22.02 - 2022-02-04
- New plugins: decodeBbox3DPlugin, pillarScatterPlugin, and voxelGeneratorPlugin
- Extend Megatron LayerNorm plugins to support larger hidden sizes
- Refactored EfficientNMS plugin for TFTRT and added implicit batch mode support
- Update base TensorRT version to 8.2.3.0
- GPT-2 greedy search speedup - now runs on GPU
- Updates to TensorRT developer tools
- Updated ONNX parser to v8.2.3.0
- Minor updates and bugfixes
- Samples: TFOD, GPT-2, demo/BERT
- Plugins: proposalPlugin, geluPlugin, bertQKVToContextPlugin, batchedNMS
- Unused source file(s) in demo/BERT
8.2.1 GA - 2021-11-24
TensorRT OSS release corresponding to TensorRT 8.2.1.8 GA release.
-
Updates since TensorRT 8.2.0 EA release.
-
Please refer to the TensorRT 8.2.1 GA release notes for more information.
-
ONNX parser v8.2.1
- Removed duplicate constant layer checks that caused some performance regressions
- Fixed expand dynamic shape calculations
- Added parser-side checks for
Scatter
layer support
-
Sample updates
- Added Tensorflow Object Detection API converter samples, including Single Shot Detector, Faster R-CNN and Mask R-CNN models
- Multiple enhancements in HuggingFace transformer demos
- Added multi-batch support
- Fixed resultant performance regression in batchsize=1
- Fixed T5 large/T5-3B accuracy issues
- Added notebooks for T5 and GPT-2
- Added CPU benchmarking option
- Deprecated
kSTRICT_TYPES
(strict type constraints). Equivalent behaviour now achieved by settingPREFER_PRECISION_CONSTRAINTS
,DIRECT_IO
, andREJECT_EMPTY_ALGORITHMS
- Removed
sampleMovieLens
- Renamed sampleReformatFreeIO to sampleIOFormats
- Add
idleTime
option for samples to control qps - Specify default value for
precisionConstraints
- Fixed reporting of TensorRT build version in trtexec
- Fixed
combineDescriptions
typo in trtexec/tracer.py - Fixed usages of of
kDIRECT_IO
-
Plugin updates
EfficientNMS
plugin support extended to TF-TRT, and for clang builds.- Sanitize header definitions for BERT fused MHA plugin
- Separate C++ and cu files in
splitPlugin
to avoid PTX generation (required for CUDA enhanced compatibility support) - Enable C++14 build for plugins
-
ONNX tooling updates
- onnx-graphsurgeon upgraded to v0.3.14
- Polygraphy upgraded to v0.33.2
- pytorch-quantization toolkit upgraded to v2.1.2
-
Build and container fixes
- Add
SM86
target to defaultGPU_ARCHS
for platforms with cuda-11.1+ - Remove deprecated
SM_35
and addSM_60
to defaultGPU_ARCHS
- Skip CUB builds for cuda 11.0+ #1455
- Fixed cuda-10.2 container build failures in Ubuntu 20.04
- Add native ARM server build container
- Install devtoolset-8 for updated g++ version in CentOS7
- Added a note on supporting c++14 builds for CentOS7
- Fixed docker build for large UIDs #1373
- Updated README instructions for Jetpack builds
- Add
-
demo enhancements
- Updated Tacotron2 instructions and add CPU benchmarking
- Fixed issues in demoBERT python notebook
-
Documentation updates
- Updated Python documentation for
add_reduce
,add_top_k
, andISoftMaxLayer
- Renamed default GitHub branch to
main
and updated hyperlinks
- Updated Python documentation for
8.2.0 EA - 2021-10-05
- Demo applications showcasing TensorRT inference of HuggingFace Transformers.
- Support is currently extended to GPT-2 and T5 models.
- Added support for the following ONNX operators:
Einsum
IsNan
GatherND
Scatter
ScatterElements
ScatterND
Sign
Round
- Added support for building TensorRT Python API on Windows.
- Notable API updates in TensorRT 8.2.0.6 EA release. See TensorRT Developer Guide for details.
