Bug in fast.ai transform.py

[irshadqemu]

transforms_pt = [RandomRotateZoom(9, 0.18, 0.1), RandomLighting(0.05, 0.1), RandomDihedral()]
tfms=tfms_from_model(f_model, sz, aug_tfms=transforms_pt, pad=sz//12)

val_idx = get_cv_idxs(train_len)
data = ImageClassifierData.from_csv(path, 'train-jpg', f'{path}train_v2.csv', bs, tfms, suffix='.jpg', val_idxs=val_idx, test_name='test-jpg')
lr=0.2
lrs=[lr/9, lr/3, lr]
learn = ConvLearner.pretrained(f_model, data, metrics=metrics)
        
learn.fit(lr, 3, cycle_len=1, cycle_mult=2)

Error: 
  0%|          | 0/506 [00:00<?, ?it/s]
---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-28-a0d195fa61d1> in <module>()
     11 learn = ConvLearner.pretrained(f_model, data, metrics=metrics)
     12 
---> 13 learn.fit(lr, 3, cycle_len=1, cycle_mult=2)

~/fastai/courses/dl1/fastai/learner.py in fit(self, lrs, n_cycle, wds, **kwargs)
    211         self.sched = None
    212         layer_opt = self.get_layer_opt(lrs, wds)
--> 213         self.fit_gen(self.model, self.data, layer_opt, n_cycle, **kwargs)
    214 
    215     def warm_up(self, start_lr=1e-5, end_lr=10, 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, metrics, callbacks, use_wd_sched, norm_wds, wds_sched_mult, **kwargs)
    158         n_epoch = sum_geom(cycle_len if cycle_len else 1, cycle_mult, n_cycle)
    159         fit(model, data, n_epoch, layer_opt.opt, self.crit,
--> 160             metrics=metrics, callbacks=callbacks, reg_fn=self.reg_fn, clip=self.clip, **kwargs)
    161 
    162     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, **kwargs)
     84         stepper.reset(True)
     85         t = tqdm(iter(data.trn_dl), leave=False, total=len(data.trn_dl))
---> 86         for (*x,y) in t:
     87             batch_num += 1
     88             for cb in callbacks: cb.on_batch_begin()

~/anaconda3/envs/fastai/lib/python3.6/site-packages/tqdm/_tqdm.py in __iter__(self)
    951 """, fp_write=getattr(self.fp, 'write', sys.stderr.write))
    952 
--> 953             for obj in iterable:
    954                 yield obj
    955                 # Update and possibly print the progressbar.

~/fastai/courses/dl1/fastai/dataset.py in __next__(self)
    241         if self.i>=len(self.dl): raise StopIteration
    242         self.i+=1
--> 243         return next(self.it)
    244 
    245     @property

~/fastai/courses/dl1/fastai/dataloader.py in __iter__(self)
     73     def __iter__(self):
     74         with ThreadPoolExecutor(max_workers=self.num_workers) as e:
---> 75             for batch in e.map(self.get_batch, iter(self.batch_sampler)):
     76                 yield get_tensor(batch, self.pin_memory)
     77 

~/anaconda3/envs/fastai/lib/python3.6/concurrent/futures/_base.py in result_iterator()
    584                     # Careful not to keep a reference to the popped future
    585                     if timeout is None:
--> 586                         yield fs.pop().result()
    587                     else:
    588                         yield fs.pop().result(end_time - time.time())

~/anaconda3/envs/fastai/lib/python3.6/concurrent/futures/_base.py in result(self, timeout)
    423                 raise CancelledError()
    424             elif self._state == FINISHED:
--> 425                 return self.__get_result()
    426 
    427             self._condition.wait(timeout)

~/anaconda3/envs/fastai/lib/python3.6/concurrent/futures/_base.py in __get_result(self)
    382     def __get_result(self):
    383         if self._exception:
--> 384             raise self._exception
    385         else:
    386             return self._result

~/anaconda3/envs/fastai/lib/python3.6/concurrent/futures/thread.py in run(self)
     54 
     55         try:
---> 56             result = self.fn(*self.args, **self.kwargs)
     57         except BaseException as exc:
     58             self.future.set_exception(exc)

~/fastai/courses/dl1/fastai/dataloader.py in get_batch(self, indices)
     66 
     67     def get_batch(self, indices):
---> 68         res = self.collate_fn([self.dataset[i] for i in indices], self.pad_idx)
     69         if not self.transpose: return res
     70         res[0] = res[0].T

~/fastai/courses/dl1/fastai/dataloader.py in <listcomp>(.0)
     66 
     67     def get_batch(self, indices):
---> 68         res = self.collate_fn([self.dataset[i] for i in indices], self.pad_idx)
     69         if not self.transpose: return res
     70         res[0] = res[0].T

