!1366 InvertPermutation support 1-d tensor input

Merge pull request !1366 from jiangjinsheng/issue_invert

mindspore/ops/operations/array_ops.py

@@ -905,9 +905,11 @@ class InvertPermutation(PrimitiveWithInfer):
         values can not be negative.
 
     Inputs:
-        - **input_x** (tuple[int]) - The input tuple is constructed by multiple
+        - **input_x** (Union(tuple[int], Tensor[int])) - The input tuple is constructed by multiple
           integers, i.e., :math:`(y_1, y_2, ..., y_S)` representing the indices.
           The values must include 0. There can be no duplicate values or negative values.
+          If the input is Tensor, it must be 1-d and the dtype is int.
+
 
     Outputs:
         tuple[int]. the lenth is same as input.
@@ -926,7 +928,11 @@ class InvertPermutation(PrimitiveWithInfer):
     def __infer__(self, x):
         x_shp = x['shape']
         x_value = x['value']
-        validator.check_value_type("shape", x_shp, [tuple], self.name)
+        validator.check_value_type("shape", x_shp, [tuple, list], self.name)
+        if mstype.issubclass_(x['dtype'], mstype.tensor):
+            validator.check('x dimension', len(x_shp), '', 1, Rel.EQ, self.name)
+            validator.check_type_same({'x dtype': x['dtype']}, mstype.int_type, self.name)
+            x_value = [int(i) for i in x_value.asnumpy()]
         z = [x_value[i] for i in range(len(x_value))]
         z.sort()