when DROP policy is used (#2611)
  • Use smaller block in Warp (#2613)

Breaking API changes

Deprecated features

  • ops.Uniform was moved to ops.random.Uniform
  • ops.CoinFlip was moved to ops.random.CoinFlip

Known issues:

  • The video loader operator requires that the key frames occur at a minimum every 10 to 15 frames of the video stream. If the key frames occur at a lesser frequency, then the returned frames may be out of sync.
  • The DALI TensorFlow plugin might not be compatible with TensorFlow versions 1.15.0 and later.
    To use DALI with the TensorFlow version that does not have a prebuilt plugin binary shipped with DALI, make sure that the compiler that is used to build TensorFlow exists on the system during the plugin installation. (Depending on the particular version, use GCC 4.8.4, GCC 4.8.5, or GCC 5.4.)
  • Due to some known issues with meltdown/spectra mitigations and DALI, DALI shows best performance when run in Docker with escalated privileges, for example:
    • privileged=yes in Extra Settings for AWS data points
    • --privileged or --security-opt seccomp=unconfined for bare Docker

Binary builds

Install via pip for CUDA 10:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda100==0.31.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda100==0.31.0

or for CUDA 11:

CUDA 11.0 build uses CUDA toolkit enhanced compatibility. It is built with the latest CUDA 11.x toolkit
while it can run on the latest, stable CUDA 11.0 capable drivers (450.80 or later). 
Using the latest driver may enable additional functionality. 
More details can be found in enhanced CUDA compatibility guide.

pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda110==0.31.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda110==0.31.0

Or use direct download links (CUDA 10.0):

Or use direct download links (CUDA 11.0):

FFmpeg source code:

  • This software uses code of FFmpeg licensed under the LGPLv2.1 and its source can be downloaded here

Libsndfile source code:

Loading

DALI v0.30.0

27 Jan 17:28
@klecki klecki
v0.30.0
ab7489a
Compare
Choose a tag to compare
DALI v0.30.0

Key Features and Enhancements

This DALI release includes the following key features and enhancements.

  • Optimized CPU resampling (#2540).
  • Added the following mathematical expressions:
    • Disallowed unwanted __bool__ conversions (#2538).
    • Added exp and log math functions (#2555).
  • Added the images argument for the COCOReader, which allows for the custom ordering of images and fixed a bug in the segmentation data parsing (#2548, #2597).
  • Added support for the nvJPEG preallocate API for a batched hardware decoder (#2544).
  • Added support surfaces with strides over 2G (#2600).
  • Enabled CUDA 11.2 builds (#2553).
  • Documentation improvements:
    • Added a supported matrix to the documentation (#2519).
    • Added a geometric transform tutorial. (#2530).
  • Allowed DALI to be compiled with Clang (#2416).
  • Added CUDA API checks in utility functions (#2517) and tests (#2516).

Fixed issues

  • Fixed the autoreset option in the iterator for the DROP policy (#2567).

Improvements

  • Make Nvjpeg2kTest more verbose (#2509)
  • Compile DALI with Clang (#2416)
  • Try to actually find the library instead of arbitrarily deciding it can't be there (#2511)
  • Enable GDS for conda build by default (#2515)
  • Pool memory resource (#2518)
  • Add GTest Event Listener with CUDA validation after TEST (#2516)
  • Disable GPU numpy reader test form sm < 6.0 (#2514)
  • Mention WarpAffine in transforms.* documentation (#2527)
  • Ops rework to prepare iter-to-iter batch size variability (#2408)
  • Fix unchecked CUDA API calls in utility functions (#2517)
  • Bump up nvidia-tensorflow version in tests (#2526)
  • Cleanup warnings in CUDA code (#2523)
  • Add debug info to RN50 pipeline (#2522)
  • Add a supported matrix to the documentation (#2519)
  • Add ArgValue utility (#2528)
  • Remove pinning numpy version in TL1_ssd_training test (#2536)
  • Remove unreachable return statement (#2541)
  • Vectorize CPU resampling (#2540)
  • Remove constraint on input type for RandomResizedCrop. Update tests. (#2549)
  • Hide ArithmeticGenericOp doc and disallow bool (#2538)
  • Support for nvJPEG preallocate API for batched HW decoder (#2544)
  • Add exp and log math functions (#2555)
  • Add COCOReader files arg support and fix bug in the segmentation data parsing (#2548)
  • Event pool (#2520)
  • Rework random number generators. RNGBase operator template and NormalDistribution. (#2513)
  • Enable CUDA 11.2 builds (#2553)
  • Adjust range of tested log inputs (#2564)
  • Add geometric transform tutorial. (#2530)
  • Add synchronization after randomizer construction. (#2565)
  • Move to the upstream version of paddle paddle (#2561)
  • Move examples to fn api (#2566)
  • Remove legacy API based nvJPEG decoder implementation (#2591)
  • Support surfaces with strides over 2G (#2600)
  • COCOReader images argument can be used to provide a custom order of images (#2597)