- Added three new APIs,
IExecutionContext: getEnqueueEmitsProfile()
,setEnqueueEmitsProfile()
, andreportToProfiler()
which can be used to collect layer profiling info when the inference is launched as a CUDA graph. - Eliminated the global logger; each
Runtime
,Builder
orRefitter
now has its own logger. - Added new operators:
IAssertionLayer
,IConditionLayer
,IEinsumLayer
,IIfConditionalBoundaryLayer
,IIfConditionalOutputLayer
,IIfConditionalInputLayer
, andIScatterLayer
. - Added new
IGatherLayer
modes:kELEMENT
andkND
- Added new
ISliceLayer
modes:kFILL
,kCLAMP
, andkREFLECT
- Added new
IUnaryLayer
operators:kSIGN
andkROUND
- Added new runtime class
IEngineInspector
that can be used to inspect the detailed information of an engine, including the layer parameters, the chosen tactics, the precision used, etc. ProfilingVerbosity
enums have been updated to show their functionality more explicitly.
- Added three new APIs,
- Updated TensorRT OSS container defaults to cuda 11.4
- CMake to target C++14 builds.
- Updated following ONNX operators:
Gather
andGatherElements
implementations to natively support negative indicesPad
layer to support ND padding, along withedge
andreflect
padding mode supportIf
layer with general performance improvements.
- Removed
sampleMLP
. - Several flags of trtexec have been deprecated:
--explicitBatch
flag has been deprecated and has no effect. When the input model is in UFF or in Caffe prototxt format, the implicit batch dimension mode is used automatically; when the input model is in ONNX format, the explicit batch mode is used automatically.--explicitPrecision
flag has been deprecated and has no effect. When the input ONNX model contains Quantization/Dequantization nodes, TensorRT automatically uses explicit precision mode.--nvtxMode=[verbose|default|none]
has been deprecated in favor of--profilingVerbosity=[detailed|layer_names_only|none]
to show its functionality more explicitly.
21.10 - 2021-10-05
- Benchmark script for demoBERT-Megatron
- Dynamic Input Shape support for EfficientNMS plugin
- Support empty dimensions in ONNX
- INT32 and dynamic clips through elementwise in ONNX parser
- Bump TensorRT version to 8.0.3.4
- Use static shape for only single batch single sequence input in demo/BERT
- Revert to using native FC layer in demo/BERT and FCPlugin only on older GPUs.
- Update demo/Tacotron2 for TensorRT 8.0
- Updates to TensorRT developer tools
- Polygraphy v0.33.0
- Added various examples, a CLI User Guide and how-to guides.
- Added experimental support for DLA.
- Added a
data to-input
tool that can combine inputs/outputs created by--save-inputs
/--save-outputs
. - Added a
PluginRefRunner
which provides CPU reference implementations for TensorRT plugins - Made several performance improvements in the Polygraphy CUDA wrapper.
- Removed the
to-json
tool which was used to convert Pickled data generated by Polygraphy 0.26.1 and older to JSON.
- Bugfixes and documentation updates in pytorch-quantization toolkit.
- Polygraphy v0.33.0
- Bumped up package versions: tensorflow-gpu 2.5.1, pillow 8.3.2
- ONNX parser enhancements and bugfixes
- Update ONNX submodule to v1.8.0
- Update convDeconvMultiInput function to properly handle deconvs
- Update RNN documentation
- Update QDQ axis assertion
- Fix bidirectional activation alpha and beta values
- Fix opset10
Resize
- Fix shape tensor unsqueeze
- Mark BOOL tiles as unsupported
- Remove unnecessary shape tensor checks
- N/A
21.09 - 2021-09-22
- Add
ONNX2TRT_VERSION
overwrite in CMake.
- Updates to TensorRT developer tools
- Fix assertion in EfficientNMSPlugin
- N/A
21.08 - 2021-08-05
- Add demoBERT and demoBERT-MT (sparsity) benchmark data for TensorRT 8.
- Added example python notebooks
- Updated samples and plugins directory structure
- Updates to TensorRT developer tools
- README fix to update build command for native aarch64 builds.
- N/A
21.07 - 2021-07-21
Identical to the TensorRT-OSS 8.0.1 Release.
8.0.1 - 2021-07-02
- Added support for the following ONNX operators:
Celu
,CumSum
,EyeLike
,GatherElements
,GlobalLpPool
,GreaterOrEqual
,LessOrEqual
,LpNormalization
,LpPool
,ReverseSequence
, andSoftmaxCrossEntropyLoss
details. - Rehauled
Resize
ONNX operator, now fully supporting the following modes:- Coordinate Transformation modes:
half_pixel
,pytorch_half_pixel
,tf_half_pixel_for_nn
,asymmetric
, andalign_corners
. - Modes:
nearest
,linear
. - Nearest Modes:
floor
,ceil
,round_prefer_floor
,round_prefer_ceil
.
