mindspore.ops.logspace

mindspore.ops.logspace(start, end, steps, base=10, *, dtype=mstype.float32)[source]

Return a tensor with steps elements, evenly distributed in the interval [ $b a s e^{s t a r t}$ , $b a s e^{e n d}$ ].

\begin{array}{r} \begin{aligned} s t e p = (e n d - s t a r t) / (s t e p s - 1) \\ o u t p u t = [b a s e^{s t a r t}, b a s e^{s t a r t + 1 * s t e p}, . . ., b a s e^{s t a r t + (s t e p s - 2) * s t e p}, b a s e^{e n d}] \end{aligned} \end{array}

Parameters

start (Union[float, Tensor]) – Start value of interval.
end (Union[float, Tensor]) – Last value of interval.
steps (int) – Number of elements.
base (int, optional) – Base of the logarithm function. Default 10 .

Keyword Arguments

dtype (mindspore.dtype, optional) – The data type specified. Default mstype.float32 .

Returns

Tensor

Supported Platforms:: Ascend GPU CPU

Examples

>>> import mindspore
>>> output = mindspore.ops.logspace(1., 10., steps = 10, base = 10)
>>> print(output)
[1.e+01 1.e+02 1.e+03 1.e+04 1.e+05 1.e+06 1.e+07 1.e+08 1.e+09 1.e+10]