Hello, I’m sure this is a simple issue, but I’ve been having a lot of difficulty and would love some help. I’m loading a learner with Load_Learner and then attempting to add a test set to train it. Here is what I have.
CNN = load_learner(path, ‘ReallyGood.pkl’)
bs = 64
data = ImageDataBunch.from_df(‘Data/’, pdlabels, folder=‘train_images’, test=‘MyTest’, ds_tfms=get_transforms(), size=224, bs=bs).normalize(imagenet_stats)
CNN.predict(data, is_test=True)
This has been giving me the error:
AttributeError Traceback (most recent call last)
in
----> 1 CNN.predict(data, is_test=True)
~/anaconda3/lib/python3.7/site-packages/fastai/basic_train.py in predict(self, item, **kwargs)
357 def predict(self, item:ItemBase, **kwargs):
358 “Return predicted class, label and probabilities for item.”
–> 359 batch = self.data.one_item(item)
360 res = self.pred_batch(batch=batch)
361 pred,x = res[0],batch[0]
~/anaconda3/lib/python3.7/site-packages/fastai/basic_data.py in one_item(self, item, detach, denorm, cpu)
179 ds = self.single_ds
180 with ds.set_item(item):
–> 181 return self.one_batch(ds_type=DatasetType.Single, detach=detach, denorm=denorm, cpu=cpu)
182
183 def show_batch(self, rows:int=5, ds_type:DatasetType=DatasetType.Train, reverse:bool=False, **kwargs)->None:
~/anaconda3/lib/python3.7/site-packages/fastai/basic_data.py in one_batch(self, ds_type, detach, denorm, cpu)
166 w = self.num_workers
167 self.num_workers = 0
–> 168 try: x,y = next(iter(dl))
169 finally: self.num_workers = w
170 if detach: x,y = to_detach(x,cpu=cpu),to_detach(y,cpu=cpu)
~/anaconda3/lib/python3.7/site-packages/fastai/basic_data.py in iter(self)
73 def iter(self):
74 “Process and returns items from DataLoader.”
—> 75 for b in self.dl: yield self.proc_batch(b)
76
77 @classmethod
~/anaconda3/lib/python3.7/site-packages/torch/utils/data/dataloader.py in next(self)
613 if self.num_workers == 0: # same-process loading
614 indices = next(self.sample_iter) # may raise StopIteration
–> 615 batch = self.collate_fn([self.dataset[i] for i in indices])
616 if self.pin_memory:
617 batch = pin_memory_batch(batch)
~/anaconda3/lib/python3.7/site-packages/torch/utils/data/dataloader.py in (.0)
613 if self.num_workers == 0: # same-process loading
614 indices = next(self.sample_iter) # may raise StopIteration
–> 615 batch = self.collate_fn([self.dataset[i] for i in indices])
616 if self.pin_memory:
617 batch = pin_memory_batch(batch)
~/anaconda3/lib/python3.7/site-packages/fastai/data_block.py in getitem(self, idxs)
631 else: x,y = self.item ,0
632 if self.tfms or self.tfmargs:
–> 633 x = x.apply_tfms(self.tfms, **self.tfmargs)
634 if hasattr(self, ‘tfms_y’) and self.tfm_y and self.item is None:
635 y = y.apply_tfms(self.tfms_y, **{**self.tfmargs_y, ‘do_resolve’:False})
~/anaconda3/lib/python3.7/site-packages/fastai/basic_data.py in getattr(self, k)
120 return cls(*dls, path=path, device=device, dl_tfms=dl_tfms, collate_fn=collate_fn, no_check=no_check)
121
–> 122 def getattr(self,k:int)->Any: return getattr(self.train_dl, k)
123 def setstate(self,data:Any): self.dict.update(data)
124
~/anaconda3/lib/python3.7/site-packages/fastai/basic_data.py in getattr(self, k)
36
37 def len(self)->int: return len(self.dl)
—> 38 def getattr(self,k:str)->Any: return getattr(self.dl, k)
39 def setstate(self,data:Any): self.dict.update(data)
40
~/anaconda3/lib/python3.7/site-packages/fastai/basic_data.py in DataLoader___getattr__(dl, k)
18 torch.utils.data.DataLoader.init = intercept_args
19
—> 20 def DataLoader___getattr__(dl, k:str)->Any: return getattr(dl.dataset, k)
21 DataLoader.getattr = DataLoader___getattr__
22
~/anaconda3/lib/python3.7/site-packages/fastai/data_block.py in getattr(self, k)
621 res = getattr(y, k, None)
622 if res is not None: return res
–> 623 raise AttributeError(k)
624
625 def setstate(self,data:Any): self.dict.update(data)
AttributeError: apply_tfms
=============================================================
I also would like to try using CNN.pred_batch and CNN.get_preds but I’m not sure how to load the test data into the re-loaded model.