spikingjelly
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fangwei123456
在用AttributeMonitor记录神经元的电压值的时候，已经设置了m.store_v_seq = True，但还是只记录一个时间的电压
我的代码如下：
model.eval()
for m in model.fc.modules():
if isinstance(m, neuron.LIFNode):
m.store_v_seq = True
print(model.fc[-1].store_v_seq)
monitor_v = monitor.AttributeMonitor(attribute_name='v', pre_forward=False, net=model.fc[-1], instance=neuron.LIFNode)
monitor_o = monitor.OutputMonitor(net=model.fc[-1], instance=neuron.LIFNode)
with torch.no_grad():
data_iter = iter(test_loader)
data, label = next(data_iter)
# 只取批次中的第一个样本
data = data[0]
label = label[0]
print(f'Label of the first sample: {label.item()}')
data = data.to(device)
out_fr = model(data)
out_spikes_counter_frequency = out_fr.cpu().numpy()
print(f'Firing rate: {out_spikes_counter_frequency}')
v_list = monitor_v.records[0].squeeze()
s_list = monitor_o.records[0].squeeze()
print(monitor_v.records, monitor_o.records, v_list.shape, s_list.shape)
numpy_array_v_list = v_list.detach().cpu().numpy()
numpy_array_s_list = s_list.detach().cpu().numpy()
visualizing.plot_1d_spikes(spikes=np.asarray(numpy_array_s_list), title='Membrane Potentials', xlabel='Simulating Step',ylabel='Neuron Index', dpi=300)
numpy_array_s_list = numpy_array_s_list.flatten()
visualizing.plot_one_neuron_v_s(numpy_array_v_list, numpy_array_s_list, v_threshold=1, v_reset=0, figsize=(12, 8), dpi=300)
plt.show()
functional.reset_net(model)
del monitor_v,monitor_o
请问作者大大，已经设置了m.store_v_seq = True，但v监视器输出如下：
[tensor([[0.6333, 0.0000, 0.7034, 0.6480]], device='cuda:0')]，只有一个时间步的，而s监视器正常有32个时间步
