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Specifications and Common Mistakes

- Specifications and Common Mistakes:

- Misspellings or punctuation mistakes,incorrect formulas, abnormal display.

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mindspore.ops.logspace

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

Return a tensor with steps elements, evenly distributed in the interval [ $bas{e}^{start}$ , $bas{e}^{end}$].

$$\begin{array}{r}\begin{array}{rl}& step=(end-start)/(steps-1)\\ & output=[bas{e}^{start},bas{e}^{start+1\ast step},...,bas{e}^{start+(steps-2)\ast step},bas{e}^{end}]\end{array}\end{array}$$

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]