Bug in forward trained model
Closed this issue · 1 comments
JNaranjo-Alcazar commented
Hi, I am trying to create an inference file (hopefully i will try to make a pull request).
The inference file has the following piece of code:
for batch in inference_dataloader:
features, head_outputs = module.forward(batch[0])
where batch[0]
is a Torch Size of [T, N, C, H, W]
The problem appears in line 132 of spiking_vgg.py
.
The error is the following:
File "/src/inference.py", line 107, in main
features, head_outputs = module.forward(batch[0])
File "/src/object_detection_module.py", line 73, in forward
features = self.backbone(events)
File "/opt/conda/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "/src/models/detection_backbone.py", line 42, in forward
feature_maps = self.model(x, classify=False)
File "/opt/conda/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "/src/models/spiking_vgg.py", line 132, in forward
x_seq = functional.seq_to_ann_forward(x, self.features[0])
File "/opt/conda/lib/python3.8/site-packages/spikingjelly/clock_driven/functional.py", line 568, in seq_to_ann_forward
y = m(y)
File "/opt/conda/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "/opt/conda/lib/python3.8/site-packages/spikingjelly/clock_driven/neuron.py", line 1114, in forward
spike_seq, self.v_seq = neuron_kernel.MultiStepParametricLIFNodePTT.apply(
File "/opt/conda/lib/python3.8/site-packages/spikingjelly/clock_driven/neuron_kernel.py", line 1162, in forward
cu_kernel_opt.wrap_args_to_raw_kernel(
File "/opt/conda/lib/python3.8/site-packages/spikingjelly/clock_driven/cu_kernel_opt.py", line 64, in wrap_args_to_raw_kernel
assert item.device.id == device
AssertionError
It seems that is a spikingjelly issue. Any ideas in order to solve this?
Thanks in advance
liberary233 commented
I also encountered this problem······has anyone solved it?