def apply_final_layers(self, inputs):
    '剩余部分\n        '
    x = inputs
    z = self.layer_norm_conds[0]
    x = self.apply(inputs=self.simplify([x, z]), layer=LayerNormalization, epsilon=1e-05, conditional=(z is not None), hidden_units=self.layer_norm_conds[1], hidden_activation=self.layer_norm_conds[2], hidden_initializer=self.initializer, name='Output-Norm')
    x = self.apply(inputs=x, layer=Dropout, rate=self.dropout_rate, name='Output-Dropout')
    x = super(GPT2, self).apply_final_layers(x)
    return x
剩余部分
def apply_final_layers(self, inputs):
    '\n        '
    x = inputs
    z = self.layer_norm_conds[0]
    x = self.apply(inputs=self.simplify([x, z]), layer=LayerNormalization, epsilon=1e-05, conditional=(z is not None), hidden_units=self.layer_norm_conds[1], hidden_activation=self.layer_norm_conds[2], hidden_initializer=self.initializer, name='Output-Norm')
    x = self.apply(inputs=x, layer=Dropout, rate=self.dropout_rate, name='Output-Dropout')
    x = super(GPT2, self).apply_final_layers(x)
    return x