You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
~\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
The text was updated successfully, but these errors were encountered:
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
The text was updated successfully, but these errors were encountered: