From 1bed26c72e9b8a7386703b8d698a4d55c379bb3f Mon Sep 17 00:00:00 2001 From: zhangxiaokun Date: Thu, 17 Jun 2021 11:28:14 +0800 Subject: [PATCH] Remove reduplicated useless proto --- ge/client/proto/ge_api.proto | 1 - ge/client/proto/ge_ir.proto | 193 -- ge/client/proto/insert_op.proto | 140 -- ge/client/proto/om.proto | 396 ---- ge/client/proto/task.proto | 179 -- ge/common/proto/ge_ir.proto | 193 -- ge/common/proto/insert_op.proto | 140 -- ge/common/proto/om.proto | 396 ---- ge/common/proto/op_mapping.proto | 75 - ge/common/proto/task.proto | 179 -- ge/common/proto/tensorflow/attr_value.proto | 70 - ge/common/proto/tensorflow/function.proto | 108 - ge/common/proto/tensorflow/graph.proto | 64 - .../proto/tensorflow/graph_library.proto | 22 - ge/common/proto/tensorflow/node_def.proto | 71 - ge/common/proto/tensorflow/op_def.proto | 172 -- .../proto/tensorflow/resource_handle.proto | 37 - ge/common/proto/tensorflow/tensor.proto | 102 - ge/common/proto/tensorflow/tensor_shape.proto | 53 - ge/common/proto/tensorflow/types.proto | 82 - ge/common/proto/tensorflow/versions.proto | 39 - ge/executor/proto/dump_task.proto | 113 - ge/executor/proto/ge_ir.proto | 193 -- ge/executor/proto/insert_op.proto | 140 -- ge/executor/proto/om.proto | 396 ---- ge/executor/proto/op_mapping.proto | 75 - ge/executor/proto/task.proto | 179 -- ge/ge_local_engine/proto/task.proto | 179 -- ge/offline/proto/ge_ir.proto | 193 -- ge/offline/proto/insert_op.proto | 140 -- ge/offline/proto/om.proto | 396 ---- ge/offline/proto/task.proto | 179 -- ge/proto/caffe/caffe.proto | 1829 ----------------- ge/proto/dump_task.proto | 113 - ge/proto/fusion_model.proto | 21 - ge/proto/fwk_adapter.proto | 37 - ge/proto/ge_api.proto | 88 - ge/proto/ge_ir.proto | 193 -- ge/proto/insert_op.proto | 140 -- ge/proto/om.proto | 396 ---- ge/proto/op_mapping.proto | 75 - ge/proto/optimizer_priority.proto | 7 - ge/proto/task.proto | 179 -- ge/proto/tensorflow/attr_value.proto | 70 - ge/proto/tensorflow/function.proto | 108 - ge/proto/tensorflow/graph.proto | 64 - ge/proto/tensorflow/graph_library.proto | 22 - ge/proto/tensorflow/node_def.proto | 71 - ge/proto/tensorflow/op_def.proto | 172 -- ge/proto/tensorflow/resource_handle.proto | 37 - ge/proto/tensorflow/tensor.proto | 102 - ge/proto/tensorflow/tensor_shape.proto | 53 - ge/proto/tensorflow/types.proto | 82 - ge/proto/tensorflow/versions.proto | 39 - 54 files changed, 8793 deletions(-) delete mode 100644 ge/client/proto/ge_api.proto delete mode 100644 ge/client/proto/ge_ir.proto delete mode 100644 ge/client/proto/insert_op.proto delete mode 100755 ge/client/proto/om.proto delete mode 100644 ge/client/proto/task.proto delete mode 100644 ge/common/proto/ge_ir.proto delete mode 100644 ge/common/proto/insert_op.proto delete mode 100644 ge/common/proto/om.proto delete mode 100644 ge/common/proto/op_mapping.proto delete mode 100644 ge/common/proto/task.proto delete mode 100644 ge/common/proto/tensorflow/attr_value.proto delete mode 100644 ge/common/proto/tensorflow/function.proto delete mode 100644 ge/common/proto/tensorflow/graph.proto delete mode 100644 ge/common/proto/tensorflow/graph_library.proto delete mode 100644 ge/common/proto/tensorflow/node_def.proto delete mode 100644 ge/common/proto/tensorflow/op_def.proto delete mode 100644 ge/common/proto/tensorflow/resource_handle.proto delete mode 100644 ge/common/proto/tensorflow/tensor.proto delete mode 100644 ge/common/proto/tensorflow/tensor_shape.proto delete mode 100644 ge/common/proto/tensorflow/types.proto delete mode 100644 ge/common/proto/tensorflow/versions.proto delete mode 100644