add custom doc and test for converter

docs/source/gs-processing/developer/input-configuration.rst

@@ -173,6 +173,15 @@ objects:
          assign to the validation set [0.0, 1.0).
       -  ``test``: The percentage of the data with available labels to
          assign to the test set [0.0, 1.0).
+   -  ``custom_split_filenames`` (JSON object, optional): Specifies the customized
+      training/validation/test mask. Once it is defined, GSProcessing will ignore
+      the ``split_rate``.
+      -  ``train``: Path of the training mask file such that each line contains
+    the original ID for node tasks, or the pair [source_id, destination_id] for edge tasks.
+      -  ``val``: Path of the validation mask file such that each line contains
+    the original ID for node tasks, or the pair [source_id, destination_id] for edge tasks.
+      -  ``test``: Path of the test mask file such that each line contains
+    the original ID for node tasks, or the pair [source_id, destination_id] for edge tasks.
 
 -  ``features`` (List of JSON objects, optional)\ **:** Describes
    the set of features for the current edge type. See the :ref:`features-object` section for details.

graphstorm-processing/tests/test_converter.py

@@ -166,6 +166,45 @@ def test_read_node_gconstruct(converter: GConstructConfigConverter, node_dict: d
         }
     ]
 
+    node_dict["nodes"].append(
+        {
+            "node_type": "paper_custom",
+            "format": {"name": "parquet"},
+            "files": ["/tmp/acm_raw/nodes/paper_custom.parquet"],
+            "node_id_col": "node_id",
+            "labels": [
+                {
+                    "label_col": "label",
+                    "task_type": "classification",
+                    "custom_split_filenames": {"train": "customized_label/node_train_idx.parquet",
+                                   "valid": "customized_label/node_val_idx.parquet",
+                                   "test": "customized_label/node_test_idx.parquet",
+                                    "column": ["ID"]},
+                    "label_stats_type": "frequency_cnt"}
+            ],
+        }
+    )
+
+    # nodes with all elements
+    # [self.type, self.format, self.files, self.separator, self.column, self.features, self.labels]
+    node_config = converter.convert_nodes(node_dict["nodes"])[2]
+    assert len(converter.convert_nodes(node_dict["nodes"])) == 3
+    assert node_config.node_type == "paper_custom"
+    assert node_config.file_format == "parquet"
+    assert node_config.files == ["/tmp/acm_raw/nodes/paper_custom.parquet"]
+    assert node_config.separator is None
+    assert node_config.column == "node_id"
+    assert node_config.labels == [
+        {
+            "column": "label",
+            "type": "classification",
+            "custom_split_filenames": {"train": "customized_label/node_train_idx.parquet",
+                                       "valid": "customized_label/node_val_idx.parquet",
+                                       "test": "customized_label/node_test_idx.parquet",
+                                       "column": ["ID"]}
+        }
+    ]
+
 
 @pytest.mark.parametrize("col_name", ["author", ["author"]])
 def test_read_edge_gconstruct(converter: GConstructConfigConverter, col_name):