Lesson3-planet fit_one_cycle error end of training

#1

After running the fit_one_cycle, I get the following error:

RuntimeError                              Traceback (most recent call last)
<ipython-input-21-be1ab4476b35> in <module>
----> 1 learn.fit_one_cycle(5, slice(lr))

~/anaconda3/envs/nfastai/lib/python3.6/site-packages/fastai/train.py in fit_one_cycle(learn, cyc_len, max_lr, moms, div_factor, pct_start, wd, callbacks, **kwargs)
     19     callbacks.append(OneCycleScheduler(learn, max_lr, moms=moms, div_factor=div_factor,
     20                                         pct_start=pct_start, **kwargs))
---> 21     learn.fit(cyc_len, max_lr, wd=wd, callbacks=callbacks)
     22 
     23 def lr_find(learn:Learner, start_lr:Floats=1e-7, end_lr:Floats=10, num_it:int=100, stop_div:bool=True, **kwargs:Any):

~/anaconda3/envs/nfastai/lib/python3.6/site-packages/fastai/basic_train.py in fit(self, epochs, lr, wd, callbacks)
    164         callbacks = [cb(self) for cb in self.callback_fns] + listify(callbacks)
    165         fit(epochs, self.model, self.loss_func, opt=self.opt, data=self.data, metrics=self.metrics,
--> 166             callbacks=self.callbacks+callbacks)
    167 
    168     def create_opt(self, lr:Floats, wd:Floats=0.)->None:

~/anaconda3/envs/nfastai/lib/python3.6/site-packages/fastai/basic_train.py in fit(epochs, model, loss_func, opt, data, callbacks, metrics)
     92     except Exception as e:
     93         exception = e
---> 94         raise e
     95     finally: cb_handler.on_train_end(exception)
     96 

~/anaconda3/envs/nfastai/lib/python3.6/site-packages/fastai/basic_train.py in fit(epochs, model, loss_func, opt, data, callbacks, metrics)
     87             if hasattr(data,'valid_dl') and data.valid_dl is not None and data.valid_ds is not None:
     88                 val_loss = validate(model, data.valid_dl, loss_func=loss_func,
---> 89                                        cb_handler=cb_handler, pbar=pbar)
     90             else: val_loss=None
     91             if cb_handler.on_epoch_end(val_loss): break

~/anaconda3/envs/nfastai/lib/python3.6/site-packages/fastai/basic_train.py in validate(model, dl, loss_func, cb_handler, pbar, average, n_batch)
     52             if not is_listy(yb): yb = [yb]
     53             nums.append(yb[0].shape[0])
---> 54             if cb_handler and cb_handler.on_batch_end(val_losses[-1]): break
     55             if n_batch and (len(nums)>=n_batch): break
     56         nums = np.array(nums, dtype=np.float32)

~/anaconda3/envs/nfastai/lib/python3.6/site-packages/fastai/callback.py in on_batch_end(self, loss)
    237         "Handle end of processing one batch with `loss`."
    238         self.state_dict['last_loss'] = loss
--> 239         stop = np.any(self('batch_end', not self.state_dict['train']))
    240         if self.state_dict['train']:
    241             self.state_dict['iteration'] += 1

~/anaconda3/envs/nfastai/lib/python3.6/site-packages/fastai/callback.py in __call__(self, cb_name, call_mets, **kwargs)
    185     def __call__(self, cb_name, call_mets=True, **kwargs)->None:
    186         "Call through to all of the `CallbakHandler` functions."
--> 187         if call_mets: [getattr(met, f'on_{cb_name}')(**self.state_dict, **kwargs) for met in self.metrics]
    188         return [getattr(cb, f'on_{cb_name}')(**self.state_dict, **kwargs) for cb in self.callbacks]
    189 

~/anaconda3/envs/nfastai/lib/python3.6/site-packages/fastai/callback.py in <listcomp>(.0)
    185     def __call__(self, cb_name, call_mets=True, **kwargs)->None:
    186         "Call through to all of the `CallbakHandler` functions."
--> 187         if call_mets: [getattr(met, f'on_{cb_name}')(**self.state_dict, **kwargs) for met in self.metrics]
    188         return [getattr(cb, f'on_{cb_name}')(**self.state_dict, **kwargs) for cb in self.callbacks]
    189 

~/anaconda3/envs/nfastai/lib/python3.6/site-packages/fastai/callback.py in on_batch_end(self, last_output, last_target, **kwargs)
    272         if not is_listy(last_target): last_target=[last_target]
    273         self.count += last_target[0].size(0)
--> 274         self.val += last_target[0].size(0) * self.func(last_output, *last_target).detach().cpu()
    275 
    276     def on_epoch_end(self, **kwargs):

~/anaconda3/envs/nfastai/lib/python3.6/site-packages/fastai/metrics.py in accuracy_thresh(y_pred, y_true, thresh, sigmoid)
     20     "Compute accuracy when `y_pred` and `y_true` are the same size."
     21     if sigmoid: y_pred = y_pred.sigmoid()
---> 22     return ((y_pred>thresh)==y_true.byte()).float().mean()
     23 
     24 def dice(input:FloatTensor, targs:LongTensor, iou:bool=False)->Rank0Tensor:

RuntimeError: The size of tensor a (418) must match the size of tensor b (8) at non-singleton dimension 1

Someone said it might be related to accuracy_thresh but I can’t figure out how to change it.

Here is my show_install():

=== Software === 
python version  : 3.6.7
fastai version  : 1.0.36
torch version   : 1.0.1
nvidia driver   : 390.116
torch cuda ver  : 9.0.176
torch cuda is   : available
torch cudnn ver : 7301
torch cudnn is  : enabled

=== Hardware === 
nvidia gpus     : 2
torch available : 2
  - gpu0        : 8119MB | GeForce GTX 1080
  - gpu1        : 8119MB | GeForce GTX 1080

=== Environment === 
platform        : Linux-4.15.0-48-generic-x86_64-with-debian-buster-sid
distro          : #51-Ubuntu SMP Wed Apr 3 08:28:49 UTC 2019
conda env       : Unknown
python          : /home/jgmeyer2/anaconda3/envs/nfastai/bin/python
sys.path        : /home/jgmeyer2/anaconda3/envs/nfastai/lib/python36.zip
/home/jgmeyer2/anaconda3/envs/nfastai/lib/python3.6
/home/jgmeyer2/anaconda3/envs/nfastai/lib/python3.6/lib-dynload

/home/jgmeyer2/.local/lib/python3.6/site-packages
/home/jgmeyer2/anaconda3/envs/nfastai/lib/python3.6/site-packages
/home/jgmeyer2/anaconda3/envs/nfastai/lib/python3.6/site-packages/IPython/extensions
/home/jgmeyer2/.ipython
1 Like

(Andreas Daiminger) #2

Hi @jgmeyer!

The two tensor sizes that do not match correspond to the batch_size and number of classes. Seems accuracy_thresh does not work here. Try to remove accuracy_thresh from metrics.

I hope accuracy_thresh gets fixed in the near future!

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