Daniel Voigt Godoy - Deep Learning with PyTorch Step-by-Step A Beginner’s Guide-leanpub

Output
{'labels': 1,
'sentence': 'There was nothing so VERY remarkable in that; nor did
Alice think it so VERY much out of the way to hear the Rabbit say to
itself, `Oh dear!',
'source': 'alice28-1476.txt'}
Now that the labels are in place, we can finally shuffle the dataset and split it into
training and test sets:
Data Preparation
1 shuffled_dataset = dataset.shuffle(seed=42)
2 split_dataset = shuffled_dataset.train_test_split(test_size=0.2)
3 split_dataset
Output
DatasetDict({
train: Dataset({
features: ['sentence', 'source'],
num_rows: 3081
})
test: Dataset({
features: ['sentence', 'source'],
num_rows: 771
})
})
The splits are actually a dataset dictionary, so you may want to retrieve the actual
datasets from it:
Data Preparation
1 train_dataset = split_dataset['train']
2 test_dataset = split_dataset['test']
Done! We have two—training and test—randomly shuffled datasets.
Building a Dataset | 895