For more details, see the 10.7 GA release notes
- Now prioritizes using plugins over local functions when a corresponding plugin is available in the registry
- Added dynamic axes support for
Squeeze
andUnsqueeze
operations - Added support for parsing mixed-precision
BatchNormalization
nodes in strongly-typed mode
For more details, see the 10.6 GA release notes
- Updated ONNX submodule version to 1.17.0
- Fix issue where conditional layers were incorrectly being added
- Updated local function metadata to contain more information
- Added support for parsing nodes with Quickly Deployable Plugins
- Fixed handling of optional outputs
For more details, see the 10.5 GA release notes.
- Added support for real-valued
STFT
operations - Improved error handling in
IParser
For more details, see the 10.4 GA release notes.
- Added support for tensor
axes
forPad
operations - Added support for
BlackmanWindow
,HammingWindow
, andHannWindow
operations - Improved error handling in
IParserRefitter
- Fixed kernel shape inference in multi-input convolutions
For more details, see the 10.3 GA release notes.
- Added support for tensor
axes
inputs forSlice
nodes - Updated
ScatterElements
importer to use an updated plugin
For more details, see the 10.2 GA release notes.
- Improved error handling with new macros and classes
- Minor changes to op importers for
GRU
andSqueeze
For more details, see the 10.1 GA release notes.
- Added
supportsModelV2
API - Added support for
DeformConv
operation - Added support for
PluginV3
TensorRT Plugins - Marked all IParser and IParserRefitter APIs as
noexcept
- Shape inputs can be passed to custom ops supported by
IPluginV3
-based plugins by indicating the input indices to be interpreted as shape inputs by a node attribute namedtensorrt_plugin_shape_input_indices
.
For more details, see the 10.0 GA release notes.
- Added support for building with with
protobuf-lite
- Fixed issue when parsing and refitting models with nested
BatchNormalization
nodes - Added support for empty inputs in custom plugin nodes
For more details, see the 10.0 EA release notes.
- Added new class
IParserRefitter
that can be used to refit a TensorRT engine with the weights of an ONNX model kNATIVE_INSTANCENORM
is now set to ON by default- Added support for
IPluginV3
interfaces from TensorRT - Added support for
INT4
quantization - Added support for the
reduction
attribute inScatterElements
- Added support for
wrap
padding mode inPad
For more details, see the 9.3 GA release notes for the fixes since 9.2 GA.
- Added native support for
INT32
andINT64
types forArgMin
andArgMax
nodes - Fixed check for valid
zero_point
values inQuantizeLinear
andDequantizeLinear
nodes
For more details, see the 9.2 GA release notes for the fixes since 9.1 GA.
- Added support for
Hardmax
- Fixed type inference for few operators to use native ONNX types
For more details, see the 9.1 GA release notes for the fixes since 9.0 GA.
- Added new
ErrorCode
enums to improve error logging - Added new members to
IParserError
to improve error logging - Added static checkers when parsing nodes, resulting better reporting of errors
For more details, see the 9.0 GA release notes for the fixes since 9.0 EA.
- Added support for FP8 and BF16 datatypes.
- Fixed a bug that previously caused
If
nodes to fail import due to branch output size mismatch - Improved support for importing ONNX Local Functions
For more details, see the 9.0 EA release notes for the fixes since 8.6 GA.
- Added support for INT64 data type. The ONNX parser no longer automatically casts INT64 to INT32.
- Added support for ONNX local functions when parsing ONNX models with the ONNX parser.
- Breaking API Change: In TensorRT 9.0, due to the introduction of INT64 as a supported data type, ONNX models with INT64 I/O require INT64 bindings. Note that prior to this release, such models required INT32 bindings.
- Updated ONNX submodule to v1.14.0.
For more details, see the 8.6 GA release notes for the fixes since 8.6 EA.
- Renamed
kVERSION_COMPATIBLE
flag tokNATIVE_INSTANCENORM
- Added support for N-D
Trilu
- Removed old LSTM importer
- Updated ONNX submodule to v1.13.1.
For more details, see the 8.6 EA release notes for new features added in TensorRT 8.6.
- Added support for
GroupNormalization
,LayerNormalization
,IsInf
operations - Added support for INT32 input types for
Argmin
,Argmax
, andTopK
- Added support for
ReverseSequence
operators with dynamic shapes - Added support for
TopK
operators with dynamicK
values - Added
OnnxParserFlag
enum andsetFlag
interfaces to the ONNX parser to modify the default parsing behavior - Added metadata tracking, now ONNX node metadata will be embedded into TensorRT layers
- All cast operations will now use the new
CastLayer
over the perviousIdentityLayer
.
