Fix map() failing to create dataset when input_dir is None (#100)

src/litdata/processing/data_processor.py

@@ -1019,7 +1019,7 @@ def run(self, data_recipe: DataRecipe) -> None:
         print("Workers are finished.")
         result = data_recipe._done(len(user_items), self.delete_cached_files, self.output_dir)
 
-        if num_nodes == node_rank + 1 and self.output_dir.url and _IS_IN_STUDIO and self.input_dir.path:
+        if num_nodes == node_rank + 1 and self.output_dir.url and _IS_IN_STUDIO:
             assert self.output_dir.path
             _create_dataset(
                 input_dir=self.input_dir.path,

tests/processing/test_data_processor.py

@@ -5,6 +5,7 @@
 from pathlib import Path
 from typing import Any, List
 from unittest import mock
+from unittest.mock import ANY, Mock
 
 import numpy as np
 import pytest
@@ -901,7 +902,7 @@ def map_fn_index(index, output_dir):
 
 
 @pytest.mark.skipif(condition=not _PIL_AVAILABLE or sys.platform == "win32", reason="Requires: ['pil']")
-def test_data_processing_map_without_input_dir(monkeypatch, tmpdir):
+def test_data_processing_map_without_input_dir_local(monkeypatch, tmpdir):
     cache_dir = os.path.join(tmpdir, "cache")
     output_dir = os.path.join(tmpdir, "target_dir")
     os.makedirs(output_dir, exist_ok=True)
@@ -920,6 +921,46 @@ def test_data_processing_map_without_input_dir(monkeypatch, tmpdir):
     assert sorted(os.listdir(output_dir)) == ["0.JPEG", "1.JPEG", "2.JPEG", "3.JPEG", "4.JPEG"]
 
 
+@pytest.mark.skipif(sys.platform == "win32", reason="Windows not supported")
+def test_data_processing_map_without_input_dir_remote(monkeypatch, tmpdir):
+    cache_dir = os.path.join(tmpdir, "cache")
+    output_dir = os.path.join("/teamspace", "datasets", "target_dir")
+
+    monkeypatch.setenv("DATA_OPTIMIZER_CACHE_FOLDER", cache_dir)
+    monkeypatch.setenv("DATA_OPTIMIZER_DATA_CACHE_FOLDER", cache_dir)
+
+    create_dataset_mock = Mock()
+    monkeypatch.setenv("LIGHTNING_CLUSTER_ID", "1")
+    monkeypatch.setenv("LIGHTNING_CLOUD_PROJECT_ID", "2")
+    monkeypatch.setenv("LIGHTNING_CLOUD_SPACE_ID", "3")
+    monkeypatch.setattr("litdata.processing.data_processor._IS_IN_STUDIO", True)
+    monkeypatch.setattr(
+        "litdata.streaming.resolver._resolve_datasets",
+        Mock(return_value=Dir(path=tmpdir / "output", url="url")),
+    )
+    monkeypatch.setattr("litdata.processing.data_processor._create_dataset", create_dataset_mock)
+
+    map(
+        map_fn_index,
+        list(range(5)),
+        output_dir=output_dir,
+        num_workers=1,
+    )
+
+    create_dataset_mock.assert_called_with(
+        input_dir=None,
+        storage_dir=str(tmpdir / "output"),
+        dataset_type=ANY,
+        empty=ANY,
+        size=ANY,
+        num_bytes=ANY,
+        data_format=ANY,
+        compression=ANY,
+        num_chunks=ANY,
+        num_bytes_per_chunk=ANY,
+    )
+
+
 @pytest.mark.skipif(condition=not _PIL_AVAILABLE or sys.platform == "win32", reason="Requires: ['pil']")
 def test_data_processing_map_weights_mismatch(monkeypatch, tmpdir):
     cache_dir = os.path.join(tmpdir, "cache")