Compatibility with the latest NumPy version 1.24 which removes "numpy.int" entry

[CloudyDory]

Read before creating a new issue

• Users who want to use SpikingJelly should first be familiar with the usage of PyTorch.
• If you do not know much about PyTorch, we recommend that the user can learn the basic tutorials of PyTorch.
• Do not ask for help with the basic conception of PyTorch/Machine Learning but not related to SpikingJelly. For these questions, please refer to Google or PyTorch Forums.

For faster response

You can @ the corresponding developers for your issue. Here is the division:

Features	Developers
Neurons and Surrogate Functions	fangwei123456 Yanqi-Chen
CUDA Acceleration	fangwei123456 Yanqi-Chen
Reinforcement Learning	lucifer2859
ANN to SNN Conversion	DingJianhao Lyu6PosHao
Biological Learning (e.g., STDP)	AllenYolk
Others	Grasshlw lucifer2859 AllenYolk Lyu6PosHao DingJianhao Yanqi-Chen fangwei123456

We are glad to add new developers who are volunteering to help solve issues to the above table.

Issue type

• [x] Bug Report
• [ ] Feature Request
• [ ] Help wanted
• [ ] Other

SpikingJelly version

0.0.0.0.14

Description numpy.int was deprecated in NumPy 1.20 and was removed in NumPy 1.24. However, the latest spikingjelly stable version 0.0.0.0.14 still uses it in some of the code, and will cause error.

For example, in spikingjelly\activation_based\auto_cuda\base.py line 233-250,

for key, value in py_dict.items():
    ctype: str = self.cparams[key]
    if isinstance(value, torch.Tensor):
        if value.dtype == torch.float:
            assert startswiths(ctype, ('const float', 'float'))

        elif value.dtype == torch.half:
            assert startswiths(ctype, ('const half2', 'half2'))

    if isinstance(value, cupy.ndarray):
        if value.dtype == np.float32:
            assert startswiths(ctype, ('const float', 'float'))

        elif value.dtype == np.float16:
            assert startswiths(ctype, ('const half2', 'half2'))

        elif value.dtype == np.int:
            assert startswiths(ctype, ('const int', 'int'))

Hope this can be fixed soon.

[fangwei123456]

Hi, this problem has been fixed in the lastest master version. The released 0.0.0.0.14 version can not be modified. You can install SpikingJelly from the latest GitHub code to avoid this bug.

[biphasic]

I ran into the same error, if you could push a new release with the error fixed that would be great! Thank you

[fangwei123456]

@biphasic You can try to install from github source code (not from pip), and check if it is ok.

[biphasic]

yes I did that and it worked well! I benchmarked SpikingJelly against other frameworks, congrats to being the fastest :D https://open-neuromorphic.org/p/snn-library-benchmarks/