Releases · NVIDIA/DALI

27 Jan 17:28

klecki

v0.30.0

ab7489a

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:

https://developer.download.nvidia.com/compute/redist/nvidia-dali/libsndfile-1.0.28.tar.gz

Assets 2

30 Dec 12:56

jantonguirao

v0.29.0

2a85811

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:

https://developer.download.nvidia.com/compute/redist/nvidia-dali/libsndfile-1.0.28.tar.gz

Assets 2

30 Nov 15:46

klecki

v0.28.0

49192e4

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:

https://developer.download.nvidia.com/compute/redist/nvidia-dali/libsndfile-1.0.28.tar.gz

Assets 2

29 Oct 16:32

klecki

v0.27.0

511c22e

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:

https://developer.download.nvidia.com/compute/redist/nvidia-dali/libsndfile-1.0.28.tar.gz

Assets 2

11 Sep 11:22

klecki

v0.25.1

db2c06f

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:

https://developer.download.nvidia.com/compute/redist/nvidia-dali-cuda110/nvidia_dali_cuda110-0.25.1-1612461-py3-none-manylinux2014_aarch64.whl

FFmpeg source code:

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

Libsndfile source code:

https://developer.download.nvidia.com/compute/redist/nvidia-dali/libsndfile-1.0.28.tar.gz

Assets 2

29 Sep 12:30

klecki

v0.26.0

1e91967

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:

https://developer.download.nvidia.com/compute/redist/nvidia-dali/libsndfile-1.0.28.tar.gz

Assets 2

28 Aug 20:02

klecki

v0.25.0

5f0c12c

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:

https://developer.download.nvidia.com/compute/redist/nvidia-dali/libsndfile-1.0.28.tar.gz

Assets 2

29 Jul 17:20

klecki

v0.24.0

81f94e0

DALI v0.24.0

Key Features and Enhancements

This DALI release includes the following key features and enhancements.

New Operators:
- Preemphasis GPU (#2025).
- GaussianBlur CPU (#1987, #2009, #2038).
Operator Improvements:
- Extended the Slice and Crop family of operators with out-of-bounds policies, which provides support for padding and trimming to existing shape (#2000, #2056, #2044).
- Moved the memory hint allocation in the Resize to the build phase (#2033).
- Optimized the Transpose GPU operator to improve the performance on non-uniform data batches (#2011, #2032).
Support for GPU data input data in the ExternalSource operator (#1997).
- Added built-in support for GPU CuPy and PyTorch tensors in ExternalSource (#2050).
- Added the ability to provide an external stream, stream 0, or automatic stream selection for GPU data access (#2050).
- Added DLPack input support to the ExternalSource operator (#2023).
Add an ability to dump info about operator output buffer size (#2039)
Improved error checking with external libraries (#2062, #2063).

Bug fixes

Fix semantics of the masks_meta field (#2029)
Fix shape comparison in C API tests. (#2045)
Fix conda build after TensorFlow 2.2 release (#2048)
Fix Slice pad support when last dimension is padded (#2056)
Fix TL1_jupyter_conda test (#2058)
Fix CropMirrorNormalize benchmark (#2059)
Fix epoch_size method in the pipeline (#2071)
Undefined name: RuntimeErrorError --> RuntimeError (#2076)
Use ==/!= to compare constant literals (str, bytes, int, float, tuple) (#2078)
Fix Assertion is always true in Python tests (#2077)
Fix undefined name errors in Python reshape tests (#2079)
Fix conda build after the new build of libprotobuf was released (#2101)

