add test

graphstorm-processing/tests/test_converter.py

@@ -65,6 +65,65 @@ def test_try_read_unsupported_feature(converter: GConstructConfigConverter, node
         _ = converter.convert_nodes(node_dict["nodes"])
 
 
+def test_try_read_invalid_gconstruct_config(converter: GConstructConfigConverter, node_dict: dict):
+    """Custom Split Columns"""
+    node_dict["nodes"][0]["labels"] = [
+        {
+            "label_col": "label",
+            "task_type": "classification",
+            "custom_split_filenames": {
+                "column": ["src", "dst", "inter"],
+            },
+            "label_stats_type": "frequency_cnt",
+        }
+    ]
+
+    with pytest.raises(AssertionError):
+        _ = converter.convert_nodes(node_dict["nodes"])
+
+    """Feature Name must exist for multiple feature columns"""
+    node_dict["nodes"][0]["features"] = [
+        {
+            "feature_col": ["feature_1", "feature_2"]
+        }
+    ]
+
+    with pytest.raises(AssertionError):
+        _ = converter.convert_nodes(node_dict["nodes"])
+
+    """Unsupported output dtype"""
+    node_dict["nodes"][0]["features"] = [
+        {
+            "feature_col": ["feature_1"],
+            "out_dtype": "float16"
+        }
+    ]
+
+    with pytest.raises(AssertionError):
+        _ = converter.convert_nodes(node_dict["nodes"])
+
+    """Unsupported format type"""
+    node_dict["nodes"][0]["format"] = \
+        {"name": "txt", "separator": ","}
+
+    with pytest.raises(AssertionError):
+        _ = converter.convert_nodes(node_dict["nodes"])
+
+
+def test_try_read_multi_task_gconstruct_config(converter: GConstructConfigConverter, node_dict: dict):
+    """Check unsupported mask column """
+    node_dict["nodes"][0]["labels"] = [
+        {
+            "label_col": "label",
+            "task_type": "classification",
+            "mask_field_names": "train_mask"
+        }
+    ]
+
+    with pytest.raises(AssertionError):
+        _ = converter.convert_nodes(node_dict["nodes"])
+
+
 @pytest.mark.parametrize("transform", ["max_min_norm", "rank_gauss"])
 @pytest.mark.parametrize("out_dtype", ["float16", "float32", "float64"])
 def test_try_convert_out_dtype(