module false

[bia1o]

Is there an accelerating module in spikingjelly? from spikingjelly.clock_driven import functional, layer, surrogate, accelerating

[fangwei123456]

This module has been removed after the 04 version.

https://github.com/fangwei123456/spikingjelly/tree/0.0.0.0.4/spikingjelly/clock_driven

[bia1o]

Ok, thank you. By the way, is there any way you can visualize the DVS128 GESTURE dataset? I want to see what gesture each sample is

[bia1o]

I didn't find accelerating module in https://github.com/fangwei123456/spikingjelly/tree/0.0.0.0.4/spikingjelly/clock_driven, Could you please send this module code again?

[fangwei123456]

is there any way you can visualize the DVS128 GESTURE dataset?

Please refert to the tutorial: https://spikingjelly.readthedocs.io/zh-cn/latest/activation_based_en/neuromorphic_datasets.html

[fangwei123456]

Could you please send this module code again?

You can find this module in an old version: https://github.com/fangwei123456/spikingjelly/blob/7e67cb1cc37271f7192d5a3cbfb32318e5de7ee7/SpikingFlow/softbp/accelerating.py

However, I think that the functions in this module can not accelerate SNNs. I used to believe that they could, but it is a mistake.

[bia1o]

Ok, thank you for your reply! I want to ask what is the time resolution of this SNN? For example, if I do gesture recognition and I set T=16, this is the time step, what is the time resolution?

[fangwei123456]

T=16 is the number of time-steps. The time resolution is not defined in SpikingJelly.

[bia1o]

Ok, thank you for your patient answer. In gesture recognition, does setting T=16 mean that a sample is divided into 16 segments and 16 frames are formed?

[fangwei123456]

does setting T=16 mean that a sample is divided into 16 segments and 16 frames are formed?

Yes.