[data] add dataloader for lance datasource

python/ray/data/_internal/datasource/lance_datasource.py

@@ -2,6 +2,7 @@
 from typing import TYPE_CHECKING, Any, Dict, Iterator, List, Optional
 
 import numpy as np
+from torch.utils.data import Dataset
 
 from ray.data._internal.util import _check_import, call_with_retry
 from ray.data.block import BlockMetadata
@@ -97,6 +98,34 @@ def estimate_inmemory_data_size(self) -> Optional[int]:
         # TODO(chengsu): Add memory size estimation to improve auto-tune of parallelism.
         return None
 
+    class LanceDataset(Dataset):
+        """Custom Dataset to load images and their corresponding captions"""
+
+        def __init__(self, ds: "LanceDatasource"):
+            self.ds = ds
+            self.lance_ds = ds.lance_ds
+
+        def __len__(self):
+            return self.lance_ds.count_rows()
+
+        def __getitem__(self, idx):
+            # Load the image and caption
+            return self.lance_ds.take(
+                [idx],
+                columns=self.ds.scanner_options["columns"],
+                filter=self.ds.scanner_options["filter"],
+            ).to_pydict()
+
+    def to_torch_dataset(
+        self,
+    ) -> Dataset:
+        return self.LanceDataset(ds=self)
+
+    def count(
+        self,
+    ) -> int:
+        return self.lance_ds.count_rows(filter=self.scanner_options["filter"])
+
 
 def _read_fragments_with_retry(
     fragment_ids,

python/ray/data/tests/test_lance.py

@@ -5,11 +5,13 @@
 import pytest
 from pkg_resources import parse_version
 from pytest_lazyfixture import lazy_fixture
+from torch.utils.data import DataLoader
 
 import ray
 from ray._private.test_utils import wait_for_condition
 from ray._private.utils import _get_pyarrow_version
 from ray.data import Schema
+from ray.data._internal.datasource.lance_datasource import LanceDatasource
 from ray.data.datasource.path_util import _unwrap_protocol
 
 
@@ -114,6 +116,37 @@ def test_lance():
     wait_for_condition(test_lance, timeout=10)
 
 
+@pytest.mark.parametrize("data_path", [lazy_fixture("local_path")])
+def test_torch_dataset(data_path):
+    setup_data_path = _unwrap_protocol(data_path)
+    path = os.path.join(setup_data_path, "test.lance")
+    num_rows = 1024
+    data = pa.table(
+        {
+            "id": pa.array(range(num_rows)),
+            "name": pa.array([f"test_{i}" for i in range(num_rows)]),
+        }
+    )
+    lance.write_dataset(data, path, max_rows_per_file=1)
+
+    ds = LanceDatasource(path, columns=["name"], filter="id < 50 and id > 10")
+    assert ds.count() == 39
+    train_ds = ds.to_torch_dataset()
+
+    def custom_collate_fn(batch):
+        if isinstance(batch[0], dict):
+            return [item["name"] for item in batch]
+        else:
+            return [item[0] for item in batch]
+
+    dataloader = DataLoader(
+        train_ds, batch_size=10, shuffle=False, collate_fn=custom_collate_fn
+    )
+    for batch in dataloader:
+        assert len(batch) == 10
+        break
+
+
 if __name__ == "__main__":
     import sys
 

python/requirements/ml/data-requirements.txt

@@ -13,4 +13,5 @@ pandas==1.5.3; python_version < '3.12'
 modin==0.31.0; python_version >= '3.12'
 pandas==2.2.2; python_version >= '3.12'
 responses==0.13.4
+torch==2.3.0
 pymars>=0.8.3; python_version < "3.12"

python/requirements/ml/data-test-requirements.txt

@@ -14,6 +14,7 @@ google-api-core==1.34.0
 webdataset
 raydp==1.7.0b20231020.dev0
 pylance
+torch==2.3.0
 delta-sharing
 pytest-mock
 decord

python/requirements_compiled.txt

@@ -1598,6 +1598,8 @@ pyjwt==2.8.0
     #   snowflake-connector-python
 pylance==0.10.18
     # via -r /ray/ci/../python/requirements/ml/data-test-requirements.txt
+torch==2.3.0
+    # via -r /ray/ci/../python/requirements/ml/data-test-requirements.txt
 pymars==0.10.0 ; python_version < "3.12"
     # via -r /ray/ci/../python/requirements/ml/data-requirements.txt
 pymongo==4.3.2