tests/data/test_tinyllama.py

# Copyright Lightning AI. Licensed under the Apache License 2.0, see LICENSE file.
from unittest import mock

import pytest
from litdata.streaming import CombinedStreamingDataset, StreamingDataLoader, StreamingDataset
from torch.utils.data import DataLoader

from litgpt.data import TinyLlama


@mock.patch("litdata.streaming.dataset.subsample_streaming_dataset", return_value=([], []))
def test_tinyllama(_, tmp_path):
    data = TinyLlama(data_path=(tmp_path / "data"))
    assert data.seq_length == 2048
    assert data.batch_size == 1

    data.connect(batch_size=2, max_seq_length=1024)
    assert data.seq_length == 1025
    assert data.batch_size == 2

    with pytest.raises(FileNotFoundError, match="The directory .*data/slimpajama/train does not exist"):
        data.prepare_data()

    (tmp_path / "data" / "slimpajama" / "train").mkdir(parents=True)
    (tmp_path / "data" / "slimpajama" / "val").mkdir(parents=True)
    (tmp_path / "data" / "starcoder").mkdir(parents=True)

    data.prepare_data()
    data.setup()

    train_dataloader = data.train_dataloader()
    assert isinstance(train_dataloader, StreamingDataLoader)
    assert isinstance(train_dataloader.dataset, CombinedStreamingDataset)

    val_dataloader = data.val_dataloader()
    assert isinstance(val_dataloader, DataLoader)
    assert isinstance(val_dataloader.dataset, StreamingDataset)

    # has attributes from super class `LightningDataModule`
    assert data.prepare_data_per_node