~/fastai/courses/dl1/fastai/dataset.py in __getitem__(self, idx)
     95     def __getitem__(self, idx):
     96         x,y = self.get_x(idx),self.get_y(idx)
---> 97         return self.get(self.transform, x, y)
     98 
     99     def __len__(self): return self.n

~/fastai/courses/dl1/fastai/dataset.py in get(self, tfm, x, y)
    100 
    101     def get(self, tfm, x, y):
--> 102         return (x,y) if tfm is None else tfm(x,y)
    103 
    104     @abstractmethod

~/fastai/courses/dl1/fastai/transforms.py in __call__(self, im, y)
    463         if crop_type == CropType.NO: crop_tfm = NoCropXY(sz, tfm_y)
    464         self.tfms = tfms + [crop_tfm, normalizer, channel_dim]
--> 465     def __call__(self, im, y=None): return compose(im, y, self.tfms)
    466 
    467 

~/fastai/courses/dl1/fastai/transforms.py in compose(im, y, fns)
    444 def compose(im, y, fns):
    445     for fn in fns:
--> 446         im, y =fn(im, y)
    447     return im if y is None else (im, y)
    448 

~/fastai/courses/dl1/fastai/transforms.py in __call__(self, x, y)
    134         if choice==0: pass
    135         elif choice==1: x = rotate_cv(x, rand0(self.deg), self.mode)
--> 136         elif choice==2: x = zoom_cv(x, random.random()*self.zoom)
    137         elif choice==3:
    138             str_choice = random.randint(0,1)

~/fastai/courses/dl1/fastai/transforms.py in zoom_cv(x, z)
     17 def zoom_cv(x,z):
     18     if z==0: return x
---> 19     r,c,*_ = im.shape
     20     M = cv2.getRotationMatrix2D((c/2,r/2),0,z+1.)
     21     return cv2.warpAffine(x,M,(c,r))

NameError: name 'im' is not defined

[yanneta]

Can you check if using RandomDihedralXY instead of RandomDihedral solves your problem? We have to fix RandomDihedral.

