mx.nd.softmin

Description

Applies the softmin function.

The resulting array contains elements in the range (0,1) and the elements along the given axis sum up to 1.

\[softmin(\mathbf{z/t})_j = \frac{e^{-z_j/t}}{\sum_{k=1}^K e^{-z_k/t}}\]

for \(j = 1, ..., K\)

t is the temperature parameter in softmax function. By default, t equals 1.0

Example:

x = [[ 1.  2.  3.]
[ 3.  2.  1.]]

softmin(x,axis=0) = [[ 0.88079703,  0.5,  0.11920292],
[ 0.11920292,  0.5,  0.88079703]]

softmin(x,axis=1) = [[ 0.66524094,  0.24472848,  0.09003057],
[ 0.09003057,  0.24472848,  0.66524094]]

Arguments

Argument

Description

data

NDArray-or-Symbol.

The input array.

axis

int, optional, default=’-1’.

The axis along which to compute softmax.

temperature

double or None, optional, default=None.

Temperature parameter in softmax

dtype

{None, ‘float16’, ‘float32’, ‘float64’},optional, default=’None’.

DType of the output in case this can’t be inferred. Defaults to the same as input’s dtype if not defined (dtype=None).

use.length

boolean or None, optional, default=0.

Whether to use the length input as a mask over the data input.