Bug fixes

  • Fix build for Jetson platform (#2512)
  • Fix aarch64 build errors (#2529)
  • Fix broken uniform operator python tests (#2556)
  • Fix Clang build (#2560)
  • Fix Xavier test crash caused by NumPy faulty build (#2596)
  • Fix autoreset option in iterator for DROP policy (#2567)
  • Fix uniform distribution test expectations (#2589)

Breaking API changes

Deprecated features

Known issues:

  • The video loader operator requires that the key frames occur at a minimum every 10 to 15 frames of the video stream. If the key frames occur at a lesser frequency, then the returned frames may be out of sync.
  • The DALI TensorFlow plugin might not be compatible with TensorFlow versions 1.15.0 and later.
    To use DALI with the TensorFlow version that does not have a prebuilt plugin binary shipped with DALI, make sure that the compiler that is used to build TensorFlow exists on the system during the plugin installation. (Depending on the particular version, use GCC 4.8.4, GCC 4.8.5, or GCC 5.4.)
  • Due to some known issues with meltdown/spectra mitigations and DALI, DALI shows best performance when run in Docker with escalated privileges, for example:
    • privileged=yes in Extra Settings for AWS data points
    • --privileged or --security-opt seccomp=unconfined for bare Docker

Binary builds

Install via pip for CUDA 10:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda100==0.30.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda100==0.30.0

or for CUDA 11:

CUDA 11.0 build uses CUDA toolkit enhanced compatibility. It is built with the latest CUDA 11.x toolkit
while it can run on the latest, stable CUDA 11.0 capable drivers (450.80 or later). 
Using the latest driver may enable additional functionality. 
More details can be found in enhanced CUDA compatibility guide.

pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda110==0.30.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda110==0.30.0

Or use direct download links (CUDA 10.0):

Or use direct download links (CUDA 11.0):

FFmpeg source code:

  • This software uses code of FFmpeg licensed under the LGPLv2.1 and its source can be downloaded here

Libsndfile source code:

Loading

DALI v0.29.0

30 Dec 12:56
@jantonguirao jantonguirao
v0.29.0
2a85811
Compare
Choose a tag to compare
DALI v0.29.0

Key Features and Enhancements

This DALI release includes the following key features and enhancements.

  • New operators:
    • NumpyReader GPU Operator with the support of GPU Direct Storage (#2477)
    • NvJpeg2K decoding was enabled in ImageDecoder operator (#2501)
    • segmentation.RandomMaskPixel operator for creating random masks containing foreground pixels (#2445)
    • OneHot for GPU (#2436)
  • Move all NVTX infrastructure into core and create DALI domain (#2472)
  • New Examples:
    • Add mask processing to COCO Reader with Augmentations example (#2426)
    • Add reductions example (#2457)
    • Example of random_mask_pixel to perform biased random crop (#2474)
    • Update ExternalSource framework examples (#2482)
  • Operator Improvements:
    • Pad: Add support for per-sample shape and alignment requirements (#2432)
    • RandomResizedCrop: enable channel-first and video support + add tests (#2430)
    • PythonFunction Operator: support for output layouts (#2486)
    • Optimize the DCT GPU kernel. (#2471)
    • COCOReader: Support for uncompressed RLE masks (#2478)
    • transforms.Rotation to accept scalar inputs (#2494)
  • Move to CUDA 11.1 update 1 (#2419)

Fixed issues

  • NumpyReader : Replace std::regex with custom implementation (#2489) - fix ABI incompatibility issues
  • Fix the dimensionality of labels in SSDRandomCrop. (#2488)