…

On Wed, Jan 10, 2018 at 1:00 PM, Irshad Muhammad ***@***.***> wrote: transforms_pt = [RandomRotateZoom(9, 0.18, 0.1), RandomLighting(0.05, 0.1), RandomDihedral()] tfms=tfms_from_model(f_model, sz, aug_tfms=transforms_pt, pad=sz//12) val_idx = get_cv_idxs(train_len) data = ImageClassifierData.from_csv(path, 'train-jpg', f'{path}train_v2.csv', bs, tfms, suffix='.jpg', val_idxs=val_idx, test_name='test-jpg') lr=0.2 lrs=[lr/9, lr/3, lr] learn = ConvLearner.pretrained(f_model, data, metrics=metrics) learn.fit(lr, 3, cycle_len=1, cycle_mult=2) Error: 0%| | 0/506 [00:00<?, ?it/s] --------------------------------------------------------------------------- NameError Traceback (most recent call last) <ipython-input-28-a0d195fa61d1> in <module>() 11 learn = ConvLearner.pretrained(f_model, data, metrics=metrics) 12 ---> 13 learn.fit(lr, 3, cycle_len=1, cycle_mult=2) ~/fastai/courses/dl1/fastai/learner.py in fit(self, lrs, n_cycle, wds, **kwargs) 211 self.sched = None 212 layer_opt = self.get_layer_opt(lrs, wds) --> 213 self.fit_gen(self.model, self.data, layer_opt, n_cycle, **kwargs) 214 215 def warm_up(self, start_lr=1e-5, end_lr=10, 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, metrics, callbacks, use_wd_sched, norm_wds, wds_sched_mult, **kwargs) 158 n_epoch = sum_geom(cycle_len if cycle_len else 1, cycle_mult, n_cycle) 159 fit(model, data, n_epoch, layer_opt.opt, self.crit, --> 160 metrics=metrics, callbacks=callbacks, reg_fn=self.reg_fn, clip=self.clip, **kwargs) 161 162 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, **kwargs) 84 stepper.reset(True) 85 t = tqdm(iter(data.trn_dl), leave=False, total=len(data.trn_dl)) ---> 86 for (*x,y) in t: 87 batch_num += 1 88 for cb in callbacks: cb.on_batch_begin() ~/anaconda3/envs/fastai/lib/python3.6/site-packages/tqdm/_tqdm.py in __iter__(self) 951 """, fp_write=getattr(self.fp, 'write', sys.stderr.write)) 952 --> 953 for obj in iterable: 954 yield obj 955 # Update and possibly print the progressbar. ~/fastai/courses/dl1/fastai/dataset.py in __next__(self) 241 if self.i>=len(self.dl): raise StopIteration 242 self.i+=1 --> 243 return next(self.it) 244 245 @Property ~/fastai/courses/dl1/fastai/dataloader.py in __iter__(self) 73 def __iter__(self): 74 with ThreadPoolExecutor(max_workers=self.num_workers) as e: ---> 75 for batch in e.map(self.get_batch, iter(self.batch_sampler)): 76 yield get_tensor(batch, self.pin_memory) 77 ~/anaconda3/envs/fastai/lib/python3.6/concurrent/futures/_base.py in result_iterator() 584 # Careful not to keep a reference to the popped future 585 if timeout is None: --> 586 yield fs.pop().result() 587 else: 588 yield fs.pop().result(end_time - time.time()) ~/anaconda3/envs/fastai/lib/python3.6/concurrent/futures/_base.py in result(self, timeout) 423 raise CancelledError() 424 elif self._state == FINISHED: --> 425 return self.__get_result() 426 427 self._condition.wait(timeout) ~/anaconda3/envs/fastai/lib/python3.6/concurrent/futures/_base.py in __get_result(self) 382 def __get_result(self): 383 if self._exception: --> 384 raise self._exception 385 else: 386 return self._result ~/anaconda3/envs/fastai/lib/python3.6/concurrent/futures/thread.py in run(self) 54 55 try: ---> 56 result = self.fn(*self.args, **self.kwargs) 57 except BaseException as exc: 58 self.future.set_exception(exc) ~/fastai/courses/dl1/fastai/dataloader.py in get_batch(self, indices) 66 67 def get_batch(self, indices): ---> 68 res = self.collate_fn([self.dataset[i] for i in indices], self.pad_idx) 69 if not self.transpose: return res 70 res[0] = res[0].T ~/fastai/courses/dl1/fastai/dataloader.py in <listcomp>(.0) 66 67 def get_batch(self, indices): ---> 68 res = self.collate_fn([self.dataset[i] for i in indices], self.pad_idx) 69 if not self.transpose: return res 70 res[0] = res[0].T ~/fastai/courses/dl1/fastai/dataset.py in __getitem__(self, idx) 95 def __getitem__(self, idx): 96 x,y = self.get_x(idx),self.get_y(idx) ---> 97 return self.get(self.transform, x, y) 98 99 def __len__(self): return self.n ~/fastai/courses/dl1/fastai/dataset.py in get(self, tfm, x, y) 100 101 def get(self, tfm, x, y): --> 102 return (x,y) if tfm is None else tfm(x,y) 103 104 @AbstractMethod ~/fastai/courses/dl1/fastai/transforms.py in __call__(self, im, y) 463 if crop_type == CropType.NO: crop_tfm = NoCropXY(sz, tfm_y) 464 self.tfms = tfms + [crop_tfm, normalizer, channel_dim] --> 465 def __call__(self, im, y=None): return compose(im, y, self.tfms) 466 467 ~/fastai/courses/dl1/fastai/transforms.py in compose(im, y, fns) 444 def compose(im, y, fns): 445 for fn in fns: --> 446 im, y =fn(im, y) 447 return im if y is None else (im, y) 448 ~/fastai/courses/dl1/fastai/transforms.py in __call__(self, x, y) 134 if choice==0: pass 135 elif choice==1: x = rotate_cv(x, rand0(self.deg), self.mode) --> 136 elif choice==2: x = zoom_cv(x, random.random()*self.zoom) 137 elif choice==3: 138 str_choice = random.randint(0,1) ~/fastai/courses/dl1/fastai/transforms.py in zoom_cv(x, z) 17 def zoom_cv(x,z): 18 if z==0: return x ---> 19 r,c,*_ = im.shape 20 M = cv2.getRotationMatrix2D((c/2,r/2),0,z+1.) 21 return cv2.warpAffine(x,M,(c,r)) NameError: name 'im' is not defined — You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub <#87>, or mute the thread <https://github.com/notifications/unsubscribe-auth/AC3CZbeGESdpvGH2wvp9lDJZdGnPjDZFks5tJST7gaJpZM4RZ8Ad> .

[jph00]

@yanneta is this solved?

[yanneta]

It should be solved now.

…

On Mon, Jan 22, 2018 at 3:55 PM, Jeremy Howard ***@***.***> wrote: @yanneta <https://github.com/yanneta> is this solved? — You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub <#87 (comment)>, or mute the thread <https://github.com/notifications/unsubscribe-auth/AC3CZfmzdDvTT0n3Hbh7lXufZ9chuw_Gks5tNR_igaJpZM4RZ8Ad> .