A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to accelerate deep learning training and inference applications.
This DALI release includes the following key features and enhancements:
fn.experimental.dilate
, fn.experimental.erode
) (#5294).fn.experimental.decoders
(#5297, #5336, #5324, #5333, #5339).fn.random_crop_generator
operator (#5304).fn.multi_paste
(#5331).naive_histogram
custom operator to test suite (#4731)There are no breaking changes in this DALI release.
No features were deprecated in this release.
experimental.readers.fits
, experimental.decoders.video
, experimental.inputs.video
, and experimental.decoders.image_random_crop
do not currently support checkpointing.privileged=yes
in Extra Settings for AWS data points--privileged
or --security-opt seccomp=unconfined
for bare Docker.NOTE: DALI builds for CUDA 12 dynamically link the CUDA toolkit. To use DALI, install the latest CUDA toolkit.
CUDA 11.0 and CUDA 12.0 builds use CUDA toolkit enhanced compatibility.
They are built with the latest CUDA 11.x/12.x toolkit respectively but they can run on the latest,
stable CUDA 11.0/CUDA 12.0 capable drivers (450.80 or later and 525.60 or later respectively).
However, using the most recent driver may enable additional functionality.
More details can be found in enhanced CUDA compatibility guide.
Install via pip for CUDA 12.0:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda120==1.36.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda120==1.36.0
For CUDA 11:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda110==1.36.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda110==1.36.0
Or use direct download links (CUDA 12.0):
Or use direct download links (CUDA 11.0):
FFmpeg source code:
Libsndfile source code:
This DALI release includes the following key features and enhancements:
do_not_convert
decorator to address problems with parallel fn.external_source
and conditional execution (#5263).fn.readers.video
handling of sequences bigger than 2GB (#5307).fn.resize
handling of samples larger than 2GB (#5306).fn.external_source
(#5268).There are no breaking changes in this DALI release.
No features were deprecated in this release.
experimental.readers.fits
, experimental.decoders.video
, experimental.inputs.video
, and experimental.decoders.image_random_crop
do not currently support checkpointing.privileged=yes
in Extra Settings for AWS data points--privileged
or --security-opt seccomp=unconfined
for bare Docker.NOTE: DALI builds for CUDA 12 dynamically link the CUDA toolkit. To use DALI, install the latest CUDA toolkit.
CUDA 11.0 and CUDA 12.0 builds use CUDA toolkit enhanced compatibility.
They are built with the latest CUDA 11.x/12.x toolkit respectively but they can run on the latest,
stable CUDA 11.0/CUDA 12.0 capable drivers (450.80 or later and 525.60 or later respectively).
However, using the most recent driver may enable additional functionality.
More details can be found in enhanced CUDA compatibility guide.
Install via pip for CUDA 12.0:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda120==1.35.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda120==1.35.0
or just:
pip install nvidia-dali-cuda120==1.35.0
pip install nvidia-dali-tf-plugin-cuda120==1.35.0
For CUDA 11:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda110==1.35.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda110==1.35.0
or just:
pip install nvidia-dali-cuda110==1.35.0
pip install nvidia-dali-tf-plugin-cuda110==1.35.0
Or use direct download links (CUDA 12.0):
Or use direct download links (CUDA 11.0):
FFmpeg source code:
Libsndfile source code:
This DALI release includes the following key features and enhancements:
fn.random_resized_crop
(#5246)fn.lookup_table
. (#5257)bboxes
in fn.ssd_random_crop
(#5240)random_resized_crop
(#5246)There are no breaking changes in this DALI release.
No features were deprecated in this release.
experimental.readers.fits
, experimental.decoders.video
, experimental.inputs.video
, and experimental.decoders.image_random_crop
do not currently support checkpointing.privileged=yes
in Extra Settings for AWS data points--privileged
or --security-opt seccomp=unconfined
for bare Docker.NOTE: DALI builds for CUDA 12 dynamically link the CUDA toolkit. To use DALI, install the latest CUDA toolkit.
CUDA 11.0 and CUDA 12.0 builds use CUDA toolkit enhanced compatibility.
They are built with the latest CUDA 11.x/12.x toolkit respectively but they can run on the latest,
stable CUDA 11.0/CUDA 12.0 capable drivers (450.80 or later and 525.60 or later respectively).
However, using the most recent driver may enable additional functionality.
More details can be found in enhanced CUDA compatibility guide.
Install via pip for CUDA 12.0:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda120==1.34.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda120==1.34.0
or just:
pip install nvidia-dali-cuda120==1.34.0
pip install nvidia-dali-tf-plugin-cuda120==1.34.0
For CUDA 11:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda110==1.34.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda110==1.34.0
or just:
pip install nvidia-dali-cuda110==1.34.0
pip install nvidia-dali-tf-plugin-cuda110==1.34.0
Or use direct download links (CUDA 12.0):
Or use direct download links (CUDA 11.0):
FFmpeg source code:
Libsndfile source code:
This DALI release includes the following key features and enhancements:
pmap
compatibility for JAX data_iterator
(#5185).fn.normalize
handling of batch of empty samples (#5223).fn.transpose
and fn.normalize
. (#5208)pmap
compatibility for JAX data_iterator
(#5185)There are no breaking changes in this DALI release.
