Applies the Softmax function to an n-dimensional input Tensor, rescaling them so that the elements of the n-dimensional output Tensor lie in the range (0,1) and sum to 1.

Softmax is defined as f_i(x) = exp(x_i-shift) / sum_j exp(x_j-shift), where shift = max_i x_i if self.computeShift is true (default).

if self.computeShift is set to false, then shift should be specified with self.shift.