udpate the dtype check for the argmin, argmax

remove the bug for the checking the type of dtype

python/paddle/fluid/tests/unittests/test_arg_min_max_v2_op.py

@@ -325,16 +325,16 @@ class TestArgMinMaxOpError(unittest.TestCase):
             def test_argmax_dtype_type():
                 data = paddle.static.data(
                     name="test_argmax", shape=[10], dtype="float32")
-                output = paddle.argmax(x=data, dtype=1)
+                output = paddle.argmax(x=data, dtype=None)
 
-            self.assertRaises(TypeError, test_argmax_dtype_type)
+            self.assertRaises(ValueError, test_argmax_dtype_type)
 
             def test_argmin_dtype_type():
                 data = paddle.static.data(
                     name="test_argmin", shape=[10], dtype="float32")
-                output = paddle.argmin(x=data, dtype=1)
+                output = paddle.argmin(x=data, dtype=None)
 
-            self.assertRaises(TypeError, test_argmin_dtype_type)
+            self.assertRaises(ValueError, test_argmin_dtype_type)
 
 
 if __name__ == '__main__':

python/paddle/tensor/search.py

@@ -167,10 +167,10 @@ def argmax(x, axis=None, keepdim=False, dtype="int64", name=None):
             "The type of 'axis'  must be int or None in argmax, but received %s."
             % (type(axis)))
 
-    if not (isinstance(dtype, str) or isinstance(dtype, np.dtype)):
-        raise TypeError(
-            "the type of 'dtype' in argmax must be str or np.dtype, but received {}".
-            format(type(dtype)))
+    if dtype is None:
+        raise ValueError(
+            "the value of 'dtype' in argmax could not be None, but received None"
+        )
 
     var_dtype = convert_np_dtype_to_dtype_(dtype)
     check_dtype(var_dtype, 'dtype', ['int32', 'int64'], 'argmin')
@@ -245,10 +245,10 @@ def argmin(x, axis=None, keepdim=False, dtype="int64", name=None):
             "The type of 'axis'  must be int or None in argmin, but received %s."
             % (type(axis)))
 
-    if not (isinstance(dtype, str) or isinstance(dtype, np.dtype)):
-        raise TypeError(
-            "the type of 'dtype' in argmin must be str or np.dtype, but received {}".
-            format(dtype(dtype)))
+    if dtype is None:
+        raise ValueError(
+            "the value of 'dtype' in argmin could not be None, but received None"
+        )
 
     var_dtype = convert_np_dtype_to_dtype_(dtype)
     check_dtype(var_dtype, 'dtype', ['int32', 'int64'], 'argmin')