mindspore.mint.cummin

mindspore.mint.cummin(input, dim)

Return the cumulative minimum values and their indices along the given dimension of the tensor.

\[\begin{split}\begin{array}{ll} \\ y_{i} = \min(x_{1}, x_{2}, ... , x_{i}) \end{array}\end{split}\]

Note

GE backend is not supported in Ascend.

Parameters

• input (Tensor) – The input tensor.

• dim (int) – Specify the dimension to compute.

Returns

Tuple of two tensors, tuple(min, min_indices).

Supported Platforms:

Ascend

Examples

>>> import mindspore
>>> a = mindspore.tensor([-0.2284, -0.6628,  0.0975,  0.2680, -1.3298, -0.4220], mindspore.float32)
>>> output = mindspore.mint.cummin(a, dim=0)
>>> print(output[0])
[-0.2284 -0.6628 -0.6628 -0.6628 -1.3298 -1.3298]
>>> print(output[1])
[0 1 1 1 4 4]