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snntorch.spikevision.spikedata.rst

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snntorch.spikevision.spikedata

All datasets are subclasses of torch.utils.data.Dataset i.e., they have __getitem__ and __len__ methods implemented. Hence, they can all be passed to a torch.utils.data.DataLoader which can load multiple samples in parallel using torch.multiprocessing workers. For example:

nmnist_data = spikevision.data.NMNIST('path/to/nmnist_root/')
data_loader = DataLoader(nmnist_data, 
                         batch_size=4,
                         shuffle=True, 
                         num_workers=args.nThreads)

For further examples on each dataset and its use, please refer to the examples.

NMNIST

snntorch.spikevision.spikedata.nmnist.NMNIST

DVSGesture

snntorch.spikevision.spikedata.dvs_gesture.DVSGesture

SHD

snntorch.spikevision.spikedata.shd.SHD