train error

[isserendipity]

hey! I have tow problems and My torch version is 1.12!
Seemly error is due to fps_pred, y_pred = model(x) .

1. The first one is division by zero .I try to use loss.item() to replace `loss.data[0],but it not work!
   The whole error is

Traceback (most recent call last):
File "D:\project\python2\CCPD-master\rpnet\rpnet.py", line 422, in
model_conv = train_model(model_conv, criterion, optimizer_conv, num_epochs=epochs)
File "D:\project\python2\CCPD-master\rpnet\rpnet.py", line 412, in train_model
print('%s %s %s\n' % (epoch, sum(lossAver) / (len(lossAver)), time() - start))
ZeroDivisionError: division by zero`.

2. The other is RuntimeError: adaptive_max_pool2d(): Expected input to have non-zero size for non-batch dimensions, but input has sizes [1, 64, 0, 0] with dimension 2 being empty.The two dimensions are zero and I don't know how to solve it!

The whole error is

Traceback (most recent call last):
File "D:\project\python2\CCPD-master\rpnet\rpnet.py", line 422, in
model_conv = train_model(model_conv, criterion, optimizer_conv, num_epochs=epochs)
File "D:\project\python2\CCPD-master\rpnet\rpnet.py", line 414, in train_model
count, correct, error, precision, avgTime = eval(model, testDirs)
File "D:\project\python2\CCPD-master\rpnet\rpnet.py", line 334, in eval
fps_pred, y_pred = model(x)
File "E:\app\anaconda3\envs\pytorch1\lib\site-packages\torch\nn\modules\module.py", line 1130, in _call_impl
return forward_call(*input, **kwargs)
File "E:\app\anaconda3\envs\pytorch1\lib\site-packages\torch\nn\parallel\data_parallel.py", line 166, in forward
return self.module(*inputs[0], **kwargs[0])
File "E:\app\anaconda3\envs\pytorch1\lib\site-packages\torch\nn\modules\module.py", line 1130, in _call_impl
return forward_call(*input, **kwargs)
File "D:\project\python2\CCPD-master\rpnet\rpnet.py", line 267, in forward
roi1 = roi_pooling_ims(_x1, boxNew.mm(p1), size=(16, 8))
File "D:\project\python2\CCPD-master\rpnet\roi_pooling.py", line 74, in roi_pooling_ims
output.append(F.adaptive_max_pool2d(im, size))
File "E:\app\anaconda3\envs\pytorch1\lib\site-packages\torch_jit_internal.py", line 423, in fn
return if_false(*args, **kwargs)
File "E:\app\anaconda3\envs\pytorch1\lib\site-packages\torch\nn\functional.py", line 1129, in _adaptive_max_pool2d
return adaptive_max_pool2d_with_indices(input, output_size)[0]
File "E:\app\anaconda3\envs\pytorch1\lib\site-packages\torch\nn\functional.py", line 1121, in adaptive_max_pool2d_with_indices
return torch._C._nn.adaptive_max_pool2d(input, output_size)
RuntimeError: adaptive_max_pool2d(): Expected input to have non-zero size for non-batch dimensions, but input has sizes [1, 64, 0, 0] with dimension 2 being empty

@detectRecog @shizhenbo