After updating fast-ai library:
sudo /opt/anaconda3/bin/conda install -c fastai fastai
Solving environment: done
## Package Plan ##
environment location: /opt/anaconda3
added / updated specs:
- fastai
The following packages will be downloaded:
package | build
---------------------------|-----------------
fastprogress-0.1.15 | py_0 13 KB fastai
fastai-1.0.19 | py_1 92 KB fastai
------------------------------------------------------------
Total: 105 KB
The following packages will be UPDATED:
fastai: 1.0.13-py_1 fastai --> 1.0.19-py_1 fastai
fastprogress: 0.1.10-py_0 fastai --> 0.1.15-py_0 fastai
Proceed ([y]/n)? y
Downloading and Extracting Packages
fastprogress-0.1.15 | 13 KB | ################################################################################################################## | 100%
fastai-1.0.19 | 92 KB | ################################################################################################################## | 100%
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
I am getting below error for data.show_batch(rows=3, figsize=(7,6)) and learn.fit_one_cycle(4) respectively
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
in
----> 1 data.show_batch(rows=3, figsize=(7,6))
/opt/anaconda3/lib/python3.6/site-packages/fastai/vision/data.py in show_batch(self, rows, figsize, is_train)
365
366 def show_batch(self:DataBunch, rows:int=None, figsize:Tuple[int,int]=(9,10), is_train:bool=True)->None:
--> 367 show_image_batch(self.train_dl if is_train else self.valid_dl, self.classes, figsize=figsize, rows=rows)
368
369 def labels_to_csv(self, dest:str)->None:
/opt/anaconda3/lib/python3.6/site-packages/fastai/vision/data.py in show_image_batch(dl, classes, rows, figsize)
44 fig, axs = plt.subplots(rows,rows,figsize=figsize)
45 for i, ax in zip(b_idx[:rows*rows], axs.flatten()):
---> 46 x,y = dl.dataset[i]
47 x.show(ax=ax, y=y, classes=classes)
48 plt.tight_layout()
/opt/anaconda3/lib/python3.6/site-packages/fastai/vision/data.py in __getitem__(self, idx)
218 "Return tfms(x),y."
219 x,y = self.ds[idx]
--> 220 x = apply_tfms(self.tfms, x, **self.kwargs)
221 if self.tfm_y: y = apply_tfms(self.tfms, y, **self.y_kwargs)
222 return x, y
/opt/anaconda3/lib/python3.6/site-packages/fastai/vision/image.py in apply_tfms(tfms, x, do_resolve, xtra, size, mult, resize_method, padding_mode, **kwargs)
591 if resize_method in (ResizeMethod.CROP,ResizeMethod.PAD):
592 x = tfm(x, size=size, padding_mode=padding_mode)
--> 593 else: x = tfm(x)
594 return x
/opt/anaconda3/lib/python3.6/site-packages/fastai/vision/image.py in __call__(self, x, *args, **kwargs)
492 def __call__(self, x:Image, *args, **kwargs)->Image:
493 "Randomly execute our tfm on `x`."
--> 494 return self.tfm(x, *args, **{**self.resolved, **kwargs}) if self.do_run else x
495
496 def _resolve_tfms(tfms:TfmList):
/opt/anaconda3/lib/python3.6/site-packages/fastai/vision/image.py in __call__(self, p, is_random, *args, **kwargs)
437 def __call__(self, *args:Any, p:float=1., is_random:bool=True, **kwargs:Any)->Image:
438 "Calc now if `args` passed; else create a transform called prob `p` if `random`."
--> 439 if args: return self.calc(*args, **kwargs)
440 else: return RandTransform(self, kwargs=kwargs, is_random=is_random, p=p)
441
/opt/anaconda3/lib/python3.6/site-packages/fastai/vision/image.py in calc(self, x, *args, **kwargs)
442 def calc(self, x:Image, *args:Any, **kwargs:Any)->Image:
443 "Apply to image `x`, wrapping it if necessary."
--> 444 if self._wrap: return getattr(x, self._wrap)(self.func, *args, **kwargs)
445 else: return self.func(x, *args, **kwargs)
446
/opt/anaconda3/lib/python3.6/site-packages/fastai/vision/image.py in pixel(self, func, *args, **kwargs)
162 def pixel(self, func:PixelFunc, *args, **kwargs)->'Image':
163 "Equivalent to `image.px = func(image.px)`."
