'target[i] = 1, iff labels[i] is correctly predicted; 0 otherwise.'

def get_softmax_correct(self, labels, target):

    assert (labels.shape == (1, self.shape[1]))
    assert (target.shape == labels.shape)
    if isinstance(labels, CUDAMatrix):
        err_code = _cudamat.get_softmax_correct(self.p_mat, labels.p_mat, target.p_mat)
    else:
        raise ValueError, 'labels    must    be    of    type    CUDAMatrix.'
    if err_code:
        raise generate_exception(err_code)
    return target