Improvements

  • Move to CUDA 11.1 update 1 (#2419)
  • RandomResizedCrop: enable channel-first and video support + add tests (#2430)
  • Pad operator: Add support for per-sample shape and alignment requirements (#2432)
  • Update clang to 10.0 (#2424)
  • Add mask processing to COCO Reader with Augmentations example (#2426)
  • Make custom nvJEPG allocator return a relevant allocation status (#2438)
  • Make the custom nvJPEG allocator not throw and return only the status (#2443)
  • Add SearchableRLEMask utility (#2441)
  • Add GPU support to OneHot operator (#2436)
  • Reduce axes names (#2425)
  • Remove CUDA headers and generate stubs in runtime (#2420)
  • TensorVector update for iter-to-iter variable batch size (#2435)
  • Fix build with all options off, relax libclang required version (#2455)
  • Add support for UINT8 and INT8 outputs in CMN + scale and shift arguments (#2458)
  • CocoReader Parse RLE masks only when piwelwise masks are requested (#2462)
  • Add reductions example (#2457)
  • Enables direct linking with libcuda.so instead of dlopen (#2459)
  • Add segmentation.RandomMaskPixel operator (#2445)
  • Skips the building of prebuilt DALI package for nvidia-tensorflow (#2451)
  • Pad to square tests (#2442)
  • Enable compile time generation of dynlink wrappers for nvml (#2463)
  • Deprecate squeeze_labels option from MXNet iterator and enhance .squeeze function to match numpy style interface (#2450)
  • Hide hidden ops and improve Enum docs quality (#2470)
  • Enforce uniform rank and type of the outputs read by CPU DataReader. (#2476)
  • Move all NVTX infrastructure into core and create DALI domain (#2472)
  • MXNet Iterator: Revert to squeeze_labels=True behavior by default (#2479)
  • Example of random_mask_pixel to perform biased random crop (#2474)
  • Update DALI dependency (#2483)
  • Update ExternalSource framework examples (#2482)
  • Optimize the DCT GPU kernel. (#2471)
  • Support the output layouts in the PythonFunction Operator (#2486)
  • transforms.Rotation to accept scalar inputs (#2494)
  • Rework tutorials general (#2480)
  • Add support for GPU based numpy reader (#2477)
  • Per sample ExternalSource (#2469)
  • Use atol instead of rtol (#2499)
  • Lifts the restriction and enables enable_frame_num and enable_timestamps for filenames (#2468)
  • Reenable nvJPEG2000 (#2501)
  • Disables GDS for the default build configuration (#2502)
  • COCOReader: Support for uncompressed RLE masks (#2478)
  • Memory manager - interfaces, utilities, monotonic resources, malloc resource (#2497)
  • Update Jetson compilation guide (#2508)
  • Makes sure that cuFile and nvJPEG2k are not possible to set when not supported (#2510)

Bug fixes

  • Fix seed in RandomResizedCrop test. (#2437)
  • QNX build fix (#2440)
  • Fix lack of proper loading of best_prec1 from the checkpoint (#2466)
  • Fix the dimensionality of labels in SSDRandomCrop. (#2488)
  • NumpyReader : Replace std::regex with custom implementation (#2489)
  • Fix CPU only mode in C API (#2496)
  • Fix bugs reported by static analysis (#2491)
  • Fix typo in STYLE_GUIDE.md (#2503)
  • Fix NVJPEG2K_ENABLED test macros (#2504)

Breaking API changes

Deprecated features

  • Deprecate squeeze_labels option from MXNet iterator and enhance .squeeze function to match numpy style interface (#2450)

Known issues:

  • The video loader operator requires that the key frames occur at a minimum every 10 to 15 frames of the video stream. If the key frames occur at a lesser frequency, then the returned frames may be out of sync.
  • The DALI TensorFlow plugin might not be compatible with TensorFlow versions 1.15.0 and later.
    To use DALI with the TensorFlow version that does not have a prebuilt plugin binary shipped with DALI, make sure that the compiler that is used to build TensorFlow exists on the system during the plugin installation. (Depending on the particular version, use GCC 4.8.4, GCC 4.8.5, or GCC 5.4.)
  • Due to some known issues with meltdown/spectra mitigations and DALI, DALI shows best performance when run in Docker with escalated privileges, for example:
    • privileged=yes in Extra Settings for AWS data points
    • --privileged or --security-opt seccomp=unconfined for bare Docker

Binary builds

Install via pip for CUDA 10
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda100==0.29.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda100==0.29.0

or for CUDA 11:

CUDA 11.0 build uses CUDA toolkit enhanced compatibility. It is built with the latest CUDA 11.x toolkit while it can run on the latest, stable CUDA 11.0 capable drivers (450.80 or later). Using the latest driver may enable additional functionality. More details can be found in enhanced CUDA compatibility guide.

pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda110==0.29.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda110==0.29.0

Or use direct download links (CUDA 10.0):

Or use direct download links (CUDA 11.0):

FFmpeg source code:

  • This software uses code of FFmpeg licensed under the LGPLv2.1 and its source can be downloaded here

Libsndfile source code:

Loading

DALI v0.28.0

30 Nov 15:46
@klecki klecki
v0.28.0
49192e4
Compare
Choose a tag to compare
DALI v0.28.0

Key Features and Enhancements

This DALI release includes the following key features and enhancements.

