mars.tensor.ldexp#
- mars.tensor.ldexp(x1, x2, out=None, where=None, **kwargs)[源代码]#
Returns x1 * 2**x2, element-wise.
The mantissas x1 and twos exponents x2 are used to construct floating point numbers
x1 * 2**x2
.- 参数
x1 (array_like) – Tensor of multipliers.
x2 (array_like, int) – Tensor of twos exponents.
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 –
- 返回
y – The result of
x1 * 2**x2
.- 返回类型
Tensor or scalar
参见
frexp
Return (y1, y2) from
x = y1 * 2**y2
, inverse to ldexp.
备注
Complex dtypes are not supported, they will raise a TypeError.
ldexp is useful as the inverse of frexp, if used by itself it is more clear to simply use the expression
x1 * 2**x2
.示例
>>> import mars.tensor as mt
>>> mt.ldexp(5, mt.arange(4)).execute() array([ 5., 10., 20., 40.], dtype=float32)
>>> x = mt.arange(6) >>> mt.ldexp(*mt.frexp(x)).execute() array([ 0., 1., 2., 3., 4., 5.])