distributions.py 文件源码

def log_Bernoulli(x, mean, average=False, dim=None):
    probs = torch.clamp( mean, min=1e-7, max=1.-1e-7 )
    log_bernoulli = x * torch.log( probs ) + (1. - x ) * torch.log( 1. - probs )
    if average:
        return torch.mean( log_bernoulli, dim )
    else:
        return torch.sum( log_bernoulli, dim )