No features were deprecated in this release.
experimental.readers.fits
, experimental.decoders.video
, experimental.inputs.video
, random_resized_crop
, and experimental.decoders.image_random_crop
do not currently support checkpointing.privileged=yes
in Extra Settings for AWS data points--privileged
or --security-opt seccomp=unconfined
for bare Docker.NOTE: DALI builds for CUDA 12 dynamically link the CUDA toolkit. To use DALI, install the latest CUDA toolkit.
CUDA 11.0 and CUDA 12.0 builds use CUDA toolkit enhanced compatibility.
They are built with the latest CUDA 11.x/12.x toolkit respectively but they can run on the latest,
stable CUDA 11.0/CUDA 12.0 capable drivers (450.80 or later and 525.60 or later respectively).
However, using the most recent driver may enable additional functionality.
More details can be found in enhanced CUDA compatibility guide.
Install via pip for CUDA 12.0:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda120==1.33.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda120==1.33.0
or for CUDA 11:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda110==1.33.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda110==1.33.0
Or use direct download links (CUDA 12.0):
Or use direct download links (CUDA 11.0):
FFmpeg source code:
Libsndfile source code:
This DALI release includes the following key features and enhancements:
fn.readers.file
, CPU fn.random generators
, and stateless operators) (#5085, #5088, #5103, #5114, #5113, #5142, #5128, #5144).fn.python_function
in the DALI pipeline (#5138).fn.fast_resize_crop_mirror
. The operator was deprecated in favor of fn.resize_crop_mirror
(#5123).fn.resize
in the DALI pipeline (#5133).__cuda_array_interface__
v3 (#5125).crop_pos_z
handling for a fixed crop window in the fn.crop
operator (#5119).fn.external_source
. The problem led to crashes when using fn.external_source
in no_copy
or parallel
mode with conditional execution enabled in the pipeline (#5101).__module__
handling and hide private modules docs (#5112)fn.fast_resize_crop_mirror
was deprecated in favour of fn.resize_crop_mirror.privileged=yes
in Extra Settings for AWS data points--privileged
or --security-opt seccomp=unconfined
for bare Docker.NOTE: DALI builds for CUDA 12 dynamically link the CUDA toolkit. To use DALI, install the latest CUDA toolkit.
CUDA 11.0 and CUDA 12.0 builds use CUDA toolkit enhanced compatibility.
They are built with the latest CUDA 11.x/12.x toolkit respectively but they can run on the latest,
stable CUDA 11.0/CUDA 12.0 capable drivers (450.80 or later and 525.60 or later respectively).
However, using the most recent driver may enable additional functionality.
More details can be found in enhanced CUDA compatibility guide.
Install via pip for CUDA 12.0:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda120==1.32.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda120==1.32.0
or for CUDA 11:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda110==1.32.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda110==1.32.0
Or use direct download links (CUDA 12.0):
Or use direct download links (CUDA 11.0):
FFmpeg source code:
Libsndfile source code:
This DALI release includes the following key features and enhancements:
data_iterator
and peekable_data_iterator
decorators for simplified JAX iterators definitions. (#5050, #5049)fn.permute_batch
operator can now be used with the conditional execution (if
expressions). (#5063)hw_decoder_bench
(#5076) There are no breaking changes in this DALI release.
privileged=yes
in Extra Settings for AWS data points--privileged
or --security-opt seccomp=unconfined
for bare Docker.NOTE: DALI builds for CUDA 12 dynamically link the CUDA toolkit. To use DALI, install the latest CUDA toolkit.
CUDA 11.0 and CUDA 12.0 builds use CUDA toolkit enhanced compatibility.
They are built with the latest CUDA 11.x/12.x toolkit respectively but they can run on the latest,
stable CUDA 11.0/CUDA 12.0 capable drivers (450.80 or later and 525.60 or later respectively).
However, using the most recent driver may enable additional functionality.
More details can be found in enhanced CUDA compatibility guide.
Install via pip for CUDA 12.0:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda120==1.31.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda120==1.31.0
or for CUDA 11:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda110==1.31.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda110==1.31.0
Or use direct download links (CUDA 12.0):
Or use direct download links (CUDA 11.0):
FFmpeg source code:
Libsndfile source code:
This DALI release includes the following key features and enhancements:
fn.*python_function
) inside DALI asynchronous pipelines (#4965, #5038).plugin.numba.fn.experimental.numba_function
) (#4000).fn.crop_mirror_normalize
) performance (#4993, #4992).fn.readers.webdataset
(#5016).fn.readers.numpy
global shuffling (#5034).fn.resize
operator family that could result in distorted outputs in initial iterations (#4990).There are no breaking changes in this DALI release.
