[BUG]: wrong argtype definitions when calling the c++ lib from python

[Naplesoul]

Describe the bug
std::bad_alloc when python calls convolution() in libintel_npu_acceleration_library.so
Maybe caused by the wrong argtype definition in bindings.py

To Reproduce
Steps to reproduce the behavior:
python==3.10, torch==2.4.1+cpu, torchvision==0.19.1+cpu, openvino==2024.3.0, intel_npu_acceleration_library==1.3.0
run the following python code:

import torch
from torchvision import models
import intel_npu_acceleration_library

pytorch_model = models.resnet50(weights=models.ResNet50_Weights.IMAGENET1K_V1)
optimized_model = intel_npu_acceleration_library.compile(pytorch_model, dtype=torch.int8)
input = torch.rand(1, 3, 224, 224, dtype=torch.float32)
output = optimized_model(input)

output:

terminate called after throwing an instance of 'std::bad_alloc'
  what():  std::bad_alloc
Aborted (core dumped)

Possible Reason
stack trace:
ps: -O0 -ggdb is added in CMakeLists.txt to export debug symbols and install the lib from src by python setup.py install
run python with gdb and get the following stack backtrace when throwing std::bad_alloc:

[BUG]: in stack 15 convolution, argument pad_begins_size=140733193388034 (it is 0x7fff00000002)

In the source of 1.3.0 and later, the argtypes in intel_npu_acceleration_library/backend/bindings.py do not match with the ones in src/bindings.cpp.

In the python file, the sizes are defined as ctypes.c_int, while in the c++ source, they are defined as size_t, which are incompatible with each other.

Possible Solution
Change the argtypes to ctypes.c_uint64 will fix the bug.
BTW, many other argtypes are wrong in bindings.py, e.g. dim0 & dim1 in linear(), they have not been fixed yet in the latest commit.

Platform

• HW: Intel Ultra 9 185H (Meteor Lake)
• OS: Ubuntu 22.04
• Version 1.3.0 and later.