Improvements

Add Convolution CPU kernel (#1987)
Lock numba version to 0.49 when librosa is used (#2016)
Add a deprecation warning for python 3.5 (#2021)
Change locked version of numba to at most 0.49, as 0.47 is the last release for py35 (#2020)
Add Preemphasis GPU operator (#2025)
Add out-of-bounds-policy (including pad support) to Slice/Crop (#2000)
Change from a custom manylinux3 to prebuild and upstream manylinux2014 (#1965)
Enable python ExternalSource operator for the GPU data (#1997)
Batched GPU transposition (#2011)
Move memory hint allocation in the Resize to the build phase (#2033)
Replace cuTT in Transpose operator with DALI kernel + move permute to core. (#2032)
Separable convolution (#2009)
Build DALI with OpenMP SIMD (#1992)
Use empty tensors for DL FW plugins instead of zeroed one (#2030)
Lanczos3 downscale + interp type notebook. (#2041)
Update docs layout template after sphinx_rtd_theme update (#2046)
Makes TF RN50 TL3 test to compile ahead of time (#2028)
Add an ability to dump info about operator output buffer size (#2039)
Add Gaussian window calculation for Gaussian Op (#2053)
Remove cuda 9 related packages from tests, update cupy to 7.5 (#2049)
Use Slice kernel to implement Pad operator (instead of SliceFlipNormalizePermutePad) (#2057)
Add PyTorch support in ExternalSource + fix handling of CUDA streams in Python frontend (#2050)
Add GaussianBlur CPU Op (#2038)
HW Decoder utilization test (#2022)
Add DLPack input support to the ExternalSource operator (#2023)
Add better return value/error status checks (#2062)
Check libjpeg return codes (#2063)
CropMirrorNormalize full pad support (#2044)
Remove confusing main from nosetest files (#2083)
Update to CUDA 11 GA toolkit (#2094)
Detect version of CUDA based on libcudart.so.* name (#2105)
Reduce Paddle RN50 test gpu mem fraction to 80% (#2152)

Breaking API changes

Deprecated feature

Added a deprecation warning for Python 3.5 (#2021).
Deprecated output_dtype and use dtype (#2051).
Added an argument deprecation mechanism and deprecated "image_type" in Crop, Slice, and CropMirrorNormalize (#2061).

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==0.24.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda100==0.24.0

or for CUDA 11:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda110==0.24.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda110==0.24.0

Or use direct download links (CUDA 10.0):

https://developer.download.nvidia.com/compute/redist/nvidia-dali-cuda100/nvidia_dali_cuda100-0.24.0-1446725-cp35-cp35m-manylinux2014_x86_64.whl
https://developer.download.nvidia.com/compute/redist/nvidia-dali-cuda100/nvidia_dali_cuda100-0.24.0-1446725-cp36-cp36m-manylinux2014_x86_64.whl
https://developer.download.nvidia.com/compute/redist/nvidia-dali-cuda100/nvidia_dali_cuda100-0.24.0-1446725-cp37-cp37m-manylinux2014_x86_64.whl
https://developer.download.nvidia.com/compute/redist/nvidia-dali-cuda100/nvidia_dali_cuda100-0.24.0-1446725-cp38-cp38-manylinux2014_x86_64.whl
https://developer.download.nvidia.com/compute/redist/nvidia-dali-tf-plugin-cuda100/nvidia-dali-tf-plugin-cuda100-0.24.0.tar.gz

Or use direct download links (CUDA 11.0):

https://developer.download.nvidia.com/compute/redist/nvidia-dali-cuda110/nvidia_dali_cuda110-0.24.0-1472979-cp35-cp35m-manylinux2014_x86_64.whl
https://developer.download.nvidia.com/compute/redist/nvidia-dali-cuda110/nvidia_dali_cuda110-0.24.0-1472979-cp36-cp36m-manylinux2014_x86_64.whl
https://developer.download.nvidia.com/compute/redist/nvidia-dali-cuda110/nvidia_dali_cuda110-0.24.0-1472979-cp37-cp37m-manylinux2014_x86_64.whl
https://developer.download.nvidia.com/compute/redist/nvidia-dali-cuda110/nvidia_dali_cuda110-0.24.0-1472979-cp38-cp38-manylinux2014_x86_64.whl
https://developer.download.nvidia.com/compute/redist/nvidia-dali-tf-plugin-cuda110/nvidia-dali-tf-plugin-cuda110-0.24.0.tar.gz

FFmpeg source code:

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

Libsndfile source code:

https://developer.download.nvidia.com/compute/redist/nvidia-dali/libsndfile-1.0.28.tar.gz

Assets 2

29 Jun 18:01

klecki

v0.23.0

d6f581b

DALI v0.23.0

Key Features and Enhancements

This DALI release includes the following key features and enhancements.

DALI packages name add -cuda110 and -cuda100 suffixes to indicate CUDA version and allow hosting all packages under single pip index. This is important only for installation, the DALI module in Python is still nvidia.dali regardless of CUDA version. See the https://docs.nvidia.com/deeplearning/dali/user-guide/docs/installation.html installation guide for details.
New and improved Operators:
- Normalize Operator for GPU (#1974, #1981, #1986).
- Support for epsilon and delta degrees of freedom arguments for Normalize Operator (#1964).
- SequenceRearrange Operator (#465).
- Erase Operator for GPU (#1971).
Improve how iterators count padded samples based on the reader (#1831) - the provided iterators can now query reader for the epoch size and sharding and handle the shard size changing from epoch-to-epoch when it's not evenly divisible by number of shards (rank) and batch size. More details can be found in https://docs.nvidia.com/deeplearning/dali/user-guide/docs/advanced_topics.html#sharding
CUDA 11 build scripts for DALI were added (#2008).

Bug fixes

Fix out-of-source build (#1975)
Fix typo in installation documentation (#1976)
Fix reference counting issue in the PythonFunction operator (#1978)
Fix the wording for preset OF argument (#1994)
Fix generation of Erase Region in kernel test (#1996)
Fix GPU spectrogram when window_length != nfft (#1999)
Fix MelFilterBank bug: setup block descriptors when changing shape between iterations. (#2001)
Change locked version of numba to at most 0.49, as 0.47 is the last release for py35 (#2016, #2020)

Improvements

Mean and Standard Deviation GPU kernels (#1919)
Linter script change: from CMake to Python (#1951)
Update links to the new location, remove deprecated installation guide (#1955)
Adding more Numpy data types (#1961)
Extend HSV example with RandomGrayscale implementation (#1962)
Add workaround for the problem with patchelf changing TLS alignment (#1952)
Add epsilon and ddof (delta degrees of freedom) arguments to Normalize. (#1964)
Small docs improvements (#1970)
Add Sequence Rearrange Op (#465)
Add a helper class for fast unsigned division, usable on host and device. (#1967)
Fix documentation drop-down menu and other links (#1972)
Erase GPU operator (#1971)
Update TF versions supported (#1973)
Add -cudaXXX to dali package name (#1948)
Add more error checking (#1979)
Make DALI test to be fPIE (#1980)
Normalize GPU kernel (#1974)
Normalize GPU - pImpl + Bessel's corrections (#1981)
Slice CPU kernel pad support (#1977)
Makes GTest and Google Benchmark fPIE, DALI binaries as dynamically relocatable (#1982)
Add more error checking in TensorFlow DALI integration (#1991)
Normalize operator for GPU backend (#1986)
Slice GPU kernel with multi-channel pad support (#1983)
Split Slice benchmarks into CPU and GPU (#1995)
Improve how iterators count padded samples based on the reader (#1831)
Remove boost from the dependencies as it is no longer used anyway (#2006)
Enable file path arguments (#2002)
Enable CUDA 11 builds (#2008)
Silence CUDA 11 compute 35 and 50 deprecation warning (#2010)
Drop CUDA 9 from docs (#2012)

Breaking API changes

DALI packages name add -cuda110 and -cuda100 suffixes to indicate CUDA version and allow hosting all packages under single pip index.
CUDA 9 is no longer supported. DALI 0.22.0 was the last release that provides CUDA 9 build.

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.
DALI TensorFlow plugin may not be compatible with TensorFlow versions 1.15.0 and/or later. If the user wants to use DALI with TensorFlow version which doesn’t have prebuilt plugin binary shipped with DALI it requires the gcc compiler that matches the one used to build TensorFlow (gcc 4.8.4 or gcc, 4.8.5 or 5.4, depending on the particular version) is present on the system.
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==0.23.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda100

or for CUDA 11:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda110==0.23.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda110

Or use direct download links (CUDA 10.0):

https://developer.download.nvidia.com/compute/redist/nvidia-dali-cuda100/nvidia_dali_cuda100-0.23.0-1396139-cp35-cp35m-manylinux1_x86_64.whl
https://developer.download.nvidia.com/compute/redist/nvidia-dali-cuda100/nvidia_dali_cuda100-0.23.0-1396139-cp36-cp36m-manylinux1_x86_64.whl
https://developer.download.nvidia.com/compute/redist/nvidia-dali-cuda100/nvidia_dali_cuda100-0.23.0-1396139-cp37-cp37m-manylinux1_x86_64.whl
https://developer.download.nvidia.com/compute/redist/nvidia-dali-cuda100/nvidia_dali_cuda100-0.23.0-1396139-cp38-cp38-manylinux1_x86_64.whl
https://developer.download.nvidia.com/compute/redist/nvidia-dali-tf-plugin-cuda100/nvidia-dali-tf-plugin-cuda100-0.23.0.tar.gz

Or use direct download links (CUDA 11.0):

https://developer.download.nvidia.com/compute/redist/nvidia-dali-cuda110/nvidia_dali_cuda110-0.23.0-1396141-cp35-cp35m-manylinux1_x86_64.whl
https://developer.download.nvidia.com/compute/redist/nvidia-dali-cuda110/nvidia_dali_cuda110-0.23.0-1396141-cp36-cp36m-manylinux1_x86_64.whl
https://developer.download.nvidia.com/compute/redist/nvidia-dali-cuda110/nvidia_dali_cuda110-0.23.0-1396141-cp37-cp37m-manylinux1_x86_64.whl
https://developer.download.nvidia.com/compute/redist/nvidia-dali-cuda110/nvidia_dali_cuda110-0.23.0-1396141-cp38-cp38-manylinux1_x86_64.whl
https://developer.download.nvidia.com/compute/redist/nvidia-dali-tf-plugin-cuda110/nvidia-dali-tf-plugin-cuda110-0.23.0.tar.gz

FFmpeg source code:

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

Libsndfile source code:

https://developer.download.nvidia.com/compute/redist/nvidia-dali/libsndfile-1.0.28.tar.gz

Assets 2

09 Jun 08:57

klecki

v0.22.0

4070053

DALI v0.22.0

Key Features and Enhancements

This DALI release includes the following key features and enhancements.

DALI now supports CUDA 11:
- DALI builds for CUDA 11 are now available.
- CUDA 9 support has been deprecated.
- DALI 0.22.0 is the final release that provides a CUDA 9 build.
Support is now available for the Ampere Hardware JPEG decoder.
The following new operators are now available:
- NumpyReader, which allows you to read standard .npy (NumPy) files (#1858).
- CoordFlip for CPU and GPU (#1894, #1895).
Readers can be set to read files directly instead of using mmap, which improves network filesystems performance (#1909).
DALI can be built as a CMake subproject (#1924).

Bug fixes

Fix TL1_tensorflow-dali_test (#1869)
Hotfix of external_source.py (#1878)
Build fix for aarch64 (incorrect cmake dependency) (#1883)
Fix TL1_ssd_training test by freezing apex version (#1898)
Fix support for dynamic per-sample shape in Warp operators (#1911)
Remove Optical flow test bug (#1902)
Fix jitter operator illegal memory access (#1914)
Fix setup_packages.py after pip update to 20.1 version (#1916)
Fix TL1_python-nvjpeg_test test dependency (#1926)
L1 test fix for Xavier (#1936)
Fix tensorflow_dataset test to run on any power of 2 number of GPUs (#1935)
Fix a race condition in ExternalSourceTest test (#1943)

