def METHOD_NAME(input_model, output_model, layers_num):
    for i in range(layers_num):
        output_model["encoder.layer." + str(i) + ".attention.self.query.weight"] = \
            input_model["encoder.encoder_0.transformer." + str(i) + ".self_attn.linear_layers.0.weight"]
        output_model["encoder.layer." + str(i) + ".attention.self.query.bias"] = \
            input_model["encoder.encoder_0.transformer." + str(i) + ".self_attn.linear_layers.0.bias"]
        output_model["encoder.layer." + str(i) + ".attention.self.key.weight"] = \
            input_model["encoder.encoder_0.transformer." + str(i) + ".self_attn.linear_layers.1.weight"]
        output_model["encoder.layer." + str(i) + ".attention.self.key.bias"] = \
            input_model["encoder.encoder_0.transformer." + str(i) + ".self_attn.linear_layers.1.bias"]
        output_model["encoder.layer." + str(i) + ".attention.self.value.weight"] = \
            input_model["encoder.encoder_0.transformer." + str(i) + ".self_attn.linear_layers.2.weight"]
        output_model["encoder.layer." + str(i) + ".attention.self.value.bias"] = \
            input_model["encoder.encoder_0.transformer." + str(i) + ".self_attn.linear_layers.2.bias"]
        output_model["encoder.layer." + str(i) + ".attention.output.dense.weight"] = \
            input_model["encoder.encoder_0.transformer." + str(i) + ".self_attn.final_linear.weight"]
        output_model["encoder.layer." + str(i) + ".attention.output.dense.bias"] = \
            input_model["encoder.encoder_0.transformer." + str(i) + ".self_attn.final_linear.bias"]
        output_model["encoder.layer." + str(i) + ".attention.output.LayerNorm.weight"] = \
            input_model["encoder.encoder_0.transformer." + str(i) + ".layer_norm_1.gamma"]
        output_model["encoder.layer." + str(i) + ".attention.output.LayerNorm.bias"] = \
            input_model["encoder.encoder_0.transformer." + str(i) + ".layer_norm_1.beta"]
        output_model["encoder.layer." + str(i) + ".intermediate.dense.weight"] = \
            input_model["encoder.encoder_0.transformer." + str(i) + ".feed_forward.linear_1.weight"]
        output_model["encoder.layer." + str(i) + ".intermediate.dense.bias"] = \
            input_model["encoder.encoder_0.transformer." + str(i) + ".feed_forward.linear_1.bias"]
        output_model["encoder.layer." + str(i) + ".output.dense.weight"] = \
            input_model["encoder.encoder_0.transformer." + str(i) + ".feed_forward.linear_2.weight"]
        output_model["encoder.layer." + str(i) + ".output.dense.bias"] = \
            input_model["encoder.encoder_0.transformer." + str(i) + ".feed_forward.linear_2.bias"]
        output_model["encoder.layer." + str(i) + ".output.LayerNorm.weight"] = \
            input_model["encoder.encoder_0.transformer." + str(i) + ".layer_norm_2.gamma"]
        output_model["encoder.layer." + str(i) + ".output.LayerNorm.bias"] = \
            input_model["encoder.encoder_0.transformer." + str(i) + ".layer_norm_2.beta"]