A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to accelerate deep learning training and inference applications.
APACHE-2.0 License
This DALI release includes the following key features and enhancements:
fn.decoders.image*
operators to use nvImageCodec as a decoding backend (#5470).fn.readers.file
support for pad_last_batch=True (#5493).blocking
argument documentation to the external source operator (#5501)@do_not_convert
for NUMBA and Python ops (#5488)OpGraph::HasConsumersInOtherStage
(#5475)There are no breaking changes in this DALI release.
DALI 1.39 is the final release that will support the MXNet integration.
experimental.readers.fits
, experimental.decoders.video
, and experimental.inputs.video
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==1.39.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda120==1.39.0
or just:
pip install nvidia-dali-cuda120==1.39.0
pip install nvidia-dali-tf-plugin-cuda120==1.39.0
For CUDA 11:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda110==1.39.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda110==1.39.0
or just:
pip install nvidia-dali-cuda110==1.39.0
pip install nvidia-dali-tf-plugin-cuda110==1.39.0
Or use direct download links (CUDA 12.0):
Or use direct download links (CUDA 11.0):
FFmpeg source code:
Libsndfile source code:
Published by stiepan 5 months ago
This DALI release includes the following key features and enhancements:
types.Constant
, fn.cast
, fn.random.choice
(#5422).There are no breaking changes in this DALI release.
DALI 1.39 will be the last release to support MXNet integration.
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==1.38.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda120==1.38.0
or just:
pip install nvidia-dali-cuda120==1.38.0
pip install nvidia-dali-tf-plugin-cuda120==1.38.0
For CUDA 11:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda110==1.38.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda110==1.38.0
or just:
pip install nvidia-dali-cuda110==1.38.0
pip install nvidia-dali-tf-plugin-cuda110==1.38.0
Or use direct download links (CUDA 12.0):
Or use direct download links (CUDA 11.0):
FFmpeg source code:
Libsndfile source code:
Published by JanuszL 6 months ago
There are no new features in this release
There are no new improvements in this release
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==1.37.1
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda120==1.37.1
or just:
pip install nvidia-dali-cuda120==1.37.1
pip install nvidia-dali-tf-plugin-cuda120==1.37.1
For CUDA 11:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda110==1.37.1
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda110==1.37.1
or just:
pip install nvidia-dali-cuda120==1.37.1
pip install nvidia-dali-tf-plugin-cuda120==1.37.1
Or use direct download links (CUDA 12.0):
Or use direct download links (CUDA 11.0):
FFmpeg source code:
Libsndfile source code:
Published by stiepan 6 months ago
This DALI release includes the following key features and enhancements:
fn.random.choice
operator. (#5380, #5387)fn.resize
operator for better GPU utilization (#5382)fn.random_bbox_crop
with the fraction of area within the crop below user-provided threshold. (#5368) stream
field in CUDA Array Interface v3 (#5425).fn.experimental.decoders.*
). (#5408)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==1.37.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda120==1.37.0
or just:
pip install nvidia-dali-cuda120==1.37.0
pip install nvidia-dali-tf-plugin-cuda120==1.37.0
For CUDA 11:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda110==1.37.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda110==1.37.0
or just:
pip install nvidia-dali-cuda120==1.37.0
pip install nvidia-dali-tf-plugin-cuda120==1.37.0
Or use direct download links (CUDA 12.0):
Or use direct download links (CUDA 11.0):
FFmpeg source code:
Libsndfile source code:
Published by stiepan 7 months ago
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:
Published by stiepan 8 months ago
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:
Published by stiepan 9 months ago
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:
Published by stiepan 10 months ago
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:
Published by stiepan 11 months ago
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:
Published by stiepan 12 months ago
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:
Published by stiepan about 1 year ago
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:
Published by stiepan about 1 year ago
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:
Published by stiepan over 1 year ago
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:
Published by stiepan over 1 year ago
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:
Published by stiepan over 1 year ago
This DALI release includes the following key features and enhancements:
fn.readers.numpy
(#4796, #4848).iscrowd
entries from COCO (#4792).fn.experimental.remap
operator (#4790).fn.external_source
(#4793).iscrowd
entries from COCO (#4792)"depleted"
operator trace (#4794)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==1.26.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda120==1.26.0
