mindspore.mint.arange

mindspore.mint.arange(start=0, end=None, step=1, *, dtype=None)[source]

Creates a sequence of numbers that begins at start and extends by increments of step up to but not including end.

Parameters

start (Union[float, int], optional) – The start of the interval. Default: 0 .
end (Union[float, int], optional) – The end of the interval, exclusive. Default: None . If None , it defaults to the value of start, and 0 is used as the starting value.
step (Union[float, int], optional) – The step size with which the array element increments. Default: 1 .

Keyword Arguments

dtype (mindspore.dtype, optional) –

The required data type of returned Tensor. Default: None . When dtype is not specified or None:

If start, end, and step are all integers, the dtype of output is int64,

If start, end, and step contain at least one floating-point number, the dtype of output is float32.

Returns

A 1-D Tensor, cast to dtype if provided, may potentially lose precision due to casting.

Raises

TypeError – If start, end or step are not of type int or float.
ValueError – If step = 0.
ValueError – If start >= end when step > 0.
ValueError – If start <= end when step < 0.

Supported Platforms:: Ascend

Examples

>>> import mindspore as ms
>>> from mindspore import Tensor, mint
>>> output = mint.arange(1, 6)
>>> print(output)
[1 2 3 4 5]
>>> print(output.dtype)
Int64
>>> output = mint.arange(0, 3, 1.2)
>>> print(output)
[0.  1.2 2.4]
>>> print(output.dtype)
Float32
>>> output = mint.arange(7, 1, -2)
>>> print(output)
[7 5 3]
>>> print(output.dtype)
Int64
>>> output = mint.arange(12, 2, -1, dtype=ms.bfloat16))
>>> print(output)
[12. 11. 10.  9.  8.  7.  6.  5.  4.  3.]
>>> print(output.dtype)
BFloat16