fix conflict

paddle/phi/api/yaml/backward.yaml

@@ -411,7 +411,7 @@
   kernel :
     func : conv3d_transpose_grad
     data_type : x
-    
+
 - backward_op : copysign_grad
   forward : copysign (Tensor x, Tensor y) -> Tensor(out)
   args : (Tensor x, Tensor y, Tensor out_grad)

python/paddle/__init__.py

@@ -414,6 +414,8 @@
     polygamma_,
     copysign,
     copysign_,
+    hypot,
+    hypot_,
 )
 
 from .tensor.random import (
@@ -914,4 +916,10 @@
     'polygamma_',
     'copysign',
     'copysign_',
+    'masked_fill',
+    'masked_fill_',
+    'hypot',
+    'hypot_',
+    'index_fill',
+    "index_fill_",
 ]

python/paddle/tensor/__init__.py

@@ -334,6 +334,10 @@
 from .math import polygamma_  # noqa: F401
 from .math import copysign  # noqa: F401
 from .math import copysign_  # noqa: F401
+from .math import renorm  # noqa: F401
+from .math import renorm_  # noqa: F401
+from .math import hypot  # noqa: F401
+from .math import hypot_  # noqa: F401
 
 from .random import multinomial  # noqa: F401
 from .random import standard_normal  # noqa: F401
@@ -729,6 +733,8 @@
     'normal_',
     'copysign',
     'copysign_',
+    'index_fill',
+    'index_fill_',
 ]
 
 # this list used in math_op_patch.py for magic_method bind

python/paddle/tensor/math.py

@@ -7024,3 +7024,56 @@ def copysign_(x, y):
     y = paddle.broadcast_to(y, out_shape)
 
     return _C_ops.copysign_(x, y)
+
+
+def hypot(x, y, name=None):
+    """
+    Calculate the length of the hypotenuse of a right-angle triangle. The equation is:
+
+    .. math::
+        out = {\\sqrt{x^2 + y^2}}
+
+    Args:
+        x (Tensor): The input Tensor, the data type is float32, float64, int32 or int64.
+        y (Tensor): The input Tensor, the data type is float32, float64, int32 or int64.
+        name (str, optional): Name for the operation (optional, default is None).For more information, please refer to :ref:`api_guide_Name`.
+
+    Returns:
+        out (Tensor): An N-D Tensor. If x, y have different shapes and are "broadcastable", the resulting tensor shape is the shape of x and y after broadcasting. If x, y have the same shape, its shape is the same as x and y. And the data type is float32 or float64.
+
+    Examples:
+
+        .. code-block:: python
+
+            >>> import paddle
+
+            >>> x = paddle.to_tensor([3], dtype='float32')
+            >>> y = paddle.to_tensor([4], dtype='float32')
+            >>> res = paddle.hypot(x, y)
+            >>> print(res)
+            Tensor(shape=[1], dtype=float32, place=Place(cpu), stop_gradient=True,
+            [5.])
+
+    """
+    if not isinstance(x, (paddle.Tensor, Variable)):
+        raise TypeError(f"x must be tensor type, but got {type(x)}")
+    if not isinstance(y, (paddle.Tensor, Variable)):
+        raise TypeError(f"y must be tensor type, but got {type(y)}")
+
+    out = (paddle.pow(x, 2) + paddle.pow(y, 2)).sqrt()
+    return out
+
+
+@inplace_apis_in_dygraph_only
+def hypot_(x, y, name=None):
+    r"""
+    Inplace version of ``hypot`` API, the output Tensor will be inplaced with input ``x``.
+    Please refer to :ref:`api_paddle_hypot`.
+    """
+    if not isinstance(x, (paddle.Tensor, Variable)):
+        raise TypeError(f"x must be tensor type, but got {type(x)}")
+    if not isinstance(y, (paddle.Tensor, Variable)):
+        raise TypeError(f"y must be tensor type, but got {type(y)}")
+
+    out = x.pow_(2).add_(y.pow(2)).sqrt_()
+    return out