# Source code for mars.tensor.arithmetic.sign

```
#!/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 TensorUnaryOp
from .utils import arithmetic_operand
@arithmetic_operand(sparse_mode="unary")
class TensorSign(TensorUnaryOp):
_op_type_ = OperandDef.SIGN
_func_name = "sign"
[docs]@infer_dtype(np.sign)
def sign(x, out=None, where=None, **kwargs):
r"""
Returns an element-wise indication of the sign of a number.
The `sign` function returns ``-1 if x < 0, 0 if x==0, 1 if x > 0``. nan
is returned for nan inputs.
For complex inputs, the `sign` function returns
``sign(x.real) + 0j if x.real != 0 else sign(x.imag) + 0j``.
complex(nan, 0) is returned for complex nan inputs.
Parameters
----------
x : array_like
Input values.
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
-------
y : Tensor
The sign of `x`.
Notes
-----
There is more than one definition of sign in common use for complex
numbers. The definition used here is equivalent to :math:`x/\sqrt{x*x}`
which is different from a common alternative, :math:`x/|x|`.
Examples
--------
>>> import mars.tensor as mt
>>> mt.sign([-5., 4.5]).execute()
array([-1., 1.])
>>> mt.sign(0).execute()
0
>>> mt.sign(5-2j).execute()
(1+0j)
"""
op = TensorSign(**kwargs)
return op(x, out=out, where=where)
```