mindspore.mint.argmin

mindspore.mint.argmin(input, dim=None, keepdim=False)[source]

Return the indices of the minimum values of a tensor across a dimension.

Parameters

input (Tensor) – Input tensor.
dim (Union[int, None], optional) – Specify the axis for calculation. If dim is None , the indices of the minimum value within the flattened input will be returned. Default: None .
keepdim (bool, optional) – Whether the output tensor retains the specified dimension. Ignored if dim is None. Default: False .

Returns

Tensor, indices of the minimum values of the input tensor across a dimension.

Raises

TypeError – If keepdim is not bool.
ValueError – If dim is out of range.

Supported Platforms:: Ascend

Examples

>>> import numpy as np
>>> from mindspore import Tensor
>>> from mindspore import mint
>>> x = Tensor(np.array([[1, 20, 5], [67, 8, 9], [130, 24, 15]]).astype(np.float32))
>>> output = mint.argmin(x, dim=-1)
>>> print(output)
[0 1 2]