Autoencoder in fastai - autoencoder

Question

I'm trying to build an autoencoder with fast.ai version 1.0.52 and struggling with how to set labels to be equal to original images. I was
following this blog post: https://alanbertl.com/autoencoder-with-fast-ai/
I replaced ImageItemList in the original code with ImageList since it was changed in the latest fastai versions.
%reload_ext autoreload
%autoreload 2
%matplotlib inline
from fastai.imports import *
from fastai.vision import *
from fastai.data_block import *
from fastai.basic_train import *
import pandas as pd
x = np.random.randint(256, size=(1000, 16384))
x = x/255
x = x.reshape(-1,128,128)
x = np.stack([x,x,x],1)
x.shape
class ArraysImageList(ImageList,FloatList):
def __init__(self, items:Iterator, log:bool=False, **kwargs):
if isinstance(items, ItemList):
items = items.items
super(FloatList,self).__init__(items,**kwargs)
def get(self,i):
return Tensor(super(FloatList,self).get(i).astype('float32'))
x_il = ArraysImageList(x)
x_ils = x_il.split_by_rand_pct()
lls = x_ils.label_from_lists(x_ils.train, x_ils.valid)
Here's the error message I get.
---------------------------------------------------------------------------
RuntimeError Traceback (most recent call last)
<ipython-input-33-cbada9e18af9> in <module>
----> 1 lls = x_ils.label_from_lists(x_ils.train, x_ils.valid)
~/.local/lib/python3.6/site-packages/fastai/data_block.py in label_from_lists(self, train_labels, valid_labels, label_cls, **kwargs)
484 self.valid = self.valid._label_list(x=self.valid, y=self.train.y.new(valid_labels, **kwargs))
485 self.__class__ = LabelLists
--> 486 self.process()
487 return self
488
~/.local/lib/python3.6/site-packages/fastai/data_block.py in process(self)
520 "Process the inner datasets."
521 xp,yp = self.get_processors()
--> 522 for ds,n in zip(self.lists, ['train','valid','test']): ds.process(xp, yp, name=n)
523 #progress_bar clear the outputs so in some case warnings issued during processing disappear.
524 for ds in self.lists:
~/.local/lib/python3.6/site-packages/fastai/data_block.py in process(self, xp, yp, name)
683 def process(self, xp:PreProcessor=None, yp:PreProcessor=None, name:str=None):
684 "Launch the processing on `self.x` and `self.y` with `xp` and `yp`."
--> 685 self.y.process(yp)
686 if getattr(self.y, 'filter_missing_y', False):
687 filt = array([o is None for o in self.y.items])
~/.local/lib/python3.6/site-packages/fastai/data_block.py in process(self, processor)
73 if processor is not None: self.processor = processor
74 self.processor = listify(self.processor)
---> 75 for p in self.processor: p.process(self)
76 return self
77
~/.local/lib/python3.6/site-packages/fastai/data_block.py in process(self, ds)
334
335 def process(self, ds):
--> 336 if self.classes is None: self.create_classes(self.generate_classes(ds.items))
337 ds.classes = self.classes
338 ds.c2i = self.c2i
~/.local/lib/python3.6/site-packages/fastai/data_block.py in generate_classes(self, items)
391 for c in items: classes = classes.union(set(c))
392 classes = list(classes)
--> 393 classes.sort()
394 return classes
395
RuntimeError: bool value of Tensor with more than one value is ambiguous
Ultimately, I want to read images using a dataframe with image paths. So I also tried the following:
import sklearn
cv = sklearn.model_selection.GroupKFold(n_splits=5)
train_inds, valid_inds = next(cv.split(iso_image_df.group, groups=iso_image_df.group))
img_lists = (ImageList.from_df(iso_image_df, resized_img_path, cols=0).split_by_idxs(train_inds, valid_inds))
src = img_lists.label_from_lists(img_lists.train, img_lists.valid)
data = (src.databunch(bs = 32).normalize(imagenet_stats))
data.show_batch(rows=3, figsize=(10, 10))
Here I get the following error message:
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-146-2514de511e64> in <module>
----> 1 data.show_batch(rows=3, figsize=(10, 10))
~/.local/lib/python3.6/site-packages/fastai/basic_data.py in show_batch(self, rows, ds_type, reverse, **kwargs)
190 #TODO: get rid of has_arg if possible
191 if has_arg(self.train_ds.y.reconstruct, 'x'):
--> 192 ys = [self.train_ds.y.reconstruct(grab_idx(y, i), x=x) for i,x in enumerate(xs)]
193 else : ys = [self.train_ds.y.reconstruct(grab_idx(y, i)) for i in range(n_items)]
194 self.train_ds.x.show_xys(xs, ys, **kwargs)
~/.local/lib/python3.6/site-packages/fastai/basic_data.py in <listcomp>(.0)
190 #TODO: get rid of has_arg if possible
191 if has_arg(self.train_ds.y.reconstruct, 'x'):
--> 192 ys = [self.train_ds.y.reconstruct(grab_idx(y, i), x=x) for i,x in enumerate(xs)]
193 else : ys = [self.train_ds.y.reconstruct(grab_idx(y, i)) for i in range(n_items)]
194 self.train_ds.x.show_xys(xs, ys, **kwargs)
~/.local/lib/python3.6/site-packages/fastai/data_block.py in reconstruct(self, t, x)
89 def reconstruct(self, t:Tensor, x:Tensor=None):
90 "Reconstruct one of the underlying item for its data `t`."
---> 91 return self[0].reconstruct(t,x) if has_arg(self[0].reconstruct, 'x') else self[0].reconstruct(t)
92
93 def new(self, items:Iterator, processor:PreProcessors=None, **kwargs)->'ItemList':
AttributeError: 'Image' object has no attribute 'reconstruct'
Any help is highly appreciated!

Answer 1

The lls are being used to create the databunch.
I've looked at it and given the API change in fastai libs I created the databunch without using the lls that were causing the error:
bs = 64
db = (ImageImageList.from_folder(mnist)
.split_by_folder()
.label_from_func(get_y_fn)
.databunch(bs=bs,num_workers=4))
EDIT: you'll need the get_y_fn; it is very simply defined
def get_y_fn(x): return x
the lls aren't used for anything else anyway
This should fix your problem, let me know if this worked for you.