I am running pytorch 0.3.0.post4 on Ubuntu 14.04 (conda 4.3.25, python 3.6.2, cuda 8.0).
Here is what I get when importing torchvision.transforms

>>> from torchvision import transforms
>>> dir(transforms)
['CenterCrop',
 'Compose',
 'Image',
 'ImageOps',
 'Lambda',
 'Normalize',
 'Pad',
 'RandomCrop',
 'RandomHorizontalFlip',
 'RandomSizedCrop',
 'Scale',
 'ToPILImage',
 'ToTensor',
 '__builtins__',
 '__cached__',
 '__doc__',
 '__file__',
 '__loader__',
 '__name__',
 '__package__',
 '__spec__',
 'division',
 'math',
 'np',
 'numbers',
 'random',
 'torch',
 'types']
As you can see most of the transforms currently documented are missing, resulting in AttributeErrors such as this one
>>> transforms.RandomResizedCrop(224)
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-9-5275ac2684b6> in <module>()
----> 1 transforms.RandomResizedCrop(224)
AttributeError: module 'torchvision.transforms' has no attribute 'RandomResizedCrop'
Am I not using the latest pytorch version or am I missing something very basic here?

Thanks for the help in advance!
              
Thanks for the reply. I didn’t know torch and torchvision were different packages.
I tried running conda install torchvision -c soumith which upgraded torchvision from 0.1.8 to 0.1.9.

As far as I can see, googling around, the latest release is 0.2. Nowhere I could find a reference to 0.3.

Do you know how to upgrade properly?
              
I have tried to update torchvision by using the command line:

conda install torchvision -c soumith
then I got this :
Solving environment: done
# All requested packages already installed.
so i used the following commands in python shell :
from torchvision import transforms
dir(transforms)
then i got the list of function and found RandomSizedCroped
              
If conda cannot find the latest package, you could try to update conda with conda update conda and then re-run the install command.
I think it’s almost the same, but while RandomSizedCrop resizes the image to its original input size, you can specify the size to which it will be resized in RandomResizedCrop.