Add prim name to error message for _grad_ops.py

mindspore/_checkparam.py

@@ -206,8 +206,8 @@ class Validator:
         def _check_tensor_type(arg):
             arg_key, arg_val = arg
             elem_type = arg_val
-            type_names = []
             if not elem_type in valid_values:
+                type_names = []
                 for t in valid_values:
                     type_names.append(str(t))
                 types_info = '[' + ", ".join(type_names) + ']'

mindspore/ops/_utils/utils.py

@@ -15,7 +15,7 @@
 
 """utils for operator"""
 
-from ..._checkparam import ParamValidator as validator
+from ..._checkparam import Validator as validator
 from ..._checkparam import Rel
 from ...common import dtype as mstype
 
@@ -62,25 +62,25 @@ def _get_broadcast_shape(x_shape, y_shape, prim_name):
     return broadcast_shape
 
 
-def _get_concat_offset(x_shp, x_type, axis):
+def _get_concat_offset(x_shp, x_type, axis, prim_name):
     """for concat and concatoffset check args and compute offset"""
-    validator.check_type("shape", x_shp, [tuple])
-    validator.check_integer("len of input_x shape", len(x_shp), 0, Rel.GT)
-    validator.check_subclass("shape0", x_type[0], mstype.tensor)
-    validator.check_integer("len of input_x0 shape", len(x_shp[0]), 0, Rel.GT)
+    validator.check_value_type("shape", x_shp, [tuple], prim_name)
+    validator.check_integer("input_x rank", len(x_shp), 0, Rel.GT, prim_name)
+    validator.check_subclass("shape0", x_type[0], mstype.tensor, prim_name)
+    validator.check_integer("len of x_shp[0]", len(x_shp[0]), 0, Rel.GT, prim_name)
     rank_base = len(x_shp[0])
-    validator.check_int_range('axis', axis, -rank_base - 1, rank_base, Rel.INC_BOTH)
+    validator.check_int_range('axis', axis, -rank_base - 1, rank_base, Rel.INC_BOTH, prim_name)
     if axis < 0:
         axis = axis + rank_base
     all_shp = x_shp[0][axis]
     offset = [0,]
     for i in range(1, len(x_shp)):
         v = x_shp[i]
-        validator.check('len of x_shp[%d]' % i, len(v), 'len of base', len(x_shp[0]))
-        validator.check('x_type[%d]' % i, x_type[i], 'base', x_type[0])
+        validator.check('len of x_shp[%d]' % i, len(v), 'len of x_shp[0]', len(x_shp[0]), Rel.EQ, prim_name)
+        validator.check('x_type[%d]' % i, x_type[i], 'x_type[0]', x_type[0], Rel.EQ, prim_name)
         for j in range(rank_base):
             if j != axis and v[j] != x_shp[0][j]:
-                raise ValueError("Concat evaluator element %d shape in input can not concat with first element" % i)
+                raise ValueError(f"For \'{prim_name}\' element {i} shape in input can not concat with first element")
         offset.append(all_shp)
         all_shp += v[axis]
     return offset, all_shp, axis

mindspore/ops/operations/array_ops.py

@@ -1316,7 +1316,7 @@ class Concat(PrimitiveWithInfer):
         axis = self.axis
         x_shp = input_x['shape']
         x_type = input_x['dtype']
-        _, all_shp, _ = _get_concat_offset(x_shp, x_type, axis)
+        _, all_shp, _ = _get_concat_offset(x_shp, x_type, axis, self.name)
         self.add_prim_attr('T', x_type[0].element_type())
         self.add_prim_attr('inputNums', len(x_shp))
         ret_shp = x_shp[0].copy()