mindspore.mint.linspace

mindspore.mint.linspace(start, end, steps, *, dtype=None)[source]

Returns a Tensor whose value is steps evenly spaced in the interval start and end (including start and end), and the length of the output Tensor is steps.

\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 = [s t a r t, s t a r t + s t e p, s t a r t + 2 * s t e p, . . ., e n d] \end{aligned} \end{array}

Warning

Atlas training series does not support int16 dtype currently.

Parameters

start (Union[float, int]) – Start value of interval. It can be a float or integer.
end (Union[float, int]) – Last value of interval. It can be a float or integer.
steps (int) – Number of ticks in the interval, inclusive of start and end. Must be positive integer.

Keyword Arguments

dtype (mindspore.dtype, optional) – The output Tensor data type. Default: None , in which case the data type of output Tensor is float32.

Returns

Tensor, has the shape of $(s t e p s,)$ , with dtype specified by dtype.

Raises

TypeError – If type of start or dtype of end is not supported.
ValueError – If steps is not positive integer.

Supported Platforms:: Ascend

Examples

>>> import mindspore as ms
>>> from mindspore import mint
>>> start = 1
>>> end = 10
>>> steps = 5
>>> output = mint.linspace(start, end, steps, dtype=ms.float32)
>>> print(output)
[ 1.    3.25  5.5   7.75 10.  ]