For more details, see the 8.5 GA release notes for new features added in TensorRT 8.5
- Added the
RandomNormal
,RandomUniform
,MeanVarianceNormalization
,RoiAlign
,Mod
,Trilu
,GridSample
andNonZero
operations - Added native support for the
NonMaxSuppression
operator - Added support for importing ONNX networks with
UINT8
I/O types
- Fixed an issue with output padding with 1D deconv
- Fixed an issue when flattening 1D tensors
- Fixed an issue when parsing String attributes from TRT plugins
- Fixed an issue when importing
If
subgraphs with shared initializer names - Fixied an issue when importing
Loop
subgraphs withINT_MAX
trip counts
- Removed
onnx2trt
binary. See the README.md for alternative binaries to run ONNX model with TensorRT.
- Updated TensorRT version to 8.4.2
- Updated ONNX submodule version to 1.12
- Updated operators support documentation
- Fixed handling of no-op
Flatten
operations - Fixed
allowZero
logic in Reshape operation
- Deprecated
onnx2trt
binary. This will be removed in the next release of TensorRT.
For more details, see the 8.4 GA release notes for new features added in TensorRT 8.4
- Added native FP16 support for importing and manipulating FP16 initializers
- Added support for
Shrink
- Added support for
Xor
- Added dynamic shape support for
ArgMax
andArgMin
- Added dynamic shape support for
Range
for floating point types
- Fixed an issue in tensor name scoping in ONNX models with nested subgraphs
- Fixed misc issues when dealing with empty tensors
- Fixed the operations in the
Celu
importer function - Removed unnecessary reshapes in the
GEMM
importer function
See the 8.2 EA release notes for new features added in TensorRT 8.2.
- Removed duplicate constant layer checks that caused some performance regressions
- Fixed expand dynamic shape calculations
- Added parser-side checks for Scatter layer support
- Added support for the following ONNX operators:
- Einsum
- IsNan
- GatherND
- Scatter
- ScatterElements
- ScatterND
- Sign
- Round
- Updated
Gather
andGatherElements
implementations to natively support negative indices - Updated
Pad
layer to support ND padding, along withedge
andreflect
padding mode support - Updated
If
layer with general performance improvements.
- Rehauled resize 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:
- QuantizeLinear/DequantizeLinear updates:
- Added support for tensor scales
- Added support for per-axis quantization
- Added support for multi-input ConvTranpose
- Added support for generic 2D padding
- Added experimental support for
NonMaxSuppression
- Moved
RefitMap
API to core TensorRT. - Added Datatype column to operators.md
- Added library only build target #659
- Added support for negative gather indices #681
- Added support for
DOUBLE
-typed inputs and weights through downcast to float #674 - Added support for optional plugin fields in FallbackPlugin path #676
- Updated license #657
- Fixed index offset calculation in GatherElements #675
- Clarified dynamic shape support for ReverseSequence
- Added opset13 support for
SoftMax
,LogSoftmax
,Squeeze
, andUnsqueeze
- Added support for the
EyeLike
operator - Added support for the
GatherElements
operator
- Added support for the
ReverseSequence
operator #590 - Updated
parse()
andsupportsModel()
API calls with an optionalmodel_path
parameter to support models with external weights #621 - Added support for the
Celu
operator - Added support for the
CumSum
operator - Added support for the
LessOrEqual
operator - Added support for the
LpNormalization
operator - Added support for the
LpPool
operator - Added support for the
GreaterOrEqual
operator - Added support for dynamic inputs in
onnx_tensorrt
python backend - Added FAQ section for commonly asked questions
- Fixed relative path imports for models with external weights [#619]#619
- Fixed importing loops operators with no loop-carried depedencies #619
- Worked around unsupported BOOL concats through casting #620
- Fixed compilation error with GCC9 #568
- Removed
onnx_tensorrt/config.py
as it is no longer needed
- Added
setup.py
to properly installonnx_tensorrt
python backend - Added 4D transpose for ONNX weights #557
- Fixed slice computations for large slices #558
- Added support for parsing large models with external data
- Added API for interfacing with TensorRT's refit feature
- Updated
onnx_tensorrt
backend to support dynamic shapes - Added support for 3D instance normalizations #515
- Improved clarity on the resize modes TRT supports #512
- Added Changelog
- Unified docker usage between ONNX-TensorRT and TensorRT.
- Removed deprecated docker files.
- Removed deprecated
setup.py
.