torch.cummin

torch.cummin(input, dim, *, out=None)

Returns a namedtuple (values, indices) where values is the cumulative minimum of elements of input in the dimension dim. And indices is the index location of each maximum value found in the dimension dim.

$$y_i = min(x_1, x_2, x_3, \dots, x_i)$$

Parameters:

• input (Tensor) – the input tensor.

• dim (int) – the dimension to do the operation over

Keyword Arguments:

out (tuple, optional) – the result tuple of two output tensors (values, indices)

Example:

>>> a = torch.randn(10)
>>> a
tensor([-0.2284, -0.6628,  0.0975,  0.2680, -1.3298, -0.4220, -0.3885,  1.1762,
     0.9165,  1.6684])
>>> torch.cummin(a, dim=0)
torch.return_types.cummin(
    values=tensor([-0.2284, -0.6628, -0.6628, -0.6628, -1.3298, -1.3298, -1.3298, -1.3298,
    -1.3298, -1.3298]),
    indices=tensor([0, 1, 1, 1, 4, 4, 4, 4, 4, 4]))