numpy LongTensor

gistfile1.txt

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-11-2832d24508dc> in <module>()
      1 lr = 5e-3
----> 2 learn.fit(lr, 3, cycle_len=1)

~/fastai/courses/dl1/fastai/learner.py in fit(self, lrs, n_cycle, wds, **kwargs)
    212         self.sched = None
    213         layer_opt = self.get_layer_opt(lrs, wds)
--> 214         return self.fit_gen(self.model, self.data, layer_opt, n_cycle, **kwargs)
    215 
    216     def warm_up(self, lr, wds=None):

~/fastai/courses/dl1/fastai/learner.py in fit_gen(self, model, data, layer_opt, n_cycle, cycle_len, cycle_mult, cycle_save_name, best_save_name, use_clr, metrics, callbacks, use_wd_sched, norm_wds, wds_sched_mult, **kwargs)
    159         n_epoch = sum_geom(cycle_len if cycle_len else 1, cycle_mult, n_cycle)
    160         return fit(model, data, n_epoch, layer_opt.opt, self.crit,
--> 161             metrics=metrics, callbacks=callbacks, reg_fn=self.reg_fn, clip=self.clip, **kwargs)
    162 
    163     def get_layer_groups(self): return self.models.get_layer_groups()

~/fastai/courses/dl1/fastai/model.py in fit(model, data, epochs, opt, crit, metrics, callbacks, stepper, **kwargs)
    104             i += 1
    105 
--> 106         vals = validate(stepper, data.val_dl, metrics)
    107         if epoch == 0: print(layout.format(*names))
    108         print_stats(epoch, [debias_loss] + vals)

~/fastai/courses/dl1/fastai/model.py in validate(stepper, dl, metrics)
    126         preds,l = stepper.evaluate(VV(x), VV(y))
    127         loss.append(to_np(l))
--> 128         res.append([f(preds.data,y) for f in metrics])
    129     return [np.mean(loss)] + list(np.mean(np.stack(res),0))
    130 

~/fastai/courses/dl1/fastai/model.py in <listcomp>(.0)
    126         preds,l = stepper.evaluate(VV(x), VV(y))
    127         loss.append(to_np(l))
--> 128         res.append([f(preds.data,y) for f in metrics])
    129     return [np.mean(loss)] + list(np.mean(np.stack(res),0))
    130 

~/fastai/courses/dl1/fastai/metrics.py in accuracy(preds, targs)
      8 def accuracy(preds, targs):
      9     preds = torch.max(preds, dim=1)[1]
---> 10     return (preds==targs).float().mean()
     11 
     12 def accuracy_thresh(thresh):

~/anaconda3/envs/fastai/lib/python3.6/site-packages/torch/tensor.py in __eq__(self, other)
    358 
    359     def __eq__(self, other):
--> 360         return self.eq(other)
    361 
    362     def __ne__(self, other):

TypeError: eq received an invalid combination of arguments - got (numpy.ndarray), but expected one of:
 * (int value)
      didn't match because some of the arguments have invalid types: (numpy.ndarray)
 * (torch.cuda.LongTensor other)
      didn't match because some of the arguments have invalid types: (numpy.ndarray)