Update `paddle.add` (#25910)

* Update `paddle.add`

remove `alpha`
update doc sample code
remove `:alias` etc

* Remove `imperative` reference from docstring

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

@@ -397,7 +397,7 @@ class TestAddOp(unittest.TestCase):
             y_1 = paddle.add(x, y, name='add_res')
             self.assertEqual(('add_res' in y_1.name), True)
 
-    def test_alpha(self):
+    def test_declarative(self):
         with fluid.program_guard(fluid.Program()):
 
             def gen_data():
@@ -408,33 +408,12 @@ class TestAddOp(unittest.TestCase):
 
             x = fluid.data(name="x", shape=[3], dtype='float32')
             y = fluid.data(name="y", shape=[3], dtype='float32')
-            z = paddle.add(x, y, alpha=10)
+            z = paddle.add(x, y)
 
             place = fluid.CPUPlace()
             exe = fluid.Executor(place)
             z_value = exe.run(feed=gen_data(), fetch_list=[z.name])
-            z_expected = np.array([12., 53., 24.])
-            self.assertEqual((z_value == z_expected).all(), True)
-
-    def test_alpha_gpu(self):
-        if not fluid.core.is_compiled_with_cuda():
-            return
-        with fluid.program_guard(fluid.Program()):
-
-            def gen_data():
-                return {
-                    "x": np.array([2, 3, 4]).astype('float32'),
-                    "y": np.array([1, 5, 2]).astype('float32')
-                }
-
-            x = fluid.data(name="x", shape=[3], dtype='float32')
-            y = fluid.data(name="y", shape=[3], dtype='float32')
-            z = paddle.add(x, y, alpha=-0.5)
-
-            place = fluid.CUDAPlace(0)
-            exe = fluid.Executor(place)
-            z_value = exe.run(feed=gen_data(), fetch_list=[z.name])
-            z_expected = np.array([1.5, 0.5, 3.])
+            z_expected = np.array([3., 8., 6.])
             self.assertEqual((z_value == z_expected).all(), True)
 
     def test_dygraph(self):
@@ -443,9 +422,9 @@ class TestAddOp(unittest.TestCase):
             np_y = np.array([1, 5, 2]).astype('float64')
             x = fluid.dygraph.to_variable(np_x)
             y = fluid.dygraph.to_variable(np_y)
-            z = paddle.add(x, y, alpha=-0.5)
+            z = paddle.add(x, y)
             np_z = z.numpy()
-            z_expected = np.array([1.5, 0.5, 3.])
+            z_expected = np.array([3., 8., 6.])
             self.assertEqual((np_z == z_expected).all(), True)
 
 

python/paddle/tensor/math.py

@@ -233,134 +233,30 @@ def _elementwise_op(helper):
     return helper.append_activation(out)
 
 
-def add(x, y, alpha=1, name=None):
+def add(x, y, name=None):
     """
 Examples:
 
-    .. code-block:: python
-
-        import paddle
-        import paddle.fluid as fluid
-        import numpy as np
-
-        def gen_data():
-            return {
-                "x": np.array([2, 3, 4]).astype('float32'),
-                "y": np.array([1, 5, 2]).astype('float32')
-            }
-
-        x = fluid.data(name="x", shape=[3], dtype='float32')
-        y = fluid.data(name="y", shape=[3], dtype='float32')
-        z1 = paddle.add(x, y)
-        z2 = paddle.add(x, y, alpha=10)
-        # z = x + y
-
-        place = fluid.CPUPlace()
-        exe = fluid.Executor(place)
-        z_value = exe.run(feed=gen_data(),
-                            fetch_list=[z1.name, z2.name])
-
-        print(z_value[0]) # [3., 8., 6.]
-        print(z_value[1]) # [12. 53. 24.]
-
-
-    .. code-block:: python
-
-        import paddle
-        import paddle.fluid as fluid
-        import numpy as np
-
-        def gen_data():
-            return {
-                "x": np.ones((2, 3, 4, 5)).astype('float32'),
-                "y": np.zeros((4, 5)).astype('float32')
-            }
-
-        x = fluid.data(name="x", shape=[2, 3, 4, 5], dtype='float32')
-        y = fluid.data(name="y", shape=[4, 5], dtype='float32')
-        z = paddle.add(x, y, name='z')
-        # z = x + y
-
-        place = fluid.CPUPlace()
-        exe = fluid.Executor(place)
-
-        z_value = exe.run(feed=gen_data(),
-                            fetch_list=[z.name])
-
-        print(z_value[0])
-        print(z_value[0].shape) # z.shape=[2,3,4,5]
-
-
-    ..  code-block:: python
-
-        import paddle
-        import paddle.fluid as fluid
-        import numpy as np
-
-        def gen_data():
-            return {
-                "x": np.random.randint(1, 5, size=[2, 3, 4, 5]).astype('float32'),
-                "y": np.random.randint(1, 5, size=[5]).astype('float32')
-            }
-
-        x = fluid.data(name="x", shape=[2,3,4,5], dtype='float32')
-        y = fluid.data(name="y", shape=[5], dtype='float32')
-        z = paddle.add(x, y)
-        # z = x / y
-
-        place = fluid.CPUPlace()
-        exe = fluid.Executor(place)
-
-        z_value = exe.run(feed=gen_data(),
-                            fetch_list=[z.name])
-        print(z_value[0])
-        print(z_value[0].shape) # z.shape=[2,3,4,5]
-
-
     ..  code-block:: python
 
