mindspore.Tensor.cummin
- Tensor.cummin(axis)[source]
Returns a tuple (values,indices) where ‘values’ is the cumulative minimum value of self Tensor along the dimension axis, and indices is the index location of each minimum value.
\[\begin{split}\begin{array}{ll} \\ y{i} = min(x{1}, x{2}, ... , x{i}) \end{array}\end{split}\]- Parameters
axis (int) – The dimension to do the operation over. The value of axis must be in the range [-x.ndim, x.ndim - 1].
- Returns
tuple [Tensor], tuple of 2 Tensors, containing the cumulative minimum of elements and the index, The shape of each output tensor is the same as self Tensor.
- Raises
TypeError – If axis is not an int.
ValueError – If axis is out the range of [-x.ndim, x.ndim - 1].
- Supported Platforms:
Ascend
GPU
CPU
Examples
>>> from mindspore import Tensor, ops >>> import mindspore >>> a = Tensor([-0.2284, -0.6628, 0.0975, 0.2680, -1.3298, -0.4220], mindspore.float32) >>> output = a.cummin(axis=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]