reduce compile time of amax and amin (#38534)

paddle/fluid/operators/reduce_ops/reduce_min_max_op.h

@@ -125,13 +125,14 @@ struct AMaxOrAMinGradFunctor {
     HANDLE_AXIS_DIM(3, 2);
     HANDLE_AXIS_DIM(4, 2);
     HANDLE_AXIS_DIM(4, 3);
-    HANDLE_AXIS_DIM(5, 2);
-    HANDLE_AXIS_DIM(5, 3);
-    HANDLE_AXIS_DIM(5, 4);
-    HANDLE_AXIS_DIM(6, 2);
-    HANDLE_AXIS_DIM(6, 3);
-    HANDLE_AXIS_DIM(6, 4);
-    HANDLE_AXIS_DIM(6, 5);
+    // comments for accelerating compiling temporarily.
+    // HANDLE_AXIS_DIM(5, 2);
+    // HANDLE_AXIS_DIM(5, 3);
+    // HANDLE_AXIS_DIM(5, 4);
+    // HANDLE_AXIS_DIM(6, 2);
+    // HANDLE_AXIS_DIM(6, 3);
+    // HANDLE_AXIS_DIM(6, 4);
+    // HANDLE_AXIS_DIM(6, 5);
   }
 };
 

python/paddle/tensor/math.py

@@ -1775,7 +1775,8 @@ def amax(x, axis=None, keepdim=False, name=None):
         while max propagates gradient to all of them.
 
     Args:
-        x(Tensor): A tensor, the data type is float32, float64, int32, int64.
+        x(Tensor): A tensor, the data type is float32, float64, int32, int64,
+            the dimension is no more than 4.
         axis(int|list|tuple, optional): The axis along which the maximum is computed.
             If :attr:`None`, compute the maximum over all elements of
             `x` and return a Tensor with a single element,
@@ -1887,7 +1888,8 @@ def amin(x, axis=None, keepdim=False, name=None):
         while min propagates gradient to all of them.
 
     Args:
-        x(Tensor): A tensor, the data type is float32, float64, int32, int64.
+        x(Tensor): A tensor, the data type is float32, float64, int32, int64, 
+            the dimension is no more than 4.
         axis(int|list|tuple, optional): The axis along which the minimum is computed.
             If :attr:`None`, compute the minimum over all elements of
             `x` and return a Tensor with a single element,