Migration from TRT5 to TRT7

bnascimento · December 8, 2020, 10:30am

Description

Lack of understanding how to migrate SSD code written for TensorRT5 to the latest TensorRT7.

A clear and concise description of the bug or issue.
While migrating from TensorRT5 to TensorRT7 I stumbled into a lack of understanding how to correctly use the new V2 plugin system on c++. For example, calls like createSSDDetectionOutputPlugin or createSSDAnchorGeneratorPlugin are now deprecated. Is there an example how to use use SSD on TensorRT7?

Environment

Ngc tensorflow 20.8 docker container

TensorRT Version: 7
GPU Type: Titan V
Nvidia Driver Version: 450.66
CUDA Version: 11
CUDNN Version: 8
Operating System + Version: Ubuntu 18.04.4 LTS
Python Version (if applicable): 3.6.9
TensorFlow Version (if applicable): 20.8
PyTorch Version (if applicable):
Baremetal or Container (if container which image + tag): Ngc tensorflow 20.8 docke

SunilJB · December 9, 2020, 8:58am

Hi @bnascimento,
We highly encourage you to move to IPluginV2IOExt or IPluginV2DynamicExt to be able to use all the new plugin functionalities.
Please refer to below sample for your reference:

github.com

NVIDIA/TensorRT/blob/492878b2df3c9bf19a26c2b66cba129f450475bc/plugin/geluPlugin/geluPlugin.cpp

/*
 * Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

#include <cuda.h>
#if CUDA_VERSION >= 10010

#include <cassert>

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