TensorRT

Ragu_23 · September 4, 2021, 3:18am

Description

There is no pixel shuffle layer in Tensor RT 8. Can Anyone suggest a way to do PIxel shuffle operation using TensorRT Python API?

Environment

TensorRT Version : 8.0
GPU Type :
Nvidia Driver Version : 470.57.02
CUDA Version : 11.3
CUDNN Version : 8.2
Operating System + Version : ubuntu20.04
Python Version (if applicable) : 3.8
TensorFlow Version (if applicable) : 2.5
PyTorch Version (if applicable) :
Baremetal or Container (if container which image + tag) :

Relevant Files

Please attach or include links to any models, data, files, or scripts necessary to reproduce your issue. (Github repo, Google Drive, Dropbox, etc.)

Steps To Reproduce

Please include:

Exact steps/commands to build your repro
Exact steps/commands to run your repro
Full traceback of errors encountered

NVES · September 4, 2021, 5:07am

Hi,
Can you try running your model with trtexec command, and share the “”–verbose"" log in case if the issue persist
https://github.com/NVIDIA/TensorRT/tree/master/samples/opensource/trtexec

You can refer below link for all the supported operators list, in case any operator is not supported you need to create a custom plugin to support that operation

github.com

onnx/onnx-tensorrt/blob/main/docs/operators.md

<!--- SPDX-License-Identifier: Apache-2.0 -->

# Supported ONNX Operators

TensorRT 8.4 supports operators up to Opset 17. Latest information of ONNX operators can be found [here](https://github.com/onnx/onnx/blob/master/docs/Operators.md)

TensorRT supports the following ONNX data types: DOUBLE, FLOAT32, FLOAT16, INT8, and BOOL

> Note: There is limited support for INT32, INT64, and DOUBLE types. TensorRT will attempt to cast down INT64 to INT32 and DOUBLE down to FLOAT, clamping values to `+-INT_MAX` or `+-FLT_MAX` if necessary.

See below for the support matrix of ONNX operators in ONNX-TensorRT.

## Operator Support Matrix

| Operator                  | Supported  | Supported Types | Restrictions                                                                                                           |
|---------------------------|------------|-----------------|------------------------------------------------------------------------------------------------------------------------|
| Abs                       | Y          | FP32, FP16, INT32 |
| Acos                      | Y          | FP32, FP16 |
| Acosh                     | Y          | FP32, FP16 |
| Add                       | Y          | FP32, FP16, INT32 |

This file has been truncated. show original

Also, request you to share your model and script if not shared already so that we can help you better.

Meanwhile, for some common errors and queries please refer to below link:

Thanks!

Topic		Replies	Views
nVidia release versions compatibility TensorRT	4	877	September 20, 2023
TensorRT, result error in fp16 TensorRT	1	693	October 19, 2021
Detectron2: faster inferencing TensorRT	2	1377	April 29, 2022
TensorRT version for CUDA 12.0 TensorRT tensorrt , cuda	1	1722	March 14, 2023
Does TensorRT exploit parallelism in a computational graph during inference? TensorRT	2	524	April 18, 2023
Can't install tensorrt package python TensorRT tensorrt , cudnn	5	2160	November 24, 2023
nvonnxparser::IParse::parse() fail,and trt report paramenter check fail TensorRT tensorrt	7	1195	July 12, 2021
Engine upgrade TensorRT	2	340	March 27, 2023
I meet an error when I doing onnx2tensorRT TensorRT tensorrt	2	1259	January 7, 2022
Mod operator unsupported in TensorRT 8.4.1 (included w/ Jetpack 5.0.2) TensorRT jetpack , tensorrt , cuda , jetson-inference , onnx	5	1516	January 2, 2023