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import numpy as np
from ... import opcodes as OperandDef
from ..utils import infer_dtype
from .core import TensorUnaryOp
from .utils import arithmetic_operand
_op_type_ = OperandDef.ARCTANH
_func_name = 'arctanh'
def arctanh(x, out=None, where=None, **kwargs):
Inverse hyperbolic tangent element-wise.
x : array_like
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.
out : Tensor
Array of the same shape as `x`.
`arctanh` is a multivalued function: for each `x` there are infinitely
many numbers `z` such that `tanh(z) = x`. The convention is to return
the `z` whose imaginary part lies in `[-pi/2, pi/2]`.
For real-valued input data types, `arctanh` always returns real output.
For each value that cannot be expressed as a real number or infinity,
it yields ``nan`` and sets the `invalid` floating point error flag.
For complex-valued input, `arctanh` is a complex analytical function
that has branch cuts `[-1, -inf]` and `[1, inf]` and is continuous from
above on the former and from below on the latter.
The inverse hyperbolic tangent is also known as `atanh` or ``tanh^-1``.
..  M. Abramowitz and I.A. Stegun, "Handbook of Mathematical Functions",
10th printing, 1964, pp. 86. http://www.math.sfu.ca/~cbm/aands/
..  Wikipedia, "Inverse hyperbolic function",
>>> import mars.tensor as mt
>>> mt.arctanh([0, -0.5]).execute()
array([ 0. , -0.54930614])
op = TensorArctanh(**kwargs)
return op(x, out=out, where=where)