Hi, I want to cast a int32 tensor to float type. How can I do that in TensorRT. I tried the Identity layer but it is not supported.
Hi, Please refer to the below links to perform inference in INT8
Hi, I am not doing INT8 quantization. What I asked is how to convert a INT32 tensor to a float precision tensor. More specifically, I want to feed second output tensor of ITopKLayer (INT32) as the input of IResizeLayer.
INT32 is for indices.
Could you please let us know is there a specific reason that you want to convert indices to float?
In some case of semantic segmentation, performing TopK (argmax) in full-size segmentation output may slow-down the pipeline. We want to perform TopK in small-size segmentation output and then scale-up the max indices mask to the origin size, all by TensorRT layers
INT32->kFloat is actually supported operation by
nvinfer1::IIdentityLayer. But looks like document not included it. Unfortunately we couldn’t find sample to share.
We request you to try and if you face any issues please share logs, issue related scripts for better assistance.
Hi, I tried again with a simple onnx with Cast operator which will be parsed as nvinfer1::IIdentityLayer by trtexec tool.
TensorRT 7.1.3 (Jetpack): The TRT engine built succesfully
TensorRT 6.3.1 (DriveOS 5.2 release): I get some error. Sample onnx model and log are attached below.
So, maybe INT32 and FLOAT conversion is not supported by TensorRT 6?temp.onnx (175 Bytes) TensorRT6.3.1-trtexec.log (6.8 KB)
With latest TRT version we could successfully generate the engine.
Yes, convert between FP32 and INT is TRT 7.0+ feature. It’s not supported in TRT version 6.