[TensorRT] ERROR: Parameter check failed at: engine.cpp::resolveSlots::1318, condition: allInputDimensionsSpecified(routine)

AI & Data Science Deep Learning (Training & Inference) TensorRT
1

Description

I build Retinaface model from Pytorch → Onnx → TensorRT.
Firstly, i build .onnx with dynamic batch as follow

input_names = ["input"]
    output_names = ["output"]
    inputs = torch.randn(1, 3, args.long_side, args.long_side).to(device)
    dynamic_axes = {
        'input': {
            0: 'batch_size'
        },
        'output': {
            0: 'batch_size'
        }
    }

    torch_out = torch.onnx._export(net, 
        inputs,
        output_onnx,
        export_params=True,
        verbose=False,
        input_names=input_names,
        output_names=output_names,
        dynamic_axes=dynamic_axes,
        opset_version=11
    )

Then i use trtexec command to generate engine files:

trtexec --onnx=Retinaface_m25_dynamic_batch.onnx --verbose --explicitBatch --minShapes=input:1x3x640x640 --optShapes=input:4x3x640x640 --maxShapes=input:8x3x640x640 --shapes=input:5x3x640x640 --saveEngine=./models/weights/retinaface.trt

I inference as follow in onnx_yolov3 python example in tensorrt repo and got this error:

[TensorRT] ERROR: Parameter check failed at: engine.cpp::resolveSlots::1318, condition: allInputDimensionsSpecified(routine)

i debug and it happen after this line:

context.execute_async(bindings=bindings, stream_handle=stream.handle)

I don’t know how to fix this problem. Plz help me.

Environment

TensorRT Version: tensorrt-7.2.3.4
GPU Type: T4
Nvidia Driver Version: 455.32
CUDA Version: 11.1
CUDNN Version: 8.0.5
Operating System + Version: Ubuntu 18.04
Python Version (if applicable): 3.7
PyTorch Version (if applicable): 1.9
Baremetal or Container (if container which image + tag):

Relevant Files

Steps To Reproduce

Please include:

  • Exact steps/commands to build your repro
  • Exact steps/commands to run your repro
  • Full traceback of errors encountered
2

Hi,
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:

  1. validating your model with the below snippet

check_model.py

import sys
import onnx
filename = yourONNXmodel
model = onnx.load(filename)
onnx.checker.check_model(model).
2) Try running your model with trtexec command.
https://github.com/NVIDIA/TensorRT/tree/master/samples/opensource/trtexec
In case you are still facing issue, request you to share the trtexec “”–verbose"" log for further debugging
Thanks!

4

Hi @NVES ,
I already checked by onnx script and i also use trt loadEngine to verify it worked, here is trtexec with --verbose option and onnx model .
Retinaface_m25_dynamic_batch.onnx (1.6 MB)
verbose_trt.txt (740.8 KB)

1 Like
5

Please share us issue repro inference script to try from our end.

6

Sorry i can’t share my script but it look like this repo

I made a little bit change from that. But not much.

7

Please help me! I can’t find any solution for this.

8

Hi @nguyenkhacduyngoc,

Its may be difficult to debug without inference script and complete error logs. You may be DM us. Please make sure you’re creating stream and allocating memory correctly.

9

Hi, tks for your help.

I finally found the solution, it was my bad.
My script didn’t contain the set_binding_shape for context in new inference.

context.set_binding_shape(0, (BATCH, 3, INPUT_H, INPUT_W))
3 Likes