or for CUDA 11:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda110==1.26.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda110==1.26.0
Or use direct download links (CUDA 12.0):
Or use direct download links (CUDA 11.0):
FFmpeg source code:
Libsndfile source code:
Published by stiepan over 1 year ago
This DALI release includes the following key features and enhancements:
fn.experimental.readers.fits
) for the CPU backend (#4591).fn.experimental.equalize
) (#4742).fn.experimental.filter
) (#4764).Pipeline.run
(#4712).fn.readers.webdataset
performance (#4708).fn.readers.numpy
(#4745).fn.experimental.decoder.image
(#4727).fn.experimental.decoders.video
returning incorrect frames for high-resolution videos (#4717).fn.experimental.decoder.image
(#4723).math.abs
and math.floor
) incorrectly processing non-scalar samples (#4746).sample
to data
in automatic augmentation APIs (#4774)Pipeline.run()
(#4712)if
predicate and not
expression (#4715)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==1.25.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda120==1.25.0
or for CUDA 11:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda110==1.25.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda110==1.25.0
Or use direct download links (CUDA 12.0):
Or use direct download links (CUDA 11.0):
FFmpeg source code:
Libsndfile source code:
Published by stiepan over 1 year ago
This DALI release includes the following key features and enhancements:
and
, or
, and not
boolean operators in pipelines (#4629, #4676).and
and or
, and not lazy not
support (#4629)There are no breaking changes in this DALI release.
No features were deprecated in this release.
experimental.decoder.image
may hang during a pipeline build or a teardown.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==1.24.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda120==1.24.0
or for CUDA 11:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda110==1.24.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda110==1.24.0
Or use direct download links (CUDA 12.0):
Or use direct download links (CUDA 11.0):
FFmpeg source code:
Libsndfile source code:
Published by stiepan over 1 year ago
This DALI release includes the following key features and enhancements:
experimental.inputs.video
operator that supports decoding large videos from memorybuffer across multiple iterations (#4613, #4584, #4603, #4564).fn.experimental.decoders.image
(#4625, #4600, #4587, #4572, #4592, #4548).fn.experimental.tensor_resize
operator (#4492).fn.experimental.equalize
operator (#4575, #4565).fn.constant
operator synchronization issue (#4643).fn.reshape
(#4631).VideoInput<MixedBackend>
(#4613)reshape
: restore the support for trailing wildcard in rel_shape
(#4623)DataId
mechanism for fn.inputs.video
operator (#4584)MixedBackend
support for InputOperator
(#4603)define_graph
argument from build
pipeline method (#4555)release_unused
function to memory pools. (#4556)constant
operator: Set proper stream in constant storage. (#4643)reshape
: Prevent out-of-bounds access with trailing wildcard in rel_shape
(#4631)rel_shape
length validation in reshape
(#4595)release_unused
. Don't rely on cudaGetMemInfo in preallocation tests. (#4596)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==1.23.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda120==1.23.0
or for CUDA 11:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda110==1.23.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda110==1.23.0
Or use direct download links (CUDA 12.0):
Or use direct download links (CUDA 11.0):
FFmpeg source code:
Libsndfile source code:
Published by stiepan almost 2 years ago
This DALI release includes the following key features and enhancements:
experimental.inputs.video
operator that supports decoding video from memorybuffer across multiple iterations to reduce memory usage (#4519).fn.experimental.filter
(convolution) operator (#4298, #4525).No major issues were fixed in this release.
VideoInput
operator for the CPU (#4519)VideoInput
operator (#4513)InputOperator
from ExternalSource
(#4505)Operator
inheritance from VideoDecoderBase
(#4508)#include <optional>
. (#4520)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==1.22.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda120==1.22.0
or for CUDA 11:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda110==1.22.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda110==1.22.0
Or use direct download links (CUDA 12.0):
Or use direct download links (CUDA 11.0):
FFmpeg source code:
Libsndfile source code:
Published by JanuszL almost 2 years ago
This DALI release includes the following key features and enhancements:
experimental.decoders.image
experimental.decoders.image_crop
experimental.decoders.image_random_crop
experimental.decoders.image_slice
The following issues were fixed in this release:
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.Install via pip for CUDA 10.2:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda102==1.21.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda102==1.21.0
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==1.21.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda110==1.21.0
Or use direct download links (CUDA 10.2):
Or use direct download links (CUDA 11.0):
FFmpeg source code:
Libsndfile source code: