add parameter check for Class Schema

mindspore/dataset/engine/datasets.py

@@ -38,7 +38,7 @@ from .iterators import DictIterator, TupleIterator
 from .validators import check, check_batch, check_shuffle, check_map, check_repeat, check_zip, check_rename, \
     check_project, check_imagefolderdatasetv2, check_mnist_cifar_dataset, check_manifestdataset, \
     check_tfrecorddataset, check_vocdataset, check_celebadataset, check_minddataset, check_generatordataset, \
-    check_zip_dataset
+    check_zip_dataset, check_add_column
 from ..core.datatypes import mstype_to_detype, mstypelist_to_detypelist
 
 try:
@@ -2334,13 +2334,20 @@ class Schema:
             self.dataset_type = ''
             self.num_rows = 0
         else:
+            if not os.path.isfile(schema_file) or not os.access(schema_file, os.R_OK):
+                raise ValueError("The file %s does not exist or permission denied!" % schema_file)
             try:
                 with open(schema_file, 'r') as load_f:
                     json_obj = json.load(load_f)
-                    self.from_json(json_obj)
             except json.decoder.JSONDecodeError:
-                raise RuntimeError("Schema file failed to load")
+                raise RuntimeError("Schema file failed to load.")
+            except UnicodeDecodeError:
+                raise RuntimeError("Schema file failed to decode.")
+            except Exception:
+                raise RuntimeError("Schema file failed to open.")
+            self.from_json(json_obj)
 
+    @check_add_column
     def add_column(self, name, de_type, shape=None):
         """
         Add new column to the schema.
@@ -2359,10 +2366,8 @@ class Schema:
         if isinstance(de_type, typing.Type):
             de_type = mstype_to_detype(de_type)
             new_column["type"] = str(de_type)
-        elif isinstance(de_type, str):
-            new_column["type"] = str(DataType(de_type))
         else:
-            raise ValueError("Unknown column type")
+            new_column["type"] = str(DataType(de_type))
 
         if shape is not None:
             new_column["shape"] = shape
@@ -2391,7 +2396,7 @@ class Schema:
         Parse the columns and add it to self.
 
         Args:
-            columns (list[str]): names of columns.
+            columns (dict or list[str]): names of columns.
 
         Raises:
             RuntimeError: If failed to parse schema file.
@@ -2399,6 +2404,8 @@ class Schema:
             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 = []
         for col in columns:
             name = None
@@ -2443,6 +2450,8 @@ class Schema:
             RuntimeError: if dataset type is missing in the object.
             RuntimeError: if columns are missing in the object.
         """
+        if not isinstance(json_obj, dict) or json_obj is None:
+            raise ValueError("Expected non-empty dict.")
         for k, v in json_obj.items():
             if k == "datasetType":
                 self.dataset_type = v

mindspore/dataset/engine/validators.py

@@ -19,10 +19,15 @@ import inspect as ins
 import os
 from functools import wraps
 from multiprocessing import cpu_count
+from mindspore._c_expression import typing
 from . import samplers
 from . import datasets
 
 INT32_MAX = 2147483647
+valid_detype = [
+    "bool", "int8", "int16", "int32", "int64", "uint8", "uint16",
+    "uint32", "uint64", "float16", "float32", "float64"
+]
 
 
 def check(method):
@@ -188,6 +193,12 @@ def check(method):
     return wrapper
 
 
+def check_valid_detype(type_):
+    if type_ not in valid_detype:
+        raise ValueError("Unknown column type")
+    return True
+
+
 def check_filename(path):
     """
     check the filename in the path
@@ -743,3 +754,42 @@ def check_project(method):
         return method(*args, **kwargs)
 
     return new_method
+
+
+def check_shape(shape, name):
+    if isinstance(shape, list):
+        for element in shape:
+            if not isinstance(element, int):
+                raise TypeError(
+                    "Each element in {0} should be of type int. Got {1}.".format(name, type(element)))
+    else:
+        raise TypeError("Expected int list.")
+
+
+def check_add_column(method):
+    """check the input arguments of add_column."""
+    @wraps(method)
+    def new_method(*args, **kwargs):
+        param_dict = make_param_dict(method, args, kwargs)
+
+        # check name; required argument
+        name = param_dict.get("name")
+        if not isinstance(name, str) or not name:
+            raise TypeError("Expected non-empty string.")
+
+        # check type; required argument
+        de_type = param_dict.get("de_type")
+        if de_type is not None:
+            if not isinstance(de_type, typing.Type) and not check_valid_detype(de_type):
+                raise ValueError("Unknown column type.")
+        else:
+            raise TypeError("Expected non-empty string.")
+
+        # check shape
+        shape = param_dict.get("shape")
+        if shape is not None:
+            check_shape(shape, "shape")
+
+        return method(*args, **kwargs)
+
+    return new_method