Confusion regarding Normalized CIFAR10 dataset in Chapter 7
tataganesh opened this issue · 0 comments
tataganesh commented
In Chapter 7, the CIFAR10 dataset is initially loaded as -
cifar10 = datasets.CIFAR10(data_path, train=True, download=True)
Then, section 7.1.4 discusses the importance of normalizing the data. The transformed CIFAR10 dataset is loaded as -
transformed_cifar10 = datasets.CIFAR10(data_path, train=True, download=False,
transform=transforms.Compose([
transforms.ToTensor(),
transforms.Normalize((0.4915, 0.4823, 0.4468),
(0.2470, 0.2435, 0.2616))
]))
However, in section 7.2.1, a dataset consisting of samples with labels 0 and 2 is created using the cifar10
variable.
cifar2 = [(img, label_map[label]) for img, label in cifar10 if label in [0, 2]]
I am assuming that the cifar10 variable here indicates the normalized cifar10 dataset. Hence, would it clearer to replace cifar10
with transformed_cifar10
?
cifar2 = [(img, label_map[label]) for img, label in transformed_cifar10 if label in [0, 2]]
This will ensure that someone who is implementing these steps understands that the normalized data is now being used to train the NN.