  • New operators:
    • Affine transform generators, which are operators that generate scale, rotate, shear, translate, crop transform matrices (#2309).
      • You can use the transforms.Combine operator to combine these matrices (#2317).
      • These transformations can be applied to data by using the CoordTransform operator.
    • Added min, max, and clamp arithmetic operators (#2298).
    • Cat and Stack Operators to concatenate and stack Tensors for the CPU and the GPU (#2301, #2339, #2350).
    • The following reductions for the CPU and the GPU (#2342, #2379 #2395):
      • Min, Max, Sum, Mean, MeanSquare, RootMeanSquare, Std, Variance
    • The MFCC operator for the GPU (#2423).
    • The SelectMasks operator (#2381).
    • Add operators for batch reordering:
      • BatchPermutation for generating random reordering of the batch.
      • PermuteBatch, which reorders tensors in a batch, based on a list of provided indices (#2417).
    • Operator Compose: PyTorch-style API to compose the operators (#2393).
  • Improvements in existing operators:
    • Added SeekFrames to the audio decoder. The redesign allows you to decide the decoded data type at runtime (#2334).
    • Added the ability to handle UTF8 text to the NemoAsrReader (#2358).
    • Added explicit file list support to the FileReader (#2389).
    • Improvements in the COCO reader API (#2406).
      • The COCOReader API now outputs relative mask polygon coordinates when the option ratio is set to True (#2375).
    • RandomBBoxCrop now optionally outputs the indices of the bounding boxes that passed the centroid filter (#2374).
  • The late initialization of torch_gpu_device in the Pytorch plugin (#2411).
  • The automatic constant-to-input promotion (#2361) and generalized handling of operator arguments (#2393).
  • Added a MNIST example for DALI and PyTorch Lightning (#2360).
  • Added the last_batch_policy to the framework iterator (#2269).
  • New builds:
    • Python 3.9 is now enabled (#2333).
    • The DALI wheels for CUDA 11 are built with CUDA 11.1 and use Enhanced Compatibility to work with CUDA 11.0 (#2302, #2356, #2367, and #2413).
    • Added support for the SM_86 architecture (#2364).
    • Added the ability to cross-build Python wheels for Jetson (#2313).

Bug fixes

  • Fix error when VideoReader is prematurely terminated (#2336)
  • Fix failure in affine transforms tests (#2337)
  • Fix the problem of output outliving the pipeline in python (#2341)
  • Fix lack of proper layout setting in the VideoReader (#2346)
  • Fix uniform generator operator (#2352)
  • Bugfixes: Default nfft value and to_snake_case implementation (#2353)
  • Fixes problems in the weekly build (#2372)
  • Fix a problem with reference to "incomplete" type (error in Clang/CUDA). (#2377)
  • Fix how DALI handles StopIteration from the ExternalSource (#2373)
  • Fix TL1_nodeps_build and TL0_cpu_only (#2391)
  • Fix CPU only mode for arithm operators (#2400)
  • Preserve shape of psuedoscalars in arithmetic ops. (#2359)

Improvements

  • Add affine transform generators: TransformScale, TransformRotation, TransformShear, TransformCrop (#2309)
  • Change code/docs language to be more inclusive (#2322)
  • Update nvidia-tensorflow test package to 20.9 and bump tensorflow-gpu minor versions (#2320)
  • Update example usage of DALIClassificationIterator in docs strings (#2306)
  • Reduce video reader memory consumption (#2308)
  • TensorJoin kernel for CPU (#2301)
  • Enable automatic python modules for operator (#2329)
  • Split GaussianBlur Python test (#2332)
  • Add CombineTransforms operator (#2317)
  • Append TensorListShapes (#2291)
  • Enable CUDA 11.1 builds (#2302)
  • Add min, max and clamp arithmetic ops (#2298)
  • Update TensorFlow plugin documentation (#2328)
  • Remove Python 3.5 support, enable Python 3.9 (#2333)
  • Enable nvJPEG2k build for CUDA 11.1 (#2343)
  • Add BUILD_DALI_NODEPS to allow building dali_core and dali_kernels without extra third party libraries present in the system (#2321)
  • Add SeekFrames to audio decoder. Redesign to allow deciding decoded data type at runtime. (#2334)
  • Add discrete mode to Uniform operator (#2340)
  • Test for utility CMake function (find_dali) (#2325)
  • Propagate new build options to other build utilities (#2349)
  • Add support for N-dim tensors to OneHot (#2345)
  • Adds a separate option to preallocate nvjPEG2k memory (#2347)
  • Tensor join GPU (#2339)
  • Reductions: min, max (#2342)
  • Tensor concatenation and stacking (#2350)
  • Use inverse (source-to-destination) matrix in WarpAffine operator (#2338)
  • Disable more dependencies for nodeps build (#2355)
  • Update DALI trademark information (#2351)
  • Reduce GPU memory fraction in TF tests to 0.5. (#2357)
  • Automatic constant-to-input promotion. (#2361)
  • Add support for SM_86 architecture (#2364)
  • Use current class next implementation in init, to avoid special handling of first batch in child classes (#2363)
  • Add ability to cross-build Python wheels for Jetson (#2313)
  • Add NemoAsrReader handling of UTF8 text (#2358)
  • Enable CUDA 11 compatibility mode (#2356)
  • Add MNIST example for DALI and PyTorch Lightning (#2360)
  • Add last_batch_policy to the framework iterator (#2269)
  • COCOReader to output relative mask polygon coordinates when the option ratio is set to True (#2375)
  • RandomBBoxCrop to optionally output the indices of the bounding boxes that passed the centroid filter (#2374)
  • Enable compatibility layer in tests for CUDA 11 (#2367)
  • Reduce Sum Op (#2379)
  • Install DALI license, copyright and acknowledgments explicitly (#2392)
  • Add layout support to OneHot operator (#2388)
  • Generalized handling of operator arguments + operator Compose. (#2393)
  • GPU DCT kernel (#2398)
  • Bump up Nvidia TF version to 20.10 (#2397)
  • More reductions (#2395)
  • Late initialization of torch_gpu_device in pytorch plugin (#2411)
  • Add a link to CUDA Enhanced Compatibility Across Minor Releases guide (#2410)
  • Add explicit file list support to FileReader. (#2389)
  • Add TransformTranslation deprecation placeholder Op (#2412)
  • Bump up the CuPy to one that supports CUDA 11.0 (#2413)
  • Add a missing include in filesystem.cc (#2414)
  • Add a warning about the Python function incompatibility with TensorFlow (#2415)
  • Improvements in COCO reader API (#2406)
  • Add operators for batch reordering (#2417)
  • Add SelectMasks operator (#2381)
  • GPU MFCC operator. (#2423)
  • Make base image for dockers customizable at the build time (#2427)

