# Source code for mars.tensor.arithmetic.isnan

```
#!/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 inject_dtype
from .core import TensorUnaryOp
from .utils import arithmetic_operand
@arithmetic_operand(sparse_mode="unary")
class TensorIsNan(TensorUnaryOp):
_op_type_ = OperandDef.ISNAN
_func_name = "isnan"
[docs]@inject_dtype(np.bool_)
def isnan(x, out=None, where=None, **kwargs):
"""
Test element-wise for NaN and return result as a boolean tensor.
Parameters
----------
x : array_like
Input tensor.
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 or bool
For scalar input, the result is a new boolean with value True if
the input is NaN; otherwise the value is False.
For array input, the result is a boolean tensor of the same
dimensions as the input and the values are True if the
corresponding element of the input is NaN; otherwise the values are
False.
See Also
--------
isinf, isneginf, isposinf, isfinite, isnat
Notes
-----
Mars uses the IEEE Standard for Binary Floating-Point for Arithmetic
(IEEE 754). This means that Not a Number is not equivalent to infinity.
Examples
--------
>>> import mars.tensor as mt
>>> mt.isnan(mt.nan).execute()
True
>>> mt.isnan(mt.inf).execute()
False
>>> mt.isnan([mt.log(-1.).execute(),1.,mt.log(0).execute()]).execute()
array([ True, False, False])
"""
op = TensorIsNan(**kwargs)
return op(x, out=out, where=where)
```