afisk
September 20, 2021, 6:09pm
1
I have found the requirements for training a TAO Toolkit model, but I am wondering what they are for running. What are the hardware requirements/recommendations for Running the LPRNet with TensorRT? Does the system the LPRNet runs on need to match the system it was trained on in any way?
Thank you
NVES
September 21, 2021, 4:28am
2
Hi ,
We recommend you to check the supported features from the below link.
These support matrices provide a look into the supported platforms, features, and hardware capabilities of the NVIDIA TensorRT 8.4.3 APIs, parsers, and layers.
You can refer below link for all the supported operators list.
For unsupported operators, you need to create a custom plugin to support the operation
<!--- 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
Thanks!