graphengine/ge/client/proto/insert_op.proto

/**
 * Copyright 2019-2020 Huawei Technologies Co., Ltd
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

syntax = "proto3";

package domi;

message InsertNewOps {
	repeated AippOpParams aipp_op = 1;
	repeated MultiShapeOpParams multi_shape_op = 2;
}

message AippOpParams {
	enum InputFormat {
		UNDEFINED = 0;
		YUV420SP_U8 = 1;
		XRGB8888_U8 = 2;
		RGB888_U8   = 3;
		YUV400_U8   = 4;
		NC1HWC0DI_FP16 = 5;
		NC1HWC0DI_S8 = 6;
		ARGB8888_U8 = 7;
		YUYV_U8 = 8;
		YUV422SP_U8 = 9;
		AYUV444_U8 = 10;
		RAW10 = 11;
		RAW12 = 12;
		RAW16 = 13;
		RAW24 = 14;
		RGB16 = 15;
		RGB20 = 16;
		RGB24 = 17;
		RGB8_IR = 18;
		RGB16_IR = 19;
		RGB24_IR = 20;
	}

	enum AippMode {
		undefined = 0;
		static = 1;
		dynamic = 2;
	}

	// AIPP模式，区分静态AIPP和动态AIPP
	AippMode aipp_mode = 1;

	// related_input_rank参数为必填，类型为整型，配置范围>=0, <=输入Data算子的个数，默认值为0。
	// 标识对模型的第几个输入做AIPP处理，例如模型有两个输入，需要对第2个输入做AIPP，则配置related_input_rank为1。
	uint32 related_input_rank = 2;

	// input_edge_idx参数为可选，类型为整型，配置范围为>=0。
	// 配置该参数的作用，在于对Data算子不同的输出做不同的AIPP处理，如果该参数没有配置，默认对related_input_rank指定的模型输入的所有输出边做AIPP。
	// 配置值 <= Data算子输出边的个数。
	repeated uint32 input_edge_idx = 3;

	// [Begin] 动态AIPP参数，配置静态AIPP时无效
	uint32 max_src_image_size = 4;

	// 是否支持旋转。默认不支持，开启支持旋转时，会有额外的空间和性能损失
	bool support_rotation = 5;

	// [End] 动态AIPP参数


	// [Begin] 静态AIPP参数，配置动态AIPP时无效
	InputFormat input_format = 51;
	bool csc_switch = 52;
	float cpadding_value = 53;
	bool rbuv_swap_switch = 54;
	bool ax_swap_switch = 55;
	bool single_line_mode = 56;

	int32 src_image_size_w = 57;
	int32 src_image_size_h = 58;

	bool crop = 59;
	int32 load_start_pos_w = 60;
	int32 load_start_pos_h = 61;
	int32 crop_size_w = 62;
	int32 crop_size_h = 63;

	bool resize = 64;
	int32 resize_output_w = 65;
	int32 resize_output_h = 66;

	bool padding = 67;
	int32 left_padding_size = 68;
	int32 right_padding_size = 69;
	int32 top_padding_size = 70;
	int32 bottom_padding_size = 71;

	int32 mean_chn_0 = 10;
	int32 mean_chn_1 = 11;
	int32 mean_chn_2 = 12;
	int32 mean_chn_3 = 19;
	float min_chn_0 = 13;
	float min_chn_1 = 14;
	float min_chn_2 = 15;
	float min_chn_3 = 20;
	repeated float var_reci_chn_0 = 16;
	repeated float var_reci_chn_1 = 17;
	repeated float var_reci_chn_2 = 18;
	repeated float var_reci_chn_3 = 21;

	repeated int32 matrix_r0c0 = 30;
	repeated int32 matrix_r0c1 = 31;
	repeated int32 matrix_r0c2 = 32;
	repeated int32 matrix_r1c0 = 33;
	repeated int32 matrix_r1c1 = 34;
	repeated int32 matrix_r1c2 = 35;
	repeated int32 matrix_r2c0 = 36;
	repeated int32 matrix_r2c1 = 37;
	repeated int32 matrix_r2c2 = 38;
	repeated int32 output_bias_0 = 39;
	repeated int32 output_bias_1 = 40;
	repeated int32 output_bias_2 = 41;
	repeated int32 input_bias_0 = 42;
	repeated int32 input_bias_1 = 43;
	repeated int32 input_bias_2 = 44;

	// [End] 静态AIPP参数

       // The n number that is used for raw/rgbir data into f16 transformation.
       // The transformation equation is x/(2^n). If set to 0, no transform is performed.
       uint32 raw_rgbir_to_f16_n = 45;
}

message MultiShapeOpParams {
	enum MultiShapeMode {
		batch      = 0;             //动态batch
		resolution = 1;             //动态分辨率，扩展用
	}

	MultiShapeMode    mode                      = 1;        //算子模式
	uint32            related_input_rank        = 2;        //新增算子插入到哪个输入


	repeated uint32 batch_list   = 11; //batch_list值，batch_list的个数是2到8之间
}