!39170 Update argmin with value tensor api name

Merge pull request !39170 from ZPaC/update-argmin-with-value-name

mindspore/python/mindspore/_extends/parse/standard_method.py

@@ -540,7 +540,7 @@ def argmax(x, axis=None):
     return P.Argmax(axis)(x)
 
 
-def arg_min_with_value(x, axis=0, keep_dims=False):
+def argmin_with_value(x, axis=0, keep_dims=False):
     """
     Calculates the minimum value with corresponding index, and returns indices and values.
 

mindspore/python/mindspore/common/tensor.py

@@ -2180,7 +2180,7 @@ class Tensor(Tensor_):
         # P.Argmin is currently not supported
         return tensor_operator_registry.get('argmax')(axis)(tensor_operator_registry.get('__neg__')(a))
 
-    def arg_min_with_value(self, axis=0, keep_dims=False):
+    def argmin_with_value(self, axis=0, keep_dims=False):
         """
         Returns the minimum value with corresponding index.
 
@@ -2215,15 +2215,15 @@ class Tensor(Tensor_):
 
         Examples:
             >>> x = Tensor(np.array([0.0, 0.4, 0.6, 0.7, 0.1]), mindspore.float32)
-            >>> output = x.arg_min_with_value()
+            >>> output = x.argmin_with_value()
             >>> print(output)
             0 0.0
-            >>> output = x.arg_min_with_value(keep_dims=True)
+            >>> output = x.argmin_with_value(keep_dims=True)
             >>> print(output)
             [0] [0.0]
         """
         self._init_check()
-        return tensor_operator_registry.get('arg_min_with_value')(self, axis, keep_dims)
+        return tensor_operator_registry.get('argmin_with_value')(self, axis, keep_dims)
 
     def cumsum(self, axis=None, dtype=None):
         """

mindspore/python/mindspore/ops/functional.py

@@ -890,7 +890,7 @@ tensor_operator_registry.register('norm', norm)
 tensor_operator_registry.register('renorm', renorm)
 tensor_operator_registry.register('adaptive_max_pool2d', AdaptiveMaxPool2D)
 tensor_operator_registry.register('coalesce', coalesce)
-tensor_operator_registry.register('arg_min_with_value', min)
+tensor_operator_registry.register('argmin_with_value', min)
 tensor_operator_registry.register('coo_add', sparse_add)
 tensor_operator_registry.register('top_k', P.TopK)
 __all__ = [name for name in dir() if name[0] != "_"]

mindspore/python/mindspore/ops/operations/array_ops.py

@@ -2161,7 +2161,7 @@ class ArgMinWithValue(Primitive):
         - If there are multiple minimum values, the index of the first minimum value is used.
         - The value range of "axis" is [-dims, dims - 1]. "dims" is the dimension length of "x".
 
-    Also see: func: `mindspore.ops.arg_min_with_value`.
+    Also see: func: `mindspore.ops.min`.
 
     Args:
         axis (int): The dimension to reduce. Default: 0.

tests/st/ops/gpu/test_argminwithvalue_op.py

@@ -109,7 +109,7 @@ def argminwithvalue_tensor(context_mode, np_type):
                          [67., 8., 9.],
                          [130., 24., 15.],
                          [0.3, -0.4, -15.]]).astype(np_type))
-    return x.arg_min_with_value(axis=-1)
+    return x.argmin_with_value(axis=-1)
 
 
 @pytest.mark.level1
@@ -184,7 +184,7 @@ def test_argminwithvalue_functional():
 @pytest.mark.env_onecard
 def test_argminwithvalue_tensor():
     """
-    Feature: support tensor's arg_min_with_value op.
+    Feature: support tensor's argmin_with_value op.
     Description: test the op using tensor.
     Expectation: expect correct result.
     """
@@ -210,7 +210,7 @@ def test_argminwithvalue_tensor():
 @pytest.mark.env_onecard
 def test_argminwithvalue_dynamic_shape():
     """
-    Feature: support arg_min_with_value op with dynamic shape.
+    Feature: support argmin_with_value op with dynamic shape.
     Description: test the op with dynamic shape
     Expectation: expect correct result.
     """