Hello,
I am learning fastai for medical research and I am an absolute beginner using Kaggle. I cut and paste the code for lesson 1 homework “Is it a bird?”.
Everything was working fine until I implemented the following code:
is_bird,_,probs = learn.predict(PILImage.create(‘bird.jpg’))
print(f"This is a: {is_bird}.“)
print(f"Probability it’s a bird: {probs[0]:.4f}”)
And I got the message below.
Please help
Time
Log Message
27.6s 1 Searching for ‘bird photos’
35.3s 2 Searching for ‘forest photos’
36.7s 3 Searching for ‘forest photo’
104.2s 4 Searching for ‘forest sun photo’
119.8s 5 Searching for ‘forest shade photo’
144.3s 6 Searching for ‘bird photo’
157.9s 7 Searching for ‘bird sun photo’
174.9s 8 Searching for ‘bird shade photo’
197.2s 9 /opt/conda/lib/python3.7/site-packages/torchvision/models/utils.py:209: UserWarning: The parameter ‘pretrained’ is deprecated since 0.13 and may be removed in the future, please use ‘weights’ instead.
197.2s 10 f"The parameter ‘{pretrained_param}’ is deprecated since 0.13 and may be removed in the future, "
197.2s 11 /opt/conda/lib/python3.7/site-packages/torchvision/models/utils.py:223: UserWarning: Arguments other than a weight enum or None for ‘weights’ are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing weights=ResNet18_Weights.IMAGENET1K_V1. You can also use weights=ResNet18_Weights.DEFAULT to get the most up-to-date weights.
197.2s 12 warnings.warn(msg)
197.4s 13 Downloading: “https://download.pytorch.org/models/resnet18-f37072fd.pth” to /root/.cache/torch/hub/checkpoints/resnet18-f37072fd.pth
270.5s 14 Traceback (most recent call last):
270.5s 15 File “”, line 1, in
270.5s 16 File “/opt/conda/lib/python3.7/site-packages/papermill/execute.py”, line 128, in execute_notebook
270.5s 17 raise_for_execution_errors(nb, output_path)
270.5s 18 File “/opt/conda/lib/python3.7/site-packages/papermill/execute.py”, line 232, in raise_for_execution_errors
270.5s 19 raise error
270.5s 20 papermill.exceptions.PapermillExecutionError:
270.5s 21 ---------------------------------------------------------------------------
270.5s 22 Exception encountered at “In [12]”:
270.5s 23 ---------------------------------------------------------------------------
270.5s 24 AttributeError Traceback (most recent call last)
270.5s 25 /tmp/ipykernel_19/1213330699.py in
270.5s 26 ----> 1 is_bird,,probs = learn.predict(PILImage.create(‘bird.jpg’))
270.5s 27 2 print(f"This is a: {is_bird}.“)
270.5s 28 3 print(f"Probability it’s a bird: {probs[0]:.4f}”)
270.5s 29
270.5s 30 /opt/conda/lib/python3.7/site-packages/fastai/learner.py in predict(self, item, rm_type_tfms, with_input)
270.5s 31 319 def predict(self, item, rm_type_tfms=None, with_input=False):
270.5s 32 320 dl = self.dls.test_dl([item], rm_type_tfms=rm_type_tfms, num_workers=0)
270.5s 33 → 321 inp,preds,,dec_preds = self.get_preds(dl=dl, with_input=True, with_decoded=True)
270.5s 34 322 i = getattr(self.dls, ‘n_inp’, -1)
270.5s 35 323 inp = (inp,) if i==1 else tuplify(inp)
270.5s 36
270.5s 37 /opt/conda/lib/python3.7/site-packages/fastai/learner.py in get_preds(self, ds_idx, dl, with_input, with_decoded, with_loss, act, inner, reorder, cbs, **kwargs)
270.5s 38 306 if with_loss: ctx_mgrs.append(self.loss_not_reduced())
270.5s 39 307 with ContextManagers(ctx_mgrs):
270.5s 40 → 308 self._do_epoch_validate(dl=dl)
270.5s 41 309 if act is None: act = getcallable(self.loss_func, ‘activation’)
270.5s 42 310 res = cb.all_tensors()
270.5s 43
270.5s 44 /opt/conda/lib/python3.7/site-packages/fastai/learner.py in _do_epoch_validate(self, ds_idx, dl)
270.5s 45 242 if dl is None: dl = self.dls[ds_idx]
270.5s 46 243 self.dl = dl
270.5s 47 → 244 with torch.no_grad(): self._with_events(self.all_batches, ‘validate’, CancelValidException)
270.5s 48 245
270.5s 49 246 def do_epoch(self):
270.5s 50
