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# Copyright Lightning AI. Licensed under the Apache License 2.0, see LICENSE file.
import sys
from unittest import mock
from unittest.mock import ANY
import pytest
from litgpt.data import LitData
@pytest.mark.skipif(sys.platform == "win32", reason="Needs to implement platform agnostic path/url joining")
@mock.patch("litgpt.data.lit_data.LitData._dataloader")
def test_input_dir_and_splits(dl_mock, tmp_path):
with pytest.raises(ValueError, match="If provided `split_names` must be a tuple of two strings"):
LitData(data_path=tmp_path, split_names=("train",))
# local dir, no splits
data = LitData(data_path=tmp_path)
data.train_dataloader()
dl_mock.assert_called_with(input_dir=str(tmp_path), train=True)
data.val_dataloader()
dl_mock.assert_called_with(input_dir=str(tmp_path), train=False)
# local dir, splits
data = LitData(data_path=tmp_path, split_names=("train", "val"))
data.train_dataloader()
dl_mock.assert_called_with(input_dir=str(tmp_path / "train"), train=True)
data.val_dataloader()
dl_mock.assert_called_with(input_dir=str(tmp_path / "val"), train=False)
# remote dir, splits
data = LitData(data_path="s3://mydataset/data", split_names=("train", "val"))
data.train_dataloader()
dl_mock.assert_called_with(input_dir="s3://mydataset/data/train", train=True)
data.val_dataloader()
dl_mock.assert_called_with(input_dir="s3://mydataset/data/val", train=False)
@pytest.mark.skipif(sys.platform == "win32", reason="Needs to implement platform agnostic path/url joining")
@mock.patch("litdata.streaming.StreamingDataset")
@mock.patch("litdata.streaming.StreamingDataLoader")
def test_dataset_args(streaming_dataloader_mock, streaming_dataset_mock, tmp_path):
data = LitData(data_path=tmp_path, seed=1000)
data.train_dataloader()
streaming_dataset_mock.assert_called_with(
input_dir=str(tmp_path),
item_loader=ANY,
shuffle=True,
seed=1000,
)
streaming_dataloader_mock.assert_called_with(
streaming_dataset_mock(),
batch_size=1,
pin_memory=True,
num_workers=8,
drop_last=True,
)
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