question about train FVC #16
Description
I want to train the model.
Traceback (most recent call last):
File "/mnt/4t/zy/FVC/main.py", line 304, in
global_step = train(epoch, global_step)
File "/mnt/4t/zy/FVC/main.py", line 202, in train
seqout["rd_loss"].backward()
File "/home/zy/anaconda3/envs/dvc/lib/python3.9/site-packages/torch/_tensor.py", line 396, in backward
torch.autograd.backward(self, gradient, retain_graph, create_graph, inputs=inputs)
File "/home/zy/anaconda3/envs/dvc/lib/python3.9/site-packages/torch/autograd/init.py", line 173, in backward
Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
File "/home/zy/anaconda3/envs/dvc/lib/python3.9/site-packages/torch/autograd/function.py", line 253, in apply
return user_fn(self, *args)
File "/home/zy/anaconda3/envs/dvc/lib/python3.9/site-packages/torch/autograd/function.py", line 399, in wrapper
outputs = fn(ctx, *args)
File "/mnt/4t/zy/FVC/subnet/dcn/deform_conv.py", line 73, in backward
deform_conv_cuda.deform_conv_backward_parameters_cuda(
RuntimeError: view size is not compatible with input tensor's size and stride (at least one dimension spans across two contiguous subspaces). Use .reshape(...) instead.