- Coordinate Transformation modes:
- Added support for multi-input ONNX
ConvTranpose
operator. - Added support for 3D spatial dimensions in ONNX
InstanceNormalization
. - Added support for generic 2D padding in ONNX.
- ONNX
QuantizeLinear
andDequantizeLinear
operators leverageIQuantizeLayer
andIDequantizeLayer
.- Added support for tensor scales.
- Added support for per-axis quantization.
- Added
EfficientNMS_TRT
,EfficientNMS_ONNX_TRT
plugins and experimental support for ONNXNonMaxSuppression
operator. - Added
ScatterND
plugin. - Added TensorRT QuickStart Guide.
- Added new samples: engine_refit_onnx_bidaf builds an engine from ONNX BiDAF model and refits engine with new weights, efficientdet and efficientnet samples for demonstrating Object Detection using TensorRT.
- Added support for Ubuntu20.04 and RedHat/CentOS 8.3.
- Added Python 3.9 support.
- Update Polygraphy to v0.30.3.
- Update ONNX-GraphSurgeon to v0.3.10.
- Update Pytorch Quantization toolkit to v2.1.0.
- Notable TensorRT API updates
- TensorRT now declares API’s with the
noexcept
keyword. All TensorRT classes that an application inherits from (such as IPluginV2) must guarantee that methods called by TensorRT do not throw uncaught exceptions, or the behavior is undefined. - Destructors for classes with
destroy()
methods were previously protected. They are now public, enabling use of smart pointers for these classes. Thedestroy()
methods are deprecated.
- TensorRT now declares API’s with the
- Moved
RefitMap
API from ONNX parser to core TensorRT. - Various bugfixes for plugins, samples and ONNX parser.
- Port demoBERT to tensorflow2 and update UFF samples to leverage nvidia-tensorflow1 container.
IPlugin
andIPluginFactory
interfaces were deprecated in TensorRT 6.0 and have been removed in TensorRT 8.0. We recommend that you write new plugins or refactor existing ones to target theIPluginV2DynamicExt
andIPluginV2IOExt
interfaces. For more information, refer to Migrating Plugins From TensorRT 6.x Or 7.x To TensorRT 8.x.x.- For plugins based on
IPluginV2DynamicExt
andIPluginV2IOExt
, certain methods with legacy function signatures (derived fromIPluginV2
andIPluginV2Ext
base classes) which were deprecated and marked for removal in TensorRT 8.0 will no longer be available.
- For plugins based on
- Removed
samplePlugin
since it showcased IPluginExt interface, which is no longer supported in TensorRT 8.0. - Removed
sampleMovieLens
andsampleMovieLensMPS
. - Removed Dockerfile for Ubuntu 16.04. TensorRT 8.0 debians for Ubuntu 16.04 require python 3.5 while minimum required python version for TensorRT OSS is 3.6.
- Removed support for PowerPC builds, consistent with TensorRT GA releases.
- We had deprecated the Caffe Parser and UFF Parser in TensorRT 7.0. They are still tested and functional in TensorRT 8.0, however, we plan to remove the support in a future release. Ensure you migrate your workflow to use
tf2onnx
,keras2onnx
or TensorFlow-TensorRT (TF-TRT). - Refer to TensorRT 8.0.1 GA Release Notes for additional details
21.06 - 2021-06-23
- Add switch for batch-agnostic mode in NMS plugin
- Add missing model.py in
uff_custom_plugin
sample
- Update to Polygraphy v0.29.2
- Update to ONNX-GraphSurgeon v0.3.9
- Fix numerical errors for float type in NMS/batchedNMS plugins
- Update demoBERT input dimensions to match Triton requirement #1051
- Optimize TLT MaskRCNN plugins:
- enable fp16 precision in multilevelCropAndResizePlugin and multilevelProposeROIPlugin
- Algorithms optimization for NMS kernels and ROIAlign kernel
- Fix invalid cuda config issue when bs is larger than 32
- Fix issues found on Jetson NANO
- Removed fcplugin from demoBERT to improve latency
21.05 - 2021-05-20
- Extended support for ONNX operator
InstanceNormalization
to 5D tensors - Support negative indices in ONNX
Gather
operator - Add support for importing ONNX double-typed weights as float
- ONNX-GraphSurgeon (v0.3.7) support for models with externally stored weights
- Update ONNX-TensorRT to 21.05
- Relicense ONNX-TensorRT under Apache2
- demoBERT builder fixes for multi-batch
- Speedup demoBERT build using global timing cache and disable cuDNN tactics
- Standardize python package versions across OSS samples
- Bugfixes in multilevelProposeROI and bertQKV plugin
- Fix memleaks in samples logger
21.04 - 2021-04-12
- SM86 kernels for BERT MHA plugin
- Added opset13 support for
SoftMax
,LogSoftmax
,Squeeze
, andUnsqueeze
. - Added support for the
EyeLike
andGatherElements
operators.
