layers2.py 文件源码

def errors_top_x(self, y, num_top=5):
        if y.ndim != self.y_pred.ndim:
            raise TypeError('y should have the same shape as self.y_pred',
                            ('y', y.type, 'y_pred', self.y_pred.type))                            

        if num_top != 5: print('val errors from top %d' % num_top) ############TOP 5 VERSION##########        

        # check if y is of the correct datatype
        if y.dtype.startswith('int'):
            # the T.neq operator returns a vector of 0s and 1s, where 1
            # represents a mistake in prediction
            y_pred_top_x = T.argsort(self.p_y_given_x, axis=1)[:, -num_top:]
            y_top_x = y.reshape((y.shape[0], 1)).repeat(num_top, axis=1)
            return T.mean(T.min(T.neq(y_pred_top_x, y_top_x).astype('int8'), axis=1))
        else:
            raise NotImplementedError()