# Source code for mars.tensor.arithmetic.copysign

```
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright 1999-2021 Alibaba Group Holding Ltd.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import numpy as np
from ... import opcodes as OperandDef
from ..utils import infer_dtype
from .core import TensorBinOp
from .utils import arithmetic_operand
@arithmetic_operand(sparse_mode="always_false")
class TensorCopysign(TensorBinOp):
_op_type_ = OperandDef.COPYSIGN
_func_name = "copysign"
[docs]@infer_dtype(np.copysign)
def copysign(x1, x2, out=None, where=None, **kwargs):
"""
Change the sign of x1 to that of x2, element-wise.
If both arguments are arrays or sequences, they have to be of the same
length. If `x2` is a scalar, its sign will be copied to all elements of
`x1`.
Parameters
----------
x1 : array_like
Values to change the sign of.
x2 : array_like
The sign of `x2` is copied to `x1`.
out : Tensor, None, or tuple of Tensor and None, optional
A location into which the result is stored. If provided, it must have
a shape that the inputs broadcast to. If not provided or `None`,
a freshly-allocated tensor is returned. A tuple (possible only as a
keyword argument) must have length equal to the number of outputs.
where : array_like, optional
Values of True indicate to calculate the ufunc at that position, values
of False indicate to leave the value in the output alone.
**kwargs
Returns
-------
out : array_like
The values of `x1` with the sign of `x2`.
Examples
--------
>>> import mars.tensor as mt
>>> mt.copysign(1.3, -1).execute()
-1.3
>>> (1/mt.copysign(0, 1)).execute()
inf
>>> (1/mt.copysign(0, -1)).execute()
-inf
>>> mt.copysign([-1, 0, 1], -1.1).execute()
array([-1., -0., -1.])
>>> mt.copysign([-1, 0, 1], mt.arange(3)-1).execute()
array([-1., 0., 1.])
"""
op = TensorCopysign(**kwargs)
return op(x1, x2, out=out, where=where)
```