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mindspore.numpy.arange

mindspore.numpy.arange(start, stop=None, step=None, dtype=None)[source]

Returns evenly spaced values within a given interval.

Parameters

start (Union[int, float]) – Start of interval. The interval includes this value. When stop is provided as a position argument, start must be given, when stop is a normal argument, start can be optional, and default is 0. Please see additional examples below.
stop (Union[int, float], optional) – End of interval. The interval does not include this value, except in some cases where step is not an integer and floating point round-off affects the length of out.
step (Union[int, float], optional) – Spacing between values. For any output out, this is the distance between two adjacent values, $o u t [i + 1] - o u t [i]$ . The default step size is 1. If step is specified as a position argument, start must also be given.
dtype (Union[mindspore.dtype, str], optional) – Designated tensor dtype. If dtype is None, the data type of the new tensor will be inferred from start, stop and step. Default is None.

Returns

Tensor with evenly spaced values.

Raises

TypeError(PyNative Mode) or RuntimeError(Graph Mode) – If input arguments have types not specified above, or arguments are not given in the correct orders specified above.

Supported Platforms:: Ascend GPU CPU

Examples

>>> import mindspore.numpy as np
>>> print(np.arange(0, 5, 1))
[0 1 2 3 4]
>>> print(np.arange(3))
[0 1 2]
>>> print(np.arange(start=0, stop=3))
[0 1 2]
>>> print(np.arange(0, stop=3, step=0.5))
[0.  0.5 1.  1.5 2.  2.5]
>>> print(np.arange(stop=3)) # This will lead to TypeError