270.5s 51 /opt/conda/lib/python3.7/site-packages/fastai/learner.py in with_events(self, f, event_type, ex, final)
270.5s 52 197
270.5s 53 198 def with_events(self, f, event_type, ex, final=noop):
270.5s 54 → 199 try: self(f’before{event_type}'); f()
270.5s 55 200 except ex: self(f’after_cancel{event_type}')
270.5s 56 201 self(f’after{event_type}‘); final()
270.5s 57
270.5s 58 /opt/conda/lib/python3.7/site-packages/fastai/learner.py in all_batches(self)
270.5s 59 203 def all_batches(self):
270.5s 60 204 self.n_iter = len(self.dl)
270.5s 61 → 205 for o in enumerate(self.dl): self.one_batch(*o)
270.5s 62 206
270.5s 63 207 def _backward(self): self.loss_grad.backward()
270.5s 64
270.5s 65 /opt/conda/lib/python3.7/site-packages/fastai/data/load.py in iter(self)
270.5s 66 125 self.before_iter()
270.5s 67 126 self.__idxs=self.get_idxs() # called in context of main process (not workers/subprocesses)
270.5s 68 → 127 for b in _loadersself.fake_l.num_workers==0:
270.5s 69 128 # pin_memory causes tuples to be converted to lists, so convert them back to tuples
270.5s 70 129 if self.pin_memory and type(b) == list: b = tuple(b)
270.5s 71
270.5s 72 /opt/conda/lib/python3.7/site-packages/torch/utils/data/dataloader.py in next(self)
270.5s 73 626 # TODO(Bug in dataloader iterator found by mypy · Issue #76750 · pytorch/pytorch · GitHub)
270.5s 74 627 self._reset() # type: ignore[call-arg]
270.5s 75 → 628 data = self._next_data()
270.5s 76 629 self._num_yielded += 1
270.5s 77 630 if self._dataset_kind == _DatasetKind.Iterable and
270.5s 78
270.5s 79 /opt/conda/lib/python3.7/site-packages/torch/utils/data/dataloader.py in _next_data(self)
270.5s 80 669 def _next_data(self):
270.5s 81 670 index = self._next_index() # may raise StopIteration
270.5s 82 → 671 data = self._dataset_fetcher.fetch(index) # may raise StopIteration
270.5s 83 672 if self._pin_memory:
270.5s 84 673 data = _utils.pin_memory.pin_memory(data, self._pin_memory_device)
270.5s 85
270.5s 86 /opt/conda/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py in fetch(self, possibly_batched_index)
270.5s 87 41 raise StopIteration
270.5s 88 42 else:
270.5s 89 —> 43 data = next(self.dataset_iter)
270.5s 90 44 return self.collate_fn(data)
270.5s 91 45
270.5s 92
270.5s 93 /opt/conda/lib/python3.7/site-packages/fastai/data/load.py in create_batches(self, samps)
270.5s 94 136 if self.dataset is not None: self.it = iter(self.dataset)
270.5s 95 137 res = filter(lambda o:o is not None, map(self.do_item, samps))
270.5s 96 → 138 yield from map(self.do_batch, self.chunkify(res))
270.5s 97 139
270.5s 98 140 def new(self, dataset=None, cls=None, **kwargs):
270.5s 99
270.5s 100 /opt/conda/lib/python3.7/site-packages/fastcore/basics.py in chunked(it, chunk_sz, drop_last, n_chunks)
270.5s 101 228 if not isinstance(it, Iterator): it = iter(it)
270.5s 102 229 while True:
270.5s 103 → 230 res = list(itertools.islice(it, chunk_sz))
270.5s 104 231 if res and (len(res)==chunk_sz or not drop_last): yield res
270.5s 105 232 if len(res)<chunk_sz: return
270.5s 106
270.5s 107 /opt/conda/lib/python3.7/site-packages/fastai/data/load.py in do_item(self, s)
270.5s 108 151 def prebatched(self): return self.bs is None
270.5s 109 152 def do_item(self, s):
270.5s 110 → 153 try: return self.after_item(self.create_item(s))
270.5s 111 154 except SkipItemException: return None
270.5s 112 155 def chunkify(self, b): return b if self.prebatched else chunked(b, self.bs, self.drop_last)
270.5s 113
270.5s 114 /opt/conda/lib/python3.7/site-packages/fastai/data/load.py in create_item(self, s)
270.5s 115 158 def retain(self, res, b): return retain_types(res, b[0] if is_listy(b) else b)
270.5s 116 159 def create_item(self, s):
270.5s 117 → 160 if self.indexed: return self.dataset[s or 0]
270.5s 118 161 elif s is None: return next(self.it)
270.5s 119 162 else: raise IndexError(“Cannot index an iterable dataset numerically - must use None.”)
