!336 revert d52282df2f

Merge pull request !336 from guozhijian/revert_5c2ded8d

mindspore/dataset/engine/datasets.py

@@ -2464,53 +2464,47 @@ class Schema:
         Parse the columns and add it to self.
 
         Args:
-            columns (dict or list[dict]): dataset attribution information, decoded from schema file.
-            if list: columns element must be dict, 'name' and 'type' must be in keys, 'shape' optional.
-            if dict: columns.keys() as name, element in columns.values() is dict, and 'type' inside, 'shape' optional.
-              example 1)
-                [{'name': 'image', 'type': 'int8', 'shape': [3, 3]},
-                 {'name': 'label', 'type': 'int8', 'shape': [1]}]
-              example 2)
-                {'image': {'shape': [3, 3], 'type': 'int8'}, 'label': {'shape': [1], 'type': 'int8'}}
+            columns (dict or list[str]): names of columns.
 
         Raises:
-            RuntimeError: If failed to parse columns.
-            RuntimeError: If unknown items in columns.
+            RuntimeError: If failed to parse schema file.
+            RuntimeError: If unknown items in schema file.
             RuntimeError: If column's name field is missing.
             RuntimeError: If column's type field is missing.
         """
+        if columns is None:
+            raise TypeError("Expected non-empty dict or string list.")
         self.columns = []
-        if isinstance(columns, list):
-            for column in columns:
-                try:
-                    name = column.pop("name")
-                except KeyError:
-                    raise RuntimeError("Column's name is missing")
-                try:
-                    de_type = column.pop("type")
-                except KeyError:
-                    raise RuntimeError("Column' type is missing")
-                shape = column.pop("shape", None)
-                column.pop("t_impl", None)
-                column.pop("rank", None)
-                if column:
-                    raise RuntimeError("Unknown field {}".format(",".join(column.keys())))
-                self.add_column(name, de_type, shape)
-        elif isinstance(columns, dict):
-            for key, value in columns.items():            
-                name = key
-                try:
-                    de_type = value.pop("type")
-                except KeyError:
-                    raise RuntimeError("Column' type is missing")
-                shape = value.pop("shape", None)
-                value.pop("t_impl", None)
-                value.pop("rank", None)
-                if value:
-                    raise RuntimeError("Unknown field {}".format(",".join(value.keys())))
-                self.add_column(name, de_type, shape)
-        else:
-            raise RuntimeError("columns must be dict or list, columns contain name, type, shape(optional).")
+        for col in columns:
+            name = None
+            shape = None
+            data_type = None
+            col_details = None
+            if isinstance(columns, list):
+                col_details = col
+                if "name" in col:
+                    name = col["name"]
+            elif isinstance(columns, dict):
+                col_details = columns[col]
+                name = col
+            else:
+                raise RuntimeError("Error parsing the schema file")
+
+            for k, v in col_details.items():
+                if k == "shape":
+                    shape = v
+                elif k == "type":
+                    data_type = v
+                elif k in ("t_impl", "rank"):
+                    pass
+                else:
+                    raise RuntimeError("Unknown field %s" % k)
+
+            if name is None:
+                raise RuntimeError("Column's name field is missing.")
+            if data_type is None:
+                raise RuntimeError("Column's type field is missing.")
+            self.add_column(name, data_type, shape)
 
     def from_json(self, json_obj):
         """