--> 164 self.px = func(self.px, *args, **kwargs)
165 return self
166
/opt/anaconda3/lib/python3.6/functools.py in wrapper(*args, **kw)
801
802 def wrapper(*args, **kw):
--> 803 return dispatch(args[0].__class__)(*args, **kw)
804
805 registry[object] = func
TypeError: crop_pad() missing 1 required positional argument: 'size'
and
epoch train_loss valid_loss error_rate
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-71-495233eaf2b4> in <module>
----> 1 learn.fit_one_cycle(4)
/opt/anaconda3/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)
20 callbacks.append(OneCycleScheduler(learn, max_lr, moms=moms, div_factor=div_factor,
21 pct_start=pct_start, **kwargs))
---> 22 learn.fit(cyc_len, max_lr, wd=wd, callbacks=callbacks)
23
24 def lr_find(learn:Learner, start_lr:Floats=1e-7, end_lr:Floats=10, num_it:int=100, stop_div:bool=True, **kwargs:Any):
/opt/anaconda3/lib/python3.6/site-packages/fastai/basic_train.py in fit(self, epochs, lr, wd, callbacks)
160 callbacks = [cb(self) for cb in self.callback_fns] + listify(callbacks)
161 fit(epochs, self.model, self.loss_func, opt=self.opt, data=self.data, metrics=self.metrics,
--> 162 callbacks=self.callbacks+callbacks)
163
164 def create_opt(self, lr:Floats, wd:Floats=0.)->None:
/opt/anaconda3/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
/opt/anaconda3/lib/python3.6/site-packages/fastai/basic_train.py in fit(epochs, model, loss_func, opt, data, callbacks, metrics)
80 cb_handler.on_epoch_begin()
81
---> 82 for xb,yb in progress_bar(data.train_dl, parent=pbar):
83 xb, yb = cb_handler.on_batch_begin(xb, yb)
84 loss = loss_batch(model, xb, yb, loss_func, opt, cb_handler)
/opt/anaconda3/lib/python3.6/site-packages/fastprogress/fastprogress.py in __iter__(self)
63 self.update(0)
64 try:
---> 65 for i,o in enumerate(self._gen):
66 yield o
67 if self.auto_update: self.update(i+1)
/opt/anaconda3/lib/python3.6/site-packages/fastai/basic_data.py in __iter__(self)
80 def __iter__(self):
81 "Process and returns items from `DataLoader`."
---> 82 for b in self.dl: yield self.proc_batch(b)
83
84 def one_batch(self)->Collection[Tensor]:
/opt/anaconda3/lib/python3.6/site-packages/torch/utils/data/dataloader.py in __next__(self)
635 self.reorder_dict[idx] = batch
636 continue
--> 637 return self._process_next_batch(batch)
638
639 next = __next__ # Python 2 compatibility
/opt/anaconda3/lib/python3.6/site-packages/torch/utils/data/dataloader.py in _process_next_batch(self, batch)
656 self._put_indices()
657 if isinstance(batch, ExceptionWrapper):
--> 658 raise batch.exc_type(batch.exc_msg)
659 return batch
660
TypeError: Traceback (most recent call last):
File "/opt/anaconda3/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 138, in _worker_loop
samples = collate_fn([dataset[i] for i in batch_indices])
File "/opt/anaconda3/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 138, in <listcomp>
samples = collate_fn([dataset[i] for i in batch_indices])
File "/opt/anaconda3/lib/python3.6/site-packages/fastai/vision/data.py", line 220, in __getitem__
x = apply_tfms(self.tfms, x, **self.kwargs)
File "/opt/anaconda3/lib/python3.6/site-packages/fastai/vision/image.py", line 593, in apply_tfms
else: x = tfm(x)
File "/opt/anaconda3/lib/python3.6/site-packages/fastai/vision/image.py", line 494, in __call__
return self.tfm(x, *args, **{**self.resolved, **kwargs}) if self.do_run else x
File "/opt/anaconda3/lib/python3.6/site-packages/fastai/vision/image.py", line 439, in __call__
if args: return self.calc(*args, **kwargs)
File "/opt/anaconda3/lib/python3.6/site-packages/fastai/vision/image.py", line 444, in calc
if self._wrap: return getattr(x, self._wrap)(self.func, *args, **kwargs)
File "/opt/anaconda3/lib/python3.6/site-packages/fastai/vision/image.py", line 164, in pixel
self.px = func(self.px, *args, **kwargs)
File "/opt/anaconda3/lib/python3.6/functools.py", line 803, in wrapper
return dispatch(args[0].__class__)(*args, **kw)
TypeError: crop_pad() missing 1 required positional argument: 'size'