270.5s 120
270.5s 121 /opt/conda/lib/python3.7/site-packages/fastai/data/core.py in getitem(self, it)
270.5s 122 456
270.5s 123 457 def getitem(self, it):
270.5s 124 → 458 res = tuple([tl[it] for tl in self.tls])
270.5s 125 459 return res if is_indexer(it) else list(zip(*res))
270.5s 126 460
270.5s 127
270.5s 128 /opt/conda/lib/python3.7/site-packages/fastai/data/core.py in (.0)
270.5s 129 456
270.5s 130 457 def getitem(self, it):
270.5s 131 → 458 res = tuple([tl[it] for tl in self.tls])
270.5s 132 459 return res if is_indexer(it) else list(zip(*res))
270.5s 133 460
270.5s 134
270.5s 135 /opt/conda/lib/python3.7/site-packages/fastai/data/core.py in getitem(self, idx)
270.5s 136 415 res = super().getitem(idx)
270.5s 137 416 if self._after_item is None: return res
270.5s 138 → 417 return self._after_item(res) if is_indexer(idx) else res.map(self._after_item)
270.5s 139 418
270.5s 140 419 # %% …/…/nbs/03_data.core.ipynb 53
270.5s 141
270.5s 142 /opt/conda/lib/python3.7/site-packages/fastai/data/core.py in _after_item(self, o)
270.5s 143 375 raise
270.5s 144 376 def subset(self, i): return self._new(self._get(self.splits[i]), split_idx=i)
270.5s 145 → 377 def _after_item(self, o): return self.tfms(o)
270.5s 146 378 def repr(self): return f"{self.class.name}: {self.items}\ntfms - {self.tfms.fs}"
270.5s 147 379 def iter(self): return (self[i] for i in range(len(self)))
270.5s 148
270.5s 149 /opt/conda/lib/python3.7/site-packages/fastcore/transform.py in call(self, o)
270.5s 150 206 self.fs = self.fs.sorted(key=‘order’)
270.5s 151 207
270.5s 152 → 208 def call(self, o): return compose_tfms(o, tfms=self.fs, split_idx=self.split_idx)
270.5s 153 209 def repr(self): return f"Pipeline: {’ → ‘.join([f.name for f in self.fs if f.name != ‘noop’])}"
270.5s 154 210 def getitem(self,i): return self.fs[i]
270.5s 155
270.5s 156 /opt/conda/lib/python3.7/site-packages/fastcore/transform.py in compose_tfms(x, tfms, is_enc, reverse, **kwargs)
270.5s 157 156 for f in tfms:
270.5s 158 157 if not is_enc: f = f.decode
270.5s 159 → 158 x = f(x, **kwargs)
270.5s 160 159 return x
270.5s 161 160
270.5s 162
270.5s 163 /opt/conda/lib/python3.7/site-packages/fastcore/transform.py in call(self, x, **kwargs)
270.5s 164 79 @property
270.5s 165 80 def name(self): return getattr(self, ‘_name’, _get_name(self))
270.5s 166 —> 81 def call(self, x, **kwargs): return self._call(‘encodes’, x, **kwargs)
270.5s 167 82 def decode (self, x, **kwargs): return self._call(‘decodes’, x, **kwargs)
270.5s 168 83 def repr(self): return f’{self.name}:\nencodes: {self.encodes}decodes: {self.decodes}’
270.5s 169
270.5s 170 /opt/conda/lib/python3.7/site-packages/fastcore/transform.py in _call(self, fn, x, split_idx, **kwargs)
270.5s 171 89 def _call(self, fn, x, split_idx=None, **kwargs):
270.5s 172 90 if split_idx!=self.split_idx and self.split_idx is not None: return x
270.5s 173 —> 91 return self._do_call(getattr(self, fn), x, **kwargs)
270.5s 174 92
270.5s 175 93 def _do_call(self, f, x, **kwargs):
270.5s 176
270.5s 177 /opt/conda/lib/python3.7/site-packages/fastcore/transform.py in do_call(self, f, x, **kwargs)
270.5s 178 95 if f is None: return x
270.5s 179 96 ret = f.returns(x) if hasattr(f,‘returns’) else None