Breaking API changes

  • Python 3.5 is no longer supported by the official DALI wheels.

Deprecated feature

Known issues:

  • The video loader operator requires that the key frames occur at a minimum every 10 to 15 frames of the video stream. If the key frames occur at a lesser frequency, then the returned frames may be out of sync.
  • The DALI TensorFlow plugin might not be compatible with TensorFlow versions 1.15.0 and later.
    To use DALI with the TensorFlow version that does not have a prebuilt plugin binary shipped with DALI, make sure that the compiler that is used to build TensorFlow exists on the system during the plugin installation. (Depending on the particular version, use GCC 4.8.4, GCC 4.8.5, or GCC 5.4.)
  • Due to some known issues with meltdown/spectra mitigations and DALI, DALI shows best performance when run in Docker with escalated privileges, for example:
    • privileged=yes in Extra Settings for AWS data points
    • --privileged or --security-opt seccomp=unconfined for bare Docker

Binary builds

Install via pip for CUDA 10
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda100==0.28.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda100==0.28.0

or for CUDA 11:

CUDA 11.0 build uses CUDA toolkit enhanced compatibility. It is built with the latest CUDA 11.x toolkit while it can run on the latest, stable CUDA 11.0 capable drivers (450.80 or later). Using the latest driver may enable additional functionality. More details can be found in enhanced CUDA compatibility guide.

pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda110==0.28.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda110==0.28.0

Or use direct download links (CUDA 10.0):

Or use direct download links (CUDA 11.0):

FFmpeg source code:

  • This software uses code of FFmpeg licensed under the LGPLv2.1 and its source can be downloaded here

Libsndfile source code:

Loading

DALI v0.27.0

29 Oct 16:32
@klecki klecki
v0.27.0
511c22e
This commit was created on GitHub.com and signed with GitHub’s verified signature. The key has expired.
GPG key ID: 4AEE18F83AFDEB23
Expired
Verified
Learn about vigilant mode.
Compare
Choose a tag to compare
DALI v0.27.0

Key Features and Enhancements

This DALI release includes the following key features and enhancements.

  • New operators:
    • CoordTransform Operator for applying a linear transformation to points or vectors (#2288)
    • GaussianBlur Gpu Operator (#2314, #2311, #2254)
    • Nemo ASR Reader (#2234)
    • Resize 3D - operator can now process 3D inputs (#2226)
    • Add Translate affine transform generator (#2297) - in the next release it will be moved to a dedicated module.
  • Use true scalars (except in classification readers) - 0-dim Tensors represent scalar values (#2318)
  • Adjust documentation after review (#2175)
  • Support for ZSTD compression for TIFF files (#2273)
  • Support for Run-Length Encodings and Pixelwise Masks in COCO Reader (#2248)
  • Support more types in Lookup table (#2290)

Bug fixes

  • Fixes crash in RandomBBoxCrop when no labels are provided (#2265)
  • Fix minor issues reported by static analysis (#2276)
  • Fix detection pipeline test on Ampere (#2304)
  • Fix BUILD_LIBSND=OFF build (#2316)
  • Fix build for LMDB disabled (#2319)

Improvements

  • Update build and test deps to the latest version (#2250)
  • Resize 3D + resize tests (#2226)
  • Allow passing a <= 0 values in the file list to allow more flexible frame indexing (#2264)
  • Extend host decoder to support jpeg2000 (#2270)
  • Add file_list argument support to the Numpy reader operator (#2274)
  • Allow Slice to silently assume absolute anchor and shape when those are represented by an integer (#2282)
  • TransformPoints kernel (#2287)
  • Add inline to LookaheadParser methods (#2289)
  • Add deprecation handling in backend (#2279)
  • Support more types in Lookup table (#2290)
  • Adjust documentation after review (#2175)
  • Transform points op (#2288)
  • Support for ZSTD compression for TIFF files (#2273)
  • Support for Run-Length Encodings and Pixelwise Masks in COCO Reader (#2248)
  • Extract a DecodeAudio implementation from Audio decoder operator (#2294)
  • Extend test_RN50_data_pipeline.py test (#2295)
  • Add ConvolutionGPU kernel based on CUTLASS (#2254)
  • Add Translate affine transform generator (#2297)
  • Add *.cuh and *.inl to list of headers to bundle (#2307)
  • Add Nemo ASR reader (#2234)
  • Add SeprableConvolutionGPU kernel (#2311)
  • Add GaussianBlur Gpu Operator (#2314)
  • Use true scalars (except in classification readers) + bug fixes (#2318)
  • Add nvjpeg2k support to GPU Image Decoder. Extend nvjpeg memory pool to support nvjpeg2k allocators.
  • Adds a separate option to preallocate nvjPEG2k memory (#2347)
  • Due to some decoding problems disable nvJPEG2K support for now by the default

Breaking API changes

Deprecated feature

Known issues:

  • The video loader operator requires that the key frames occur at a minimum every 10 to 15 frames of the video stream. If the key frames occur at a lesser frequency, then the returned frames may be out of sync.
  • The DALI TensorFlow plugin might not be compatible with TensorFlow versions 1.15.0 and later.
    To use DALI with the TensorFlow version that does not have a prebuilt plugin binary shipped with DALI, make sure that the compiler that is used to build TensorFlow exists on the system during the plugin installation. (Depending on the particular version, use GCC 4.8.4, GCC 4.8.5, or GCC 5.4.)
  • Due to some known issues with meltdown/spectra mitigations and DALI, DALI shows best performance when run in Docker with escalated privileges, for example:
    • privileged=yes in Extra Settings for AWS data points
    • --privileged or --security-opt seccomp=unconfined for bare Docker

Binary builds

Install via pip for CUDA 10
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda100==0.27.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda100==0.27.0

or for CUDA 11:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda110==0.27.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda110==0.27.0

Or use direct download links (CUDA 10.0):

Or use direct download links (CUDA 11.0):

FFmpeg source code:

  • This software uses code of FFmpeg licensed under the LGPLv2.1 and its source can be downloaded here

Libsndfile source code:

Loading

DALI 0.25.1

11 Sep 11:22
@klecki klecki
v0.25.1
db2c06f
Compare
Choose a tag to compare
DALI 0.25.1

Key Features and Enhancements

This is a patch release that contains only fixes.

Bug fixes

  • Fixed a crash that occurred when DALI CUDA 11 runs on pre 450.x driver with the compatibility layer (#2208, #2230).

Known issues

  • The video loader operator requires that the key frames occur at a minimum every 10 to 15 frames of the video stream. If the key frames occur at a lesser frequency, then the returned frames may be out of sync.
  • The DALI TensorFlow plugin might not be compatible with TensorFlow versions 1.15.0 and later.
    To use DALI with the TensorFlow version that does not have a prebuilt plugin binary shipped with DALI, make sure that the compiler that is used to build TensorFlow exists on the system during the plugin installation. (Depending on the particular version, use GCC 4.8.4, GCC 4.8.5, or GCC 5.4.)
  • Due to some known issues with meltdown/spectra mitigations and DALI, DALI shows best performance when run in Docker with escalated privileges, for example:
    • privileged=yes in Extra Settings for AWS data points
    • --privileged or --security-opt seccomp=unconfined for bare Docker

Binary builds

Install via pip for CUDA 10
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda100==0.25.1
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda100==0.25.1

or for CUDA 11:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda110==0.25.1
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda110==0.25.1

Or use direct download links (CUDA 10.0):

Or use direct download links (CUDA 11.0):

SBSA aarch64 CUDA 11.0 direct download link:

FFmpeg source code:

  • This software uses code of FFmpeg licensed under the LGPLv2.1 and its source can be downloaded here

Libsndfile source code:

Loading

DALI v0.26.0

29 Sep 12:30
@klecki klecki
v0.26.0
1e91967
Compare
Choose a tag to compare
DALI v0.26.0

Key Features and Enhancements

This DALI release includes the following key features and enhancements.

  • New operators:
    • Add PeekShape operator to learn the decoded image shape (#2205)
  • Add an ability to run DALI without GPU (#2165)
  • Optimize single-channel audio resampling with SSE2 (#2240)
  • Add ability to pass DALI TensorList or a list of DALI Tensors to exernal source (#2244)
  • Enhance error messages in case of not supported data types in operators (#2211)
  • Add a more verbose message about unsupported videos (#2203)
  • Use copy kernel when making a contiguous batch during ShareUserData, if user requested it (#2200)

Bug fixes

  • Fix typo in VERSION
  • Fix lack of input type checking in GPU variant of Spectrogram operator (#2192)
  • Fix TensorListView::to_static (#2216)
  • Temporarily freeze protobuf packages versions in Conda (#2222)
  • Fix VideoReader error checking when opening files (#2223)
  • Fix NVTX annotations (#2215)
  • Fix docker/build.sh to use Python 3 for TF plugin (#2214)
  • Fix hw_decoder_load=0.0 for ImageDecoder related tests that require deterministic results (#2232)
  • Fix a memory leak in the audio decoder (#2235)
  • Fix for TF nightly container (#2236)
  • Fix wrong jupyter execution syntax (#2241)
  • Fix TL1_ssd_training test (#2243)

Improvements

  • Use copy kernel when making a contiguous batch during ShareUserData, if user requested it (#2200)
  • Update ExternalSource documentation (#2201)
  • Use NVCC to detect cuda release version (#2194)
  • DALI TF stop requiring DALI to be installed before build_ext step (#2204)
  • Add PeekShape operator to learn the decoded image shape (#2205)
  • Remove dummy package (#2207)
  • Add a more verbose message about unsupported videos (#2203)
  • Enhance error messages in case of not supported data types in operators (#2211)
  • Add more supported types to SliceBase (#2210)
  • Add an ability to run DALI without GPU (#2165)
  • Add CUTLASS to third party with an initial code layout (#2237)
  • Make the CUTLASS template files pass lint check (#2238)
  • Use SSE2 for single-channel audio resampling (#2240)
  • Add nvidia-tensorflow to DALI tests (#2075)
  • Update APEX version to the latest stable and tested version (#2246)
  • Fuzzing targets (#2219)
  • Add ability to pass DALI TensorList or a list of DALI Tensors to exernal source (#2244)
  • 3D resampling (#1489)
  • Skip VP9 tests instead of failing if codec is not supported. (#2251)

Breaking API changes

Deprecated feature

Known issues:

  • The video loader operator requires that the key frames occur at a minimum every 10 to 15 frames of the video stream. If the key frames occur at a lesser frequency, then the returned frames may be out of sync.
  • The DALI TensorFlow plugin might not be compatible with TensorFlow versions 1.15.0 and later.
    To use DALI with the TensorFlow version that does not have a prebuilt plugin binary shipped with DALI, make sure that the compiler that is used to build TensorFlow exists on the system during the plugin installation. (Depending on the particular version, use GCC 4.8.4, GCC 4.8.5, or GCC 5.4.)
  • Due to some known issues with meltdown/spectra mitigations and DALI, DALI shows best performance when run in Docker with escalated privileges, for example:
    • privileged=yes in Extra Settings for AWS data points
    • --privileged or --security-opt seccomp=unconfined for bare Docker

Binary builds

Install via pip for CUDA 10
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda100==0.26.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda100==0.26.0

or for CUDA 11:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda110==0.26.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda110==0.26.0

Or use direct download links (CUDA 10.0):

Or use direct download links (CUDA 11.0):

FFmpeg source code:

  • This software uses code of FFmpeg licensed under the LGPLv2.1 and its source can be downloaded here

Libsndfile source code:

Loading

DALI v0.25.0

28 Aug 20:02
@klecki klecki
v0.25.0
5f0c12c
Compare
Choose a tag to compare
DALI v0.25.0

Key Features and Enhancements

This DALI release includes the following key features and enhancements.

  • Added support for aarch64 Server Base System Architecture (#2110) - we provide a build for CUDA 11 that can be installed following the installation guide.
  • New operators:
    • Normal Distribution GPU Operator (#2125)
    • Video reader resize (#2097)
  • Improvements to ExternalSource Op:
    • Added the no_copy option, which allows DALI to borrow a user's memory instead of copying it (#2024).
    • Removed the redundant copy in the ExternalSource operator (#2124)
  • Reworked the Resize operator family, including video, channel-first, RoI, and multiple-type support (#2164) with the new Resize tutorial (#2189).
  • Bundled all python versions into one wheel (#2096).
    • One DALI wheel can be used with all supported Python versions, including 3.5, 3.6, 3.7 and 3.8.
  • Improved error messages and added information about the Operator of origin (#2065).
  • Extended the following C APIs to copy output and input samples:
    • daliOutputCopy (#2145) and daliOutputCopySamples (#2161, #2186).
    • These APIs allow you to use the copy kernel and reduce the amount of copied memory and to use the copy kernel in ShareUserData (#2200).
  • Performance improvements:
    • Arithmetic Ops GPU (#2137)
    • Priorities in CPU thread pool allowing for better load balancing with uneven samples (#2092, #2102)

Bug fixes

  • Fix aarch64 builds that are still gcc 5.x based (#2099)
  • Fix conda build after the new build of libprotobuf was released (#2101)
  • Fix the lack of setting the right device in the ExternalSource (#2112)
  • Fix lack of a proper include to set CUDART_VERSION inside nvml.h and nvml_wrap.h (#2113)
  • Fix layout propagation in Gaussian Blur (#2118)
  • Fix layout propagation in Erase (#2133)
  • Fix TF dataset notebook (#2135)
  • Fix lack of MXNet plugin docs generation (#2146)
  • Fix TL3_RN50_convergence test for PaddlePaddle (#2159)
  • Workaround a bug in compiler, magically converting instance call to static call. (#2162)
  • Fix the need to have a numpy installed when test_utils.py is just imported (#2166)
  • Fix missing layouts in operators (#2136)
  • Fix QNX build (#2199)

