trtexec --onnx=my_model.onnx --batch=1 --saveEngine=test.engine --verbose
fails with the below error
[06/16/2021-12:03:24] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 498 for ONNX tensor: 498
[06/16/2021-12:03:24] [V] [TRT] ModelImporter.cpp:179: Cast_9 [Cast] outputs: [498 → ()],
[06/16/2021-12:03:24] [V] [TRT] ModelImporter.cpp:103: Parsing node: Neg_10 [Neg]
[06/16/2021-12:03:24] [V] [TRT] ModelImporter.cpp:119: Searching for input: 498
[06/16/2021-12:03:24] [V] [TRT] ModelImporter.cpp:125: Neg_10 [Neg] inputs: [498 → ()],
ERROR: onnx2trt_utils.cpp:1686 In function unaryHelper:
 Assertion failed: validUnaryType
[06/16/2021-12:03:24] [E] Failed to parse onnx file
[06/16/2021-12:03:24] [E] Parsing model failed
[06/16/2021-12:03:24] [E] Engine creation failed
[06/16/2021-12:03:24] [E] Engine set up failed
TensorRT Version: 184.108.40.206
GPU Type: GeForce RTX 3090 , 1070
Nvidia Driver Version: 460.32.03
CUDA Version: 11.2
CUDNN Version: 220.127.116.11
Operating System + Version: ubuntu 20.04
Python Version (if applicable):
TensorFlow Version (if applicable):
PyTorch Version (if applicable):
Baremetal or Container (if container which image + tag):
Steps To Reproduce
trtexec --onnx=midas.onnx --batch=1 --saveEngine=test.engine --verbose
- Exact steps/commands to build your repro
- Exact steps/commands to run your repro
- Full traceback of errors encountered
Request you to share the ONNX model and the script if not shared already so that we can assist you better.
Alongside you can try few things:
- validating your model with the below snippet
filename = yourONNXmodel
model = onnx.load(filename)
2) Try running your model with trtexec command.
In case you are still facing issue, request you to share the trtexec “”–verbose"" log for further debugging
thanks for your response ! I did share the links of log, the model earlier. Please find them my_model.onnx - Google Drive
trt.log - Google Drive
Inference from the onnxmodel works fine.
The following snippet outputs
input shape [1, 3, 512, 512]
output name 1349
model_name = “my_model.onnx”
sess = onnxruntime.InferenceSession(model_name)
input_name = sess.get_inputs().name
print(input_name) # input.1
input_shape = sess.get_inputs().shape
print(“input shape”, input_shape) # [1, 3, 384, 672]
output_name = sess.get_outputs().name
print(“output name”, output_name)
It is known issue. Fix will be available soon in future releases.
Thanks polisetty for your reponse ! Would it be possible to explain whats the actual cause so that I could alter my model !
The main reason for this issue is TRT currently does not support INT32 types for the NEG operator. Fix for this will be available soon in future releases.
Hello. Any updates regarding the issue? Currently using TRT v. 7.2.1 and got the same error.