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Description
Hi,
Thank you for your project. It's helpful. I'm tried to launch your train.py script on a new dataset and i have encounter the following error
File "src/train.py", line 60, in
metric_list=metric_list, verbose=True)
File "/workspace/src/unet/model.py", line 186, in fit_dataset
train_logs = self.fit_epoch(dataset, n_batch=n_batch, shuffle=shuffle)
File "/workspace/src/unet/model.py", line 99, in fit_epoch
training_loss = self.loss(y_out, y_batch)
File "/usr/local/lib/python3.6/site-packages/torch/nn/modules/module.py", line 493, in call
result = self.forward(*input, **kwargs)
File "/workspace/src/unet/metrics.py", line 25, in forward
ignore_index=self.ignore_index)
File "/usr/local/lib/python3.6/site-packages/torch/nn/functional.py", line 2056, in cross_entropy
return nll_loss(log_softmax(input, 1), target, weight, None, ignore_index, None, reduction)
File "/usr/local/lib/python3.6/site-packages/torch/nn/functional.py", line 1873, in nll_loss
ret = torch._C._nn.nll_loss2d(input, target, weight, _Reduction.get_enum(reduction), ignore_index)
RuntimeError: Assertion `cur_target >= 0 && cur_target < n_classes' failed. at /pytorch/aten/src/THNN/generic/SpatialClassNLLCriterion.c:109
As i search in the internet for the cause, i find that maybe it's the dimensions of the output layer. The problem is thta i did not change anything and i used a similar dataset
Thank you for your help