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TensorRT OSS v8.0.1
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@rajeevsrao rajeevsrao released this 02 Jul 23:37
· 43 commits to master since this release
8.0.1
eb5de99

TensorRT OSS release corresponding to TensorRT 8.0.1.6 GA release.

Added

  • Added support for the following ONNX operators: Celu, CumSum, EyeLike, GatherElements, GlobalLpPool, GreaterOrEqual, LessOrEqual, LpNormalization, LpPool, ReverseSequence, and SoftmaxCrossEntropyLoss.
  • Rehauled Resize ONNX operator, now fully supporting the following modes:
    • Coordinate Transformation modes: half_pixel, pytorch_half_pixel, tf_half_pixel_for_nn, asymmetric, and align_corners.
    • Modes: nearest, linear.
    • Nearest Modes: floor, ceil, round_prefer_floor, round_prefer_ceil.
  • 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 and DequantizeLinear operators leverage IQuantizeLayer and IDequantizeLayer.
    • Added support for tensor scales.
    • Added support for per-axis quantization.
  • Added EfficientNMS_TRT, EfficientNMS_ONNX_TRT plugins and experimental support for ONNX NonMaxSuppression 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.

Changed

  • 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. The destroy() methods are deprecated.
  • 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.

Removed

  • IPlugin and IPluginFactory 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 the IPluginV2DynamicExt and IPluginV2IOExt 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 and IPluginV2IOExt, certain methods with legacy function signatures (derived from IPluginV2 and IPluginV2Ext base classes) which were deprecated and marked for removal in TensorRT 8.0 will no longer be available.
  • Removed samplePlugin since it showcased IPluginExt interface, which is no longer supported in TensorRT 8.0.
  • Removed sampleMovieLens and sampleMovieLensMPS.
  • 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.

Notes

  • 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).

Signed-off-by: Rajeev Rao rajeevrao@nvidia.com

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