fix the document for the api multiply (#45304)

* update the document for the api multiply

* update the document for the api multiply; test=document_fix

* update the document for the api multiply; test=document_fix

* update the document for the api multiply; test=document_fix

* note;test=document_fix
Co-authored-by: NLigoml <39876205+Ligoml@users.noreply.github.com>

python/paddle/tensor/math.py

@@ -342,8 +342,8 @@ def pow(x, y, name=None):
     .. math::
         out = x^{y} 
 
-    **Note**:
-    ``paddle.pow`` supports broadcasting. If you want know more about broadcasting, please refer to :ref:`user_guide_broadcasting` .
+    Note:
+        ``paddle.pow`` supports broadcasting. If you want know more about broadcasting, please refer to :ref:`user_guide_broadcasting` .
 
 
     Args:
@@ -669,8 +669,8 @@ def divide(x, y, name=None):
     .. math::
         out = x / y
 
-    **Note**:
-    ``paddle.divide`` supports broadcasting. If you want know more about broadcasting, please refer to :ref:`user_guide_broadcasting` .
+    Note:
+        ``paddle.divide`` supports broadcasting. If you want know more about broadcasting, please refer to :ref:`user_guide_broadcasting` .
 
     Args:
         x (Tensor): the input tensor, it's data type should be float32, float64, int32, int64.
@@ -712,8 +712,8 @@ def floor_divide(x, y, name=None):
     .. math::
         out = x // y
 
-    **Note**:
-    ``paddle.floor_divide`` supports broadcasting. If you want know more about broadcasting, please refer to :ref:`user_guide_broadcasting` .
+    Note:
+        ``paddle.floor_divide`` supports broadcasting. If you want know more about broadcasting, please refer to :ref:`user_guide_broadcasting` .
 
     Args:
         x (Tensor): the input tensor, it's data type should be int32, int64.
@@ -754,8 +754,8 @@ def remainder(x, y, name=None):
 
         out = x \% y
 
-    **Note**:
-    ``paddle.remainder`` supports broadcasting. If you want know more about broadcasting, please refer to :ref:`user_guide_broadcasting` .
+    Note:
+        ``paddle.remainder`` supports broadcasting. If you want know more about broadcasting, please refer to :ref:`user_guide_broadcasting` .
 
     Args:
         x (Tensor): the input tensor, it's data type should be float32, float64, int32, int64.
@@ -799,8 +799,8 @@ def multiply(x, y, name=None):
     .. math::
         out = x * y
 
-    **Note**:
-    ``paddle.multiply`` supports broadcasting. If you would like to know more about broadcasting, please refer to :ref:`user_guide_broadcasting` .
+    Note:
+        ``paddle.multiply`` supports broadcasting. If you would like to know more about broadcasting, please refer to :ref:`user_guide_broadcasting`.
 
     Args:
         x (Tensor): the input tensor, its data type should be one of float32, float64, int32, int64, bool.
@@ -852,8 +852,8 @@ def maximum(x, y, name=None):
     .. math::
         out = max(x, y)
 
-    **Note**:
-    ``paddle.maximum`` supports broadcasting. If you want know more about broadcasting, please refer to :ref:`user_guide_broadcasting` .
+    Note:
+        ``paddle.maximum`` supports broadcasting. If you want know more about broadcasting, please refer to :ref:`user_guide_broadcasting` .
 
     Args:
         x (Tensor): the input tensor, it's data type should be float32, float64, int32, int64.
@@ -913,8 +913,8 @@ def minimum(x, y, name=None):
     .. math::
         out = min(x, y)
 
-    **Note**:
-    ``paddle.minimum`` supports broadcasting. If you want know more about broadcasting, please refer to :ref:`user_guide_broadcasting` .
+    Note:
+        ``paddle.minimum`` supports broadcasting. If you want know more about broadcasting, please refer to :ref:`user_guide_broadcasting` .
 
     Args:
         x (Tensor): the input tensor, it's data type should be float32, float64, int32, int64.
@@ -976,8 +976,8 @@ def fmax(x, y, name=None):
     .. math::
         out = fmax(x, y)
 
-    **Note**:
-    ``paddle.fmax`` supports broadcasting. If you want know more about broadcasting, please refer to :ref:`user_guide_broadcasting` .
+    Note:
+        ``paddle.fmax`` supports broadcasting. If you want know more about broadcasting, please refer to :ref:`user_guide_broadcasting` .
 
     Args:
         x (Tensor): the input tensor, it's data type should be float32, float64, int32, int64.
@@ -1039,8 +1039,8 @@ def fmin(x, y, name=None):
     .. math::
         out = fmin(x, y)
 
-    **Note**:
-    ``paddle.fmin`` supports broadcasting. If you want know more about broadcasting, please refer to :ref:`user_guide_broadcasting` .
+    Note:
+        ``paddle.fmin`` supports broadcasting. If you want know more about broadcasting, please refer to :ref:`user_guide_broadcasting` .
 
     Args:
         x (Tensor): the input tensor, it's data type should be float32, float64, int32, int64.
@@ -1093,25 +1093,6 @@ def fmin(x, y, name=None):
             x, y, axis=axis, act=act, op_name=op_type)
     return _elementwise_op(LayerHelper(op_type, **locals()))
 
-for func in [
-        multiply
-]:
-    proto_dict = {'multiply': 'elementwise_mul'}
-    op_proto = OpProtoHolder.instance().get_op_proto(proto_dict[func.__name__])
-
-    additional_args_lines = [
-        "name (string, optional): Name of the output. \
-        Default is None. It's used to print debug info for developers. Details: \
-        :ref:`api_guide_Name` "
-    ]
-
-    func.__doc__ = _generate_doc_string_(
-        op_proto,
-        additional_args_lines=additional_args_lines,
-        skip_attrs_set={"x_data_format", "y_data_format", "axis",
-            "use_quantizer", "mkldnn_data_type", "Scale_x", "Scale_y", "Scale_out"
-        }) + """\n""" + str(func.__doc__)
-
 
 def sum(x, axis=None, dtype=None, keepdim=False, name=None):
     """
@@ -3046,8 +3027,8 @@ def cumsum(x, axis=None, dtype=None, name=None):
     """
     The cumulative sum of the elements along a given axis. 
     
-    **Note**:
-    The first element of the result is the same as the first element of the input. 
+    Note:
+        The first element of the result is the same as the first element of the input. 
 
     Args:
         x (Tensor): The input tensor needed to be cumsumed.
@@ -3185,8 +3166,8 @@ def cumprod(x, dim=None, dtype=None, name=None):
     """
     Compute the cumulative product of the input tensor x along a given dimension dim.
 
-    **Note**:
-    The first element of the result is the same as the first element of the input.
+    Note:
+        The first element of the result is the same as the first element of the input.
 
     Args:
         x (Tensor): the input tensor need to be cumproded.
@@ -3521,7 +3502,7 @@ def tanh_(x, name=None):
 
 def increment(x, value=1.0, name=None):
     """
-    The OP is usually used for control flow to increment the data of :attr:`x` by an amount :attr:`value`.
+    The API is usually used for control flow to increment the data of :attr:`x` by an amount :attr:`value`.
     Notice that the number of elements in :attr:`x` must be equal to 1.
 
     Args:
@@ -4669,7 +4650,7 @@ def heaviside(x, y, name=None):
                 \end{array}
             \\right.
 
-    Notes:
+    Note:
         ``paddle.heaviside`` supports broadcasting. If you want know more about broadcasting, please refer to :ref:`user_guide_broadcasting`.
 
     Args: