04_mnist_basics: RuntimeError encountered after running learn.fit_one_cycle

[naity]

dls = ImageDataLoaders.from_folder(path, num_workers=0)
learn = cnn_learner(dls, resnet18, pretrained=False,
                    loss_func=F.cross_entropy, metrics=accuracy)
learn.fit_one_cycle(1, 0.1)

---

RuntimeError Traceback (most recent call last)
in
2 learn = cnn_learner(dls, resnet18, pretrained=False,
3 loss_func=F.cross_entropy, metrics=accuracy)
----> 4 learn.fit_one_cycle(1, 0.1)

~\anaconda3\envs\fastai2\lib\site-packages\fastcore\utils.py in _f(*args, **kwargs)
429 init_args.update(log)
430 setattr(inst, 'init_args', init_args)
--> 431 return inst if to_return else f(*args, **kwargs)
432 return _f
433

~\anaconda3\envs\fastai2\lib\site-packages\fastai2\callback\schedule.py in fit_one_cycle(self, n_epoch, lr_max, div, div_final, pct_start, wd, moms, cbs, reset_opt)
111 scheds = {'lr': combined_cos(pct_start, lr_max/div, lr_max, lr_max/div_final),
112 'mom': combined_cos(pct_start, *(self.moms if moms is None else moms))}
--> 113 self.fit(n_epoch, cbs=ParamScheduler(scheds)+L(cbs), reset_opt=reset_opt, wd=wd)
114
115 # Cell

~\anaconda3\envs\fastai2\lib\site-packages\fastcore\utils.py in _f(*args, **kwargs)
429 init_args.update(log)
430 setattr(inst, 'init_args', init_args)
--> 431 return inst if to_return else f(*args, **kwargs)
432 return _f
433

~\anaconda3\envs\fastai2\lib\site-packages\fastai2\learner.py in fit(self, n_epoch, lr, wd, cbs, reset_opt)
201 try:
202 self.epoch=epoch; self('begin_epoch')
--> 203 self._do_epoch_train()
204 self._do_epoch_validate()
205 except CancelEpochException: self('after_cancel_epoch')

~\anaconda3\envs\fastai2\lib\site-packages\fastai2\learner.py in _do_epoch_train(self)
173 try:
174 self.dl = self.dls.train; self('begin_train')
--> 175 self.all_batches()
176 except CancelTrainException: self('after_cancel_train')
177 finally: self('after_train')

~\anaconda3\envs\fastai2\lib\site-packages\fastai2\learner.py in all_batches(self)
151 def all_batches(self):
152 self.n_iter = len(self.dl)
--> 153 for o in enumerate(self.dl): self.one_batch(*o)
154
155 def one_batch(self, i, b):

~\anaconda3\envs\fastai2\lib\site-packages\fastai2\learner.py in one_batch(self, i, b)
159 self.pred = self.model(*self.xb); self('after_pred')
160 if len(self.yb) == 0: return
--> 161 self.loss = self.loss_func(self.pred, *self.yb); self('after_loss')
162 if not self.training: return
163 self.loss.backward(); self('after_backward')

~\anaconda3\envs\fastai2\lib\site-packages\torch\nn\functional.py in cross_entropy(input, target, weight, size_average, ignore_index, reduce, reduction)
2420 if size_average is not None or reduce is not None:
2421 reduction = _Reduction.legacy_get_string(size_average, reduce)
-> 2422 return nll_loss(log_softmax(input, 1), target, weight, None, ignore_index, None, reduction)
2423
2424

~\anaconda3\envs\fastai2\lib\site-packages\torch\nn\functional.py in nll_loss(input, target, weight, size_average, ignore_index, reduce, reduction)
2216 .format(input.size(0), target.size(0)))
2217 if dim == 2:
-> 2218 ret = torch._C._nn.nll_loss(input, target, weight, _Reduction.get_enum(reduction), ignore_index)
2219 elif dim == 4:
2220 ret = torch._C._nn.nll_loss2d(input, target, weight, _Reduction.get_enum(reduction), ignore_index)

RuntimeError: Expected object of scalar type Long but got scalar type Int for argument #2 'target' in call to _thnn_nll_loss_forward

[jph00]

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