270.5s 180 —> 97 return retain_type(f(x, **kwargs), x, ret)
270.5s 181 98 res = tuple(self.do_call(f, x, **kwargs) for x in x)
270.5s 182 99 return retain_type(res, x)
270.5s 183
270.5s 184 /opt/conda/lib/python3.7/site-packages/fastcore/dispatch.py in call(self, *args, **kwargs)
270.5s 185 118 elif self.inst is not None: f = MethodType(f, self.inst)
270.5s 186 119 elif self.owner is not None: f = MethodType(f, self.owner)
270.5s 187 → 120 return f(*args, **kwargs)
270.5s 188 121
270.5s 189 122 def get(self, inst, owner):
270.5s 190
270.5s 191 /opt/conda/lib/python3.7/site-packages/fastai/vision/core.py in create(cls, fn, **kwargs)
270.5s 192 123 if isinstance(fn,bytes): fn = io.BytesIO(fn)
270.5s 193 124 if isinstance(fn,Image.Image) and not isinstance(fn,cls): return cls(fn)
270.5s 194 → 125 return cls(load_image(fn, **merge(cls._open_args, kwargs)))
270.5s 195 126
270.5s 196 127 def show(self, ctx=None, **kwargs):
270.5s 197
270.5s 198 /opt/conda/lib/python3.7/site-packages/fastai/vision/core.py in load_image(fn, mode)
270.5s 199 96 def load_image(fn, mode=None):
270.5s 200 97 “Open and load a PIL.Image and convert to mode”
270.5s 201 —> 98 im = Image.open(fn)
270.5s 202 99 im.load()
270.5s 203 100 im = im._new(im.im)
270.5s 204
270.5s 205 /opt/conda/lib/python3.7/site-packages/PIL/Image.py in open(fp, mode, formats)
270.5s 206 3138 exclusive_fp = True
270.5s 207 3139
270.5s 208 → 3140 prefix = fp.read(16)
270.5s 209 3141
270.5s 210 3142 preinit()
270.5s 211
270.5s 212 /opt/conda/lib/python3.7/site-packages/PIL/Image.py in getattr(self, name)
270.5s 213 515 deprecate(“Image categories”, 10, “is_animated”, plural=True)
270.5s 214 516 return self._category
270.5s 215 → 517 raise AttributeError(name)
270.5s 216 518
270.5s 217 519 @property
270.5s 218
270.5s 219 AttributeError: read
270.5s 220
285.6s 221 /opt/conda/lib/python3.7/site-packages/traitlets/traitlets.py:2935: FutureWarning: --Exporter.preprocessors=[“remove_papermill_header.RemovePapermillHeader”] for containers is deprecated in traitlets 5.0. You can pass --Exporter.preprocessors item … multiple times to add items to a list.
285.6s 222 FutureWarning,
285.6s 223 [NbConvertApp] Converting notebook notebook.ipynb to notebook
286.0s 224 [NbConvertApp] Writing 986114 bytes to notebook.ipynb
300.9s 225 /opt/conda/lib/python3.7/site-packages/traitlets/traitlets.py:2935: FutureWarning: --Exporter.preprocessors=[“nbconvert.preprocessors.ExtractOutputPreprocessor”] for containers is deprecated in traitlets 5.0. You can pass --Exporter.preprocessors item … multiple times to add items to a list.
300.9s 226 FutureWarning,
300.9s 227 [NbConvertApp] Converting notebook notebook.ipynb to html
302.1s 228 /opt/conda/lib/python3.7/site-packages/bleach/sanitizer.py:168: NoCssSanitizerWarning: ‘style’ attribute specified, but css_sanitizer not set.
302.1s 229 category=NoCssSanitizerWarning,
302.1s 230 [NbConvertApp] Support files will be in __results___files/
302.1s 231 [NbConvertApp] Making directory __results___files
302.1s 232 [NbConvertApp] Making directory __results___files
302.1s 233 [NbConvertApp] Making directory __results___files
I’m trying to run the notebook for the