Here is one of the points listed in the implementation instruction:

- It’s important to note that the “
`y_pred`

” and “`y_true`

” inputs of tf.keras.losses.categorical_crossentropy are expected to be of shape (number of examples, num_classes).

If you read the comments on the input arguments:

```
Arguments:
logits -- output of forward propagation (output of the last LINEAR unit), of shape (6, num_examples)
labels -- "true" labels vector, same shape as Z3
```

It is because the logits and labels are not in the shape that is expected by the categorical_crossentropy, so, in order for it to work correctly, we need to transpose logits and labels.