- Updated TensorRT version to v7.2.3.4.
- Update to ONNX-TensorRT 21.03
- ONNX-GraphSurgeon (v0.3.4) - updates fold_constants to correctly exit early.
- Set default CUDA_INSTALL_DIR #798
- Plugin bugfixes, qkv kernels for sm86
- Fixed GroupNorm CMakeFile for cu sources #1083
- Permit groupadd with non-unique GID in build containers #1091
- Avoid
reinterpret_cast
#146 - Clang-format plugins and samples
- Avoid arithmetic on void pointer in multilevelProposeROIPlugin.cpp #1028
- Update BERT plugin documentation.
- Removes extra terminate call in InstanceNorm
21.03 - 2021-03-09
- Optimized FP16 NMS/batchedNMS plugins with n-bit radix sort and based on
IPluginV2DynamicExt
ProposalDynamic
andCropAndResizeDynamic
plugins based onIPluginV2DynamicExt
- ONNX-TensorRT v21.03 update
- ONNX-GraphSurgeon v0.3.3 update
- Bugfix for
scaledSoftmax
kernel
- N/A
21.02 - 2021-02-01
- TensorRT Python API bindings
- TensorRT Python samples
- FP16 support to batchedNMSPlugin #1002
- Configurable input size for TLT MaskRCNN Plugin #986
- TensorRT version updated to 7.2.2.3
- ONNX-TensorRT v21.02 update
- Polygraphy v0.21.1 update
- PyTorch-Quantization Toolkit v2.1.0 update
- Documentation update, ONNX opset 13 support, ResNet example
- ONNX-GraphSurgeon v0.28 update
- demoBERT builder updated to work with Tensorflow2 (in compatibility mode)
- Refactor Dockerfiles for OSS container
- N/A
20.12 - 2020-12-18
- Add configurable input size for TLT MaskRCNN Plugin
- Update symbol export map for plugins
- Correctly use channel dimension when creating Prelu node
- Fix Jetson cross compilation CMakefile
- N/A
20.11 - 2020-11-20
- API documentation for ONNX-GraphSurgeon
- N/A
20.10 - 2020-10-22
- Polygraphy v0.20.13 - Deep Learning Inference Prototyping and Debugging Toolkit
- PyTorch-Quantization Toolkit v2.0.0
- Updated BERT plugins for variable sequence length inputs
- Optimized kernels for sequence lengths of 64 and 96 added
- Added Tacotron2 + Waveglow TTS demo #677
- Re-enable
GridAnchorRect_TRT
plugin with rectangular feature maps #679 - Update batchedNMS plugin to IPluginV2DynamicExt interface #738
- Support 3D inputs in InstanceNormalization plugin #745
- Added this CHANGELOG.md
- ONNX GraphSurgeon - v0.2.7 with bugfixes, new examples.
- demo/BERT bugfixes for Jetson Xavier
- Updated build Dockerfile to cuda-11.1
- Updated ClangFormat style specification according to TensorRT coding guidelines
- N/A
7.2.1 - 2020-10-20
- Polygraphy v0.20.13 - Deep Learning Inference Prototyping and Debugging Toolkit
- PyTorch-Quantization Toolkit v2.0.0
- Updated BERT plugins for variable sequence length inputs
- Optimized kernels for sequence lengths of 64 and 96 added
- Added Tacotron2 + Waveglow TTS demo #677
- Re-enable
GridAnchorRect_TRT
plugin with rectangular feature maps #679 - Update batchedNMS plugin to IPluginV2DynamicExt interface #738
- Support 3D inputs in InstanceNormalization plugin #745
- Added this CHANGELOG.md
- ONNX GraphSurgeon - v0.2.7 with bugfixes, new examples.
- demo/BERT bugfixes for Jetson Xavier
- Updated build Dockerfile to cuda-11.1
- Updated ClangFormat style specification according to TensorRT coding guidelines
- N/A