Improvements

Add support for array and cuda_array interface for DALI tensor (#1857)
Add collapse_dim and collapse_dims for TensorListShape. (#1862)
Add support for TensorFlow 2.2.0rc2 (#1860)
Add ExternalSource to "C API" (#1865)
Numpy reader (#1858)
Add TensorGPU and TensorListGPU constructors based on CUDA array interface (#1868)
Bump up OpenCV version to 4.3.0, libturbo-jpeg to 2.0.4, libtiff to 4.1.0, FFmpeg to 4.2.2 (#1783)
Add "no exec check" to SmallVector to prevent warnings in host-only functions. (#1870)
Allow for a separate dali_tf_plugin pip wheel step (#1856)
QA tests: Fix nvidia-dali-tf-plugin to uninstall weekly and nightly packages (#1877)
make install target for installing DALI on system where it's build (#1854)
Allow RandomBBoxCrop thresholds to refer to relative overlap alternatively to IoU (#1874)
Add a link to release notes in the docs (#1881)
Operator diagnostics mechanism (#1880)
Reductions: position-dependent preprocessing, kernels for unhandled edge cases (#1884)
Update Horovod in Tensorflow test (#1887)
Add an ability to strip DALI whl binary from debug symbols (#1897)
Extend conda testing (#1784)
Copy out core* files if the test_body fails (#1890)
Make volume return 1 for 0-dim shape. (#1906)
Update DALI PyTorch RN50 example to the latest AMP version (#1888)
Add a specialized TF dataset for conda (#1910)
Deserialize pipeline in python API (#1912)
Add CoordFlip CPU operator (#1894)
Restore an ability to use direct read of files instead of mmap (#1909)
Use only ImportError in setup_packages (#1922)
Collect exit code from test_body (#1923)
Coordinate Flip GPU operator (#1895)
DALI as a git submodule (#1924)
Add Erase GPU Kernel (#1903)
C API ExternalSource for GPU input (#1892)
Fix warning condition in ExternalSource (#1934)
Reduce GPU - kernel frontend (#1882)
Add checking alignment argument for 0 in the pad operator (#1937)
Move from http://xiph.org to GitHub for libflac, libvorbis and libogg (#1938)
C API function: inherit parameters from serialized pipeline (#1932)
Use LinearTransformation kernel in ColorTwist GPU Op (#1918)
Adjust test sizes for Erase GPU Kernel (#1939)
Use user stream by default in copy_to_external/feed_ndarray (#1921)
Move to TensorFlow 2.2.0 from 2.2.0-RC2 (#1946)
Add support for random_shuffle argument in test_RN50_data_pipeline (#1945)
Proper DALI initialization in process & daliInitialize function (#1929)
Update clang version to 8.0.1 in deps image (#1949)
Add support for nvjpeg HW decoder, including rework to accommodate different decoding methods in one batch
Fix "hw_decoder_load" handling for slice/cropImageDecoder for nvJPEG
Move HW decoding to separate stream
Fix linter in nvjpeg HW decoder
Deprecate CUDA 9
Add CUDA 11 to the installation guide and build.sh

Breaking API changes

None

Deprecated feature

CUDA 9 support is deprecated. DALI 0.22.0 is the last release that provides CUDA 9 build.

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.
DALI TensorFlow plugin may not be compatible with TensorFlow versions 1.15.0 and/or later. If the user wants to use DALI with TensorFlow version which doesn’t have prebuilt plugin binary shipped with DALI it requires the gcc compiler that matches the one used to build TensorFlow (gcc 4.8.4 or gcc, 4.8.5 or 5.4, depending on the particular version) is present on the system.
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 9:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/cuda/9.0 nvidia-dali==0.22.0
or for CUDA 10:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/cuda/10.0 nvidia-dali==0.22.0
or for CUDA 11:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/cuda/11.0 nvidia-dali==0.22.0

Or use direct download links (CUDA 9.0):
https://developer.download.nvidia.com/compute/redist/cuda/9.0/nvidia-dali/nvidia_dali-0.22.0-1313462-cp35-cp35m-manylinux1_x86_64.whl
https://developer.download.nvidia.com/compute/redist/cuda/9.0/nvidia-dali/nvidia_dali-0.22.0-1313462-cp36-cp36m-manylinux1_x86_64.whl
https://developer.download.nvidia.com/compute/redist/cuda/9.0/nvidia-dali/nvidia_dali-0.22.0-1313462-cp37-cp37m-manylinux1_x86_64.whl
https://developer.download.nvidia.com/compute/redist/cuda/9.0/nvidia-dali/nvidia_dali-0.22.0-1313462-cp38-cp38-manylinux1_x86_64.whl
https://developer.download.nvidia.com/compute/redist/cuda/9.0/nvidia-dali-tf-plugin/nvidia-dali-tf-plugin-0.22.0.tar.gz

Or use direct download links (CUDA 10.0):

https://developer.download.nvidia.com/compute/redist/cuda/10.0/nvidia-dali/nvidia_dali-0.22.0-1313464-cp35-cp35m-manylinux1_x86_64.whl
https://developer.download.nvidia.com/compute/redist/cuda/10.0/nvidia-dali/nvidia_dali-0.22.0-1313464-cp36-cp36m-manylinux1_x86_64.whl
https://developer.download.nvidia.com/compute/redist/cuda/10.0/nvidia-dali/nvidia_dali-0.22.0-1313464-cp37-cp37m-manylinux1_x86_64.whl
https://developer.download.nvidia.com/compute/redist/cuda/10.0/nvidia-dali/nvidia_dali-0.22.0-1313464-cp38-cp38-manylinux1_x86_64.whl
https://developer.download.nvidia.com/compute/redist/cuda/10.0/nvidia-dali-tf-plugin/nvidia-dali-tf-plugin-0.22.0.tar.gz

Or use direct download links (CUDA 11.0):

https://developer.download.nvidia.com/compute/redist/cuda/11.0/nvidia-dali/nvidia_dali-0.22.0-1313465-cp35-cp35m-manylinux1_x86_64.whl
https://developer.download.nvidia.com/compute/redist/cuda/11.0/nvidia-dali/nvidia_dali-0.22.0-1313465-cp36-cp36m-manylinux1_x86_64.whl
https://developer.download.nvidia.com/compute/redist/cuda/11.0/nvidia-dali/nvidia_dali-0.22.0-1313465-cp37-cp37m-manylinux1_x86_64.whl
https://developer.download.nvidia.com/compute/redist/cuda/11.0/nvidia-dali/nvidia_dali-0.22.0-1313465-cp38-cp38-manylinux1_x86_64.whl
https://developer.download.nvidia.com/compute/redist/cuda/11.0/nvidia-dali-tf-plugin/nvidia-dali-tf-plugin-0.22.0.tar.gz

FFmpeg source code:

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

Libsndfile source code:

https://developer.download.nvidia.com/compute/redist/nvidia-dali/libsndfile-1.0.28.tar.gz

Assets 2

Releases: NVIDIA/DALI

DALI v0.30.0

Key Features and Enhancements

Fixed issues

Improvements

Bug fixes

Breaking API changes

Deprecated features

Known issues:

Binary builds

DALI v0.29.0

Key Features and Enhancements

Fixed issues

Improvements

Bug fixes

Breaking API changes

Deprecated features

Known issues:

Binary builds

DALI v0.28.0

Key Features and Enhancements

Bug fixes

Improvements

Breaking API changes

Deprecated feature

Known issues:

Binary builds

DALI v0.27.0

Key Features and Enhancements

Bug fixes

Improvements

Breaking API changes

Deprecated feature

Known issues:

Binary builds

DALI 0.25.1

Key Features and Enhancements

Bug fixes

Known issues

Binary builds

DALI v0.26.0

Key Features and Enhancements

Bug fixes

Improvements

Breaking API changes

Deprecated feature

Known issues:

Binary builds

DALI v0.25.0

Key Features and Enhancements

Bug fixes

Improvements

Breaking API changes

Deprecated feature

Known issues:

Binary builds

DALI v0.24.0

Key Features and Enhancements

Bug fixes

Improvements

Breaking API changes

Deprecated feature

Known issues:

Binary builds

DALI v0.23.0

Key Features and Enhancements

Bug fixes

Improvements

Breaking API changes

Deprecated feature

Known issues:

Binary builds

DALI v0.22.0

Key Features and Enhancements

Bug fixes

Improvements

Breaking API changes

Deprecated feature

Known issues:

Binary builds