Creates a criterion that optimizes a multi-label one-versus-all loss based on max-entropy, between input x and target y of size (N, C).

## Arguments

- input
tensor (N,*) where ** means, any number of additional dimensions

- target
tensor (N,*) , same shape as the input

- weight
weight tensor to apply on the loss.

- reduction
(string, optional) – Specifies the reduction to apply to the output: 'none' | 'mean' | 'sum'. 'none': no reduction will be applied, 'mean': the sum of the output will be divided by the number of elements in the output, 'sum': the output will be summed. Default: 'mean'