Assignment AWS computer vision

[ragguem]

Question 1
First, let's get a particular dataset for this exercise. We will be using the CIFAR10 dataset which is built-in in MXNet in the gluon.data.vision.datasets library.

In the following cell you will complete the function definition so that it returns the CIFAR10 dataset from MXNet. The function should return both the training and the validation dataset. To make things more exciting, the function should examine both the training and validation dataset and return the index that corresponds to the first occurrence of each class in CIFAR10.

For example, the first class (label) in the CIFAR10 training dataset is 6, this corresponds to index 0 in the training dataset. For the remaining classes in the dataset, find the index in the training dataset where that class first occurs. Repeat the same process for the validation dataset. To summarize, the get_cifar_10_dataset function below should return 4 values. The CIFAR10 training dataset, the indices of the training dataset that correspond to the first occurrence of each class, The CIFAR10 validation dataset and the indices of the validation dataset that correspond to the first occurrence of each class.

def get_cifar10_dataset():
train_data = None
val_data = None

train_indices = {}
val_indices = {}

// code here

[phreakyphoenix]

I'm unable to understand the issue. Please paraphrase.