Improvements

  • Update to CUDA 11 GA toolkit (#2094)
  • Allow nvJPEG to pre-allocate pinned and device buffers during construction (#2081)
  • Add zero-copy to the ExternalSource operator (#2024)
  • Introduce priorities in ThreadPool (#2092)
  • Video reader resize (#2097)
  • Detect version of CUDA based on libcudart.so.* name (#2105)
  • Add Operator origin information to most errors (#2065)
  • Enhance Pad documentation (#2098)
  • Bundle all python versions into one wheel (#2096)
  • Use new nvmlDeviceGetCpuAffinityWithinScope API for thread binding (#2093)
  • Use new ThreadPool API to post work with priority (#2102)
  • TensorListView generalized reshape and reinterpret (#2108)
  • Update aarch64_linux build to Jetpack 4.4 and CUDA 10.2 (#2107)
  • Renable VP9 video tests after driver update (#2117)
  • Remove usage of future from DALI (#2119)
  • Removes redundant copy in ExternalSource operator (#2124)
  • Add more verbose info when HwDecoderUtilizationTest is skipped (#2106)
  • Per-stream/per-device object pool. (#2127)
  • Fix PaddlePaddle test broken by rarfile update not compatible with Python 3.5 (#2130)
  • Add missing and a partial check in linter for this include file. (#2131)
  • Add libprotobuf-static as DALI conda build dependency (#2132)
  • Auto apply dataset options (#1963)
  • Add an option to use a copy kernel to feed external input (#2122)
  • Adjust mel filter test to librosa change (#2144)
  • Add dependency to dali_kernels to dali lib (#2143)
  • Tune Arithmetic Op launch specification (#2137)
  • Add daliOutputCopy (#2145)
  • Reduce memory usage in VideoReadeResize test (#2149)
  • Normal Distribution GPU Operator (#2125)
  • Remove pinning of numba version as librosa 0.8.0 has been released (#2151)
  • Add an ability to suppress _iterator_deprecation_warning (#2154)
  • Span-of-arrays flattening + minor layout utils (#2156)
  • Remove deprecated use of ltrb in BboxRandomCrop (#2141)
  • Improve PyTorch and MXNet ExternalSource examples (#2147)
  • Enable DALI build and tests for SBSA (#2110)
  • Add --disable-mmap flag to RN50 data pipeline test (#2163)
  • Make TF dataset build for 2.3.0 (#2160)
  • Enforce recordio indices are not empty (#2157)
  • Add daliOutputCopySamples (#2161)
  • Use TIFFGetFieldDefaulted and remove warning about falling back to GenericImage decoder (#2153)
  • Add an information about the faulty image to CreateImage invocation in nvjpeg_decoder_decoupled_api.h (#2174)
  • Add proper error handling where there are no valid sequences in the VideoReader (#2180)
  • Update instruction how run ResNet50 example for PyTorch (#2170)
  • Add the possibility to skip individual samples when using daliOutputCopySamples (#2186)
  • Change DALI build command to use minor CUDA version as well (#2155)
  • Reworked Resize operator family - video, channel-first, RoI and multiple type support (#2164)
  • Move to Update 1 release of CUDA 11 toolkit (#2188)
  • Make the test deterministically pick video files. (#2190)
  • Resize tutorial (#2189)
  • Use copy kernel when making a contiguous batch during ShareUserData, if user requested it (#2200)

Breaking API changes

  • Remove deprecated use of ltrb in BboxRandomCrop (#2141)

Deprecated feature

Known issues:

  • The video loader operator requires that the key frames occur at a minimum every 10 to 15 frames of the video stream. If the key frames occur at a lesser frequency, then the returned frames may be out of sync.
  • The DALI TensorFlow plugin might not be compatible with TensorFlow versions 1.15.0 and later.
    To use DALI with the TensorFlow version that does not have a prebuilt plugin binary shipped with DALI, make sure that the compiler that is used to build TensorFlow exists on the system during the plugin installation. (Depending on the particular version, use GCC 4.8.4, GCC 4.8.5, or GCC 5.4.)
  • Due to some known issues with meltdown/spectra mitigations and DALI, DALI shows best performance when run in Docker with escalated privileges, for example:
    • privileged=yes in Extra Settings for AWS data points
    • --privileged or --security-opt seccomp=unconfined for bare Docker

Binary builds

Install via pip for CUDA 10
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda100==0.25.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda100==0.25.0

or for CUDA 11:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda110==0.25.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda110==0.25.0

Or use direct download links (CUDA 10.0):

Or use direct download links (CUDA 11.0):

FFmpeg source code:

  • This software uses code of FFmpeg licensed under the LGPLv2.1 and its source can be downloaded here

Libsndfile source code:

Loading