The DALI 0.24.0 is not yet a major release, so the features, functionality, and
performance might be limited.
Using DALI 0.24.0
To upgrade to DALI 0.24.0 from an older version of DALI, follow
the installation and usage information in the DALI User Guide.
Note: The internal DALI C++ API used for operator’s implementation, and
the C++ API that enables using DALI as a library from native code, is
not yet officially supported. Hence these APIs may change in the next release
without advance notice.
Key Features and Enhancements
This DALI release includes the following key features and
enhancements.
-
The DALI package name now adds -cuda110 and
-cuda100 suffixes to indicate the CUDA version and
allows the hosting of all packages under one pip index.
This is important only for installation, and the DALI module in Python is
still `nvidia.dali` regardless of the CUDA version.
Refer to the Installation section in the DALI User Guide for more
information.
- New Operators:
- Preemphasis (#2025 )
-
GaussianBlur CPU (#1987, #2009, and #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).
Fixed Issues
This DALI release includes the following fixes.
Breaking Changes
Empty for now.
Deprecated Features
- 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 frequency that is less than 10-15 frames, the
returned frames might 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 that is 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 the best performance when running 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