-
Notifications
You must be signed in to change notification settings - Fork 40
Description
Traceback (most recent call last):
File "tctrack_original/tools/train_tctrackpp.py", line 303, in
main()
File "tctrack_original/tools/train_tctrackpp.py", line 298, in main
train(train_loader, dist_model, optimizer, lr_scheduler, tb_writer)
File "tctrack_original/tools/train_tctrackpp.py", line 187, in train
outputs = model(data,videorange)
File "tctrack/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl
return forward_call(*input, **kwargs)
File "tctrack/lib/python3.9/site-packages/torch/nn/parallel/data_parallel.py", line 168, in forward
outputs = self.parallel_apply(replicas, inputs, kwargs)
File "tctrack/lib/python3.9/site-packages/torch/nn/parallel/data_parallel.py", line 178, in parallel_apply
return parallel_apply(replicas, inputs, kwargs, self.device_ids[:len(replicas)])
File "tctrack/lib/python3.9/site-packages/torch/nn/parallel/parallel_apply.py", line 86, in parallel_apply
output.reraise()
File "tctrack/lib/python3.9/site-packages/torch/_utils.py", line 461, in reraise
raise exception
RuntimeError: Caught RuntimeError in replica 0 on device 0.
Original Traceback (most recent call last):
File "tctrack/lib/python3.9/site-packages/torch/nn/parallel/parallel_apply.py", line 61, in _worker
output = module(*input, **kwargs)
File "tctrack/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl
return forward_call(*input, **kwargs)
File "tctrack_original/pysot/models/utile_tctrackplus/model_builder.py", line 142, in forward
loc,cls2,cls3=self.grader(xf[:,-1,:,:,:],zf,xf[:,:-1,:,:,:].permute(1,0,2,3,4))
File "tctrack/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl
return forward_call(input, **kwargs)
File "tctrack_original/pysot/models/utile_tctrackplus/utile.py", line 99, in forward
ppres=self.conv1(self.xcorr_depthwise(px[0],z))
File "tctrack_original/pysot/models/utile_tctrackplus/utile.py", line 88, in xcorr_depthwise
x = x.reshape(1, batchchannel, x.size(2), x.size(3))
RuntimeError: shape '[1, 8960, 26, 26]' is invalid for input of size 12113920