Could not decode serialized type: np.ndarray. This could be because a required module is missing

Description

I'm trying to generate a calibration cache file for post-training-quantizatio using Polygraphy.
For which I created custom input json file referring to this [https://github.com/NVIDIA/TensorRT/blob/main/tools/Polygraphy/how-to/use_custom_input_data.md]. The input shape of the model is (1,3,384,640).

The command used is below -
polygraphy convert model.onnx --int8 --load-inputs custom.json --calibration-cache custom_calib.cache -o model_trt.engine [I] Loading input data from custom.json [!] Could not decode serialized type: np.ndarray. This could be because a required module is missing.

Environment

TensorRT Version: 10.0.1.6-1

NVIDIA GPU: Tesla T4

NVIDIA Driver Version: 470.239.06

CUDA Version: 11.4

CUDNN Version:

Operating System: Ubuntu 20.04.6 LTS

Python Version (if applicable): 3.8.10

Tensorflow Version (if applicable):

PyTorch Version (if applicable):

Baremetal or Container (if so, version):

Relevant Files

Model link:

Steps To Reproduce

Commands or scripts: polygraphy convert model.onnx --int8 --load-inputs custom.json --calibration-cache custom_calib.cache -o model_trt.engine

Have you tried the latest release?:

Can this model run on other frameworks? For example run ONNX model with ONNXRuntime (polygraphy run <model.onnx> --onnxrt): Yes

Start by reproducing the reported polygraphy convert command with the attached custom.json, focusing on how the input data is serialized and decoded as np.ndarray. Confirm the failure and identify the needed correction so the command can load the inputs and produce the calibration cache and TensorRT engine.