         import paddle
-        import paddle.fluid as fluid
         import numpy as np
 
-        x = fluid.data(name="x", shape=[3], dtype="float32")
-        y = fluid.data(name='y', shape=[3], dtype='float32')
+        paddle.disable_static()
+        np_x = np.array([2, 3, 4]).astype('float64')
+        np_y = np.array([1, 5, 2]).astype('float64')
+        x = paddle.to_variable(np_x)
+        y = paddle.to_variable(np_y)
         z = paddle.add(x, y)
-
-        place = fluid.CPUPlace()
-        exe = fluid.Executor(place)
-        data1 = np.array([2, 3, 4], dtype='float32')
-        data2 = np.array([1, 5, 2], dtype='float32')
-        z_value = exe.run(feed={'x': data1,
-                                'y': data2},
-                                fetch_list=[z])
-        print(z_value[0]) # [3. 8. 6.]
-
-
-    ..  code-block:: python
-
-        import paddle
-        import paddle.fluid as fluid
-        import numpy as np
-
-        with fluid.dygraph.guard():
-            np_x = np.array([2, 3, 4]).astype('float64')
-            np_y = np.array([1, 5, 2]).astype('float64')
-            x = fluid.dygraph.to_variable(np_x)
-            y = fluid.dygraph.to_variable(np_y)
-            z = paddle.add(x, y, alpha=-0.5)
-            np_z = z.numpy()
-            print(np_z)  # [1.5, 0.5, 3. ]
+        np_z = z.numpy()
+        print(np_z)  # [3., 8., 6. ]
 
     """
     op_type = 'elementwise_add'
     axis = -1
-    act = None
-    if alpha != 1:
-        y = scale(y, scale=alpha)
     if in_dygraph_mode():
         return _elementwise_op_in_dygraph(
-            x, y, axis=axis, act=act, op_name=op_type)
+            x, y, axis=axis, op_name=op_type)
 
     return _elementwise_op(LayerHelper(op_type, **locals()))
 
@@ -621,30 +517,21 @@ for func in [
 ]:
     proto_dict = {'add': 'elementwise_add', 'div': 'elementwise_div', 'maximum': 'elementwise_max', 'minimum': 'elementwise_min', 'multiply': 'elementwise_mul'}
     op_proto = OpProtoHolder.instance().get_op_proto(proto_dict[func.__name__])
-    if func.__name__ in ['add']:
-        alias_main = ':alias_main: paddle.%(func)s' % {'func': func.__name__}
-        alias = ':alias: paddle.%(func)s, paddle.tensor.%(func)s, paddle.tensor.math.%(func)s' % {'func': func.__name__}
-
-        additional_args_lines = [
-            "alpha (int|float, optional): The alpha factor of the input. Default is 1. If alpha is not 1, the equation becomes Out = X + alpha * Y.",
-            "name (string, optional): Name of the output. \
-            Default is None. It's used to print debug info for developers. Details: \
-            :ref:`api_guide_Name` "
-        ]
-    else:
-        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__ = alias_main + """\n""" + alias + """\n""" + _generate_doc_string_(
+    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(input, dim=None, dtype=None, keep_dim=False, name=None):
     """
 	:alias_main: paddle.sum