NVIDIA/DALI v1.52.0

DALI v1.52.0

Repository: NVIDIA/DALI

Tag: v1.52.0

Published: 2025-10-27T14:10:55Z

Prerelease: no

Release notes: Key Features and Enhancements --- This DALI release includes the following key features and enhancements:

• Introduced experimental Dynamic Mode: imperative execution model with lazy evaluation for easier integration into Python workflows. (#6066, #6064, #6060, #6056, #6042, #6039, #6037, #6036, #5954)
• Dynamic mode: add augmentation gallery (#6057)
• DALI Dynamic docs main page (#6052)
• Added pipeline ZOO - snippets and examples for common image and video processing use cases. (#5922)
• Added support for CUDA 13U2 (#6063)
• Added fn.decoders.numpy (#5953) and CPU fn.paste operators (#5968).

Thank you @5had3z for your contributions.

• Exposed knobs for pipeline dynamic executor:
• Exposed executor's stream_policy and concurrency options (#5983)
• Environment variable to control executor threads. (#5949)

Fixed Issues ---

• Fixed stream ordering in Tensor::Copy and Tensor(List)GPU.as_cpu (#6070)
• Fixed conversion of pinned tensors to DLPack. (#6061)
• Fixed DLPack stride check if stride pointer is NULL
• Fixed handling of videos without keyframes and reuse of old indices (#6058)
• Fixed resize_crop_mirror video output shape (#5957)

Improvements ---

• Update to FFmpeg 8.0
• Dynamic mode: add augmentation gallery (#6057)
• Add dynamic API for math functions + tests. (#6066)
• Rename DALI2 to dynamic (#6064)
• Move to CUDA 13.0 U2 (#6063)
• Dynamic mode: operator base classes and operator call generator (#6060)
• Update VERSION to 1.52.0
• Update deps 25/10 (#6053)
• Dynamic Mode: Tensor and Batch Types (#6056)
• Remove CMake from acknowledgements. (#6020)
• DALI Dynamic docs main page (#6052)
• Reduce minimum throughput for experimental decoder in TL1_decoder_perf (#6050)
• Fix TL0_video_plugin to run with sanitizer (#6040)
• Imperative mode: Invocation (#6042)
• Update LD_PRELOAD in sanitizer configuration, exclude more numba tests (#6041)
• Imperative mode: EvalContext, EvalMode, Type and Device (#6039)
• Update the test environment to Ubuntu 24.04 (#6033)
• Update curl 3.15 -> 3.16 (#6038)
• Add TensorList broadcasting constructor. (#6037)
• Backend changes for imperative mode (#6036)
• Add nvcc/nvjitlink version compatibility check to numba CUDA test (#6035)
• Unify minimum required CMake version. (#6022)
• Fix installation of Horovod in TL1_tensorflow-dali_test (#6024)
• Remove confusing warning on host decoder fallback (#6029)
• Add stream argument to TensorGPU DLPack constructor. (#6015)
• Cumulative dependency update for September 2025. (#6017)
• Silence false warnings in sanitized build (#6018)
• Lower the 5% threshold in image decoder perf test to 15% to account for off iterations (#6021)
• Bump CMake to 3.25.2 (#6019)
• Move to CUDA 13.0 U1 (#6016)
• Move to the gcc-toolset-14 (#6014)
• Update test packages (#6010)
• Correct support matrix entry for Orin (#6008)
• Silence a false positive warning triggered by GCC 12.2.1 (#6002)
• Fix CVE-2024-13978 and CVE-2025-8534 in libtiff (#6007)
• Bump up OpenCV version to 4.12 in conda (#6005)
• Move to the latest nvJPEG2k (#6000)
• Enable more aggressive binary compression (#6001)
• Use subprocess.run in get_tf_compiler_version to avoid CalledProcessError on grep (#5991)
• Add functions that change the type of the tensor or tensor list to a different type of the same size. (#5995)
• Update OpenCV version in tests (#5987)
• Improve performance of experimental.resize (#5662)
• Expose executor policy flags (#5983)
• Pin CMake to max 4.0.3 in jupter_conda tests. (#5985)
• Add driver version check to the usage of numba_cuda (#5982)
• Fix nvComp installation in tests (#5984)
• Update DALI_DEPS_VERSION to use patched libtiff (#5981)
• Improve creating image batches in CV-CUDA ops (#5966)
• Dependency update 07-2025 (#5978)
• Make the numba operator compatible with the numba-cuda package (#5975)
• Adjust TF plugin build dependencies (#5976)
• fn.paste CPU impl (#5968)
• Make sure that protobuf always uses own absl version instead of system one (#5974)
• Thread pool with semaphore and spinlock (#5970)
• Extend GetInputDevice in OpSchema python bindings. (#5972)
• Remove data preparation instructions from the video superres use case (#5965)
• Added fn.decoders.numpy (#5953)
• Pipeline zoo - initial commit (#5922)
• Expose Stream, Operator and Workspace in Python (#5954)
• Fix nvcc not working with sanitizer (#5959)
• Make the number of dynamic executor threads configurable via environment variables. (#5949)

Bug Fixes ---

• Fix stream ordering in Tensor::Copy and Tensor(List)GPU.as_cpu
• Fix conversion of pinned tensors to DLPack. (#6061)
• Fix DLPack tests to use HWC layout instead of NHWC (#6062)
• Fix handling of videos without keyframes and reuse of old indices (#6058)
• Refactor layout handling in Python backend + add layout dimensionality checks in Tensor and TensorList python bindings (#6054)
• Fix standalone op output streams. (#6055)
• Remove EvalContext destructor. (#6043)
• Fix static analysis issues (#6032)
• Install newer CMake in TL0_jupyter (#6034)
• Disable PYBIND11_FINDPYTHON in CMakeLists.txt (#6031)
• Remove a custom patch for PyCuda, add numba_cuda version constrain (#6023)
• Bugfix: Skip DLPack stride check if stride pointer is NULL
• Improve error handling in ThreadPool (#6011)
• Fix test_backend_impl launch command (#6003)
• Remove unnecessary default values from optional arguments. (#5992)
• Add missing backslash in test scripts. (#5986)
• Fixes outdated DALI mannylinux tag (#5980)
• resize_crop_mirror - invalid video output shape fix (#5957)

Breaking API changes --- There are no breaking changes in this DALI release.

Deprecated features --- No features were deprecated in this release.

Known issues: ---

• In some cases, the pass-through parallel external source outputs may be corrupted when used with pipelined dynamic executor. The issue occurs when all four conditions are met: 1. the pipeline uses dynamic executor exec_dynamic=True (default), 2. the external_source runs in parallel mode (parallel=True), 3. the ES output is directly returned from the pipeline, 4. the ES output is a single contiguous chunk of memory (either batch=True or batch_size=1). Currently, as a workaround, user can specify exec_dynamic=False when instantiating pipeline or add an extra fn.copy to prevent directly returning ES outputs from the pipeline.
• A problem with insufficient static TLS…