No features were deprecated in this release.
privileged=yes
in Extra Settings for AWS data points--privileged
or --security-opt seccomp=unconfined
for bare Docker.NOTE: DALI builds for CUDA 12 dynamically link the CUDA toolkit. To use DALI, install the latest CUDA toolkit.
CUDA 11.0 and CUDA 12.0 builds use CUDA toolkit enhanced compatibility.
They are built with the latest CUDA 11.x/12.x toolkit respectively but they can run on the latest,
stable CUDA 11.0/CUDA 12.0 capable drivers (450.80 or later and 525.60 or later respectively).
However, using the most recent driver may enable additional functionality.
More details can be found in enhanced CUDA compatibility guide.
Install via pip for CUDA 12.0:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda120==1.30.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda120==1.30.0
or for CUDA 11:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda110==1.30.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda110==1.30.0
Or use direct download links (CUDA 12.0):
Or use direct download links (CUDA 11.0):
FFmpeg source code:
Libsndfile source code:
This DALI release includes the following key features and enhancements:
fn.experimental.median_blur
operator. (#4950, #4975)jax.Sharding
to dali.plugin.jax.DALIGenericIterator
(#4969).fn.crop_mirror_normalize
operator (#4972).Getting Started
link in README (#4962)There are no breaking changes in this DALI release.
No features were deprecated in this release.
privileged=yes
in Extra Settings for AWS data points--privileged
or --security-opt seccomp=unconfined
for bare Docker.NOTE: DALI builds for CUDA 12 dynamically link the CUDA toolkit. To use DALI, install the latest CUDA toolkit.
CUDA 11.0 and CUDA 12.0 builds use CUDA toolkit enhanced compatibility.
They are built with the latest CUDA 11.x/12.x toolkit respectively but they can run on the latest,
stable CUDA 11.0/CUDA 12.0 capable drivers (450.80 or later and 525.60 or later respectively).
However, using the most recent driver may enable additional functionality.
More details can be found in enhanced CUDA compatibility guide.
Install via pip for CUDA 12.0:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda120==1.29.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda120==1.29.0
or for CUDA 11:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda110==1.29.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda110==1.29.0
Or use direct download links (CUDA 12.0):
Or use direct download links (CUDA 11.0):
FFmpeg source code:
Libsndfile source code:
This DALI release includes the following key features and enhancements:
cudaMallocAsync
support (#4900, #4923, and #4921).DALIRaggedIterator
, a DALI Pytorch plugin iterator that supports non-uniform tensors (#4911).No major fixes are included in this release.
No features were deprecated in this release.
privileged=yes
in Extra Settings for AWS data points--privileged
or --security-opt seccomp=unconfined
for bare Docker.NOTE: DALI builds for CUDA 12 dynamically link the CUDA toolkit. To use DALI, install the latest CUDA toolkit.
CUDA 11.0 and CUDA 12.0 builds use CUDA toolkit enhanced compatibility.
They are built with the latest CUDA 11.x/12.x toolkit respectively but they can run on the latest,
stable CUDA 11.0/CUDA 12.0 capable drivers (450.80 or later and 525.60 or later respectively).
However, using the most recent driver may enable additional functionality.
More details can be found in enhanced CUDA compatibility guide.
Install via pip for CUDA 12.0:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda120==1.28.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda120==1.28.0
or for CUDA 11:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda110==1.28.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda110==1.28.0
Or use direct download links (CUDA 12.0):
Or use direct download links (CUDA 11.0):
FFmpeg source code:
Libsndfile source code:
This DALI release includes the following key features and enhancements:
fn.readers.tfrecord
(#4820).fn.experimental.readers.fits
images that are stored in the FITS format (#4752).fn.experimental.decoders
(#4846).gast
version requirement (#4896)feed_input
documentation regarding prefetching (#4875)blocking
option in the external source operator (#4874)There are no breaking changes in this DALI release.
DALI 1.27 is the final release that will support Python 3.6.
privileged=yes
in Extra Settings for AWS data points--privileged
or --security-opt seccomp=unconfined
for bare Docker.NOTE: DALI builds for CUDA 12 dynamically link the CUDA toolkit. To use DALI, install the latest CUDA toolkit.
CUDA 11.0 and CUDA 12.0 builds use CUDA toolkit enhanced compatibility.
They are built with the latest CUDA 11.x/12.x toolkit respectively but they can run on the latest,
stable CUDA 11.0/CUDA 12.0 capable drivers (450.80 or later and 525.60 or later respectively).
However, using the most recent driver may enable additional functionality.
More details can be found in enhanced CUDA compatibility guide.
Install via pip for CUDA 12.0:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda120==1.27.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda120==1.27.0
or for CUDA 11:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda110==1.27.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda110==1.27.0
Or use direct download links (CUDA 12.0):
Or use direct download links (CUDA 11.0):
FFmpeg source code:
Libsndfile source code: