I am new with Pytorch and not very expert in CNN.
I have done a successful classifier with the tutorial that they provide [Tutorial Pytorch](http://pytorch.org/tutorials/beginner/transfer_learning_tutorial.html), but I don't really understand what I am doing when loading the data.

They do some data augmentation and normalisation for training, but when I try to modify the parameters, the code does not work.

```
# Data augmentation and normalization for training
# Just normalization for validation
data_transforms = {
    'train': transforms.Compose([
        transforms.RandomResizedCrop(224),
        transforms.RandomHorizontalFlip(),
        transforms.ToTensor(),
        transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
    ]),
    'val': transforms.Compose([
        transforms.Resize(256),
        transforms.CenterCrop(224),
        transforms.ToTensor(),
        transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
    ]),
}

```

Am I extending my training dataset? I don't see the data augmentation.

Why if I modify the value of transforms.RandomResizedCrop(224) the data loading stop working? 

Do I need to transform as well the test dataset?

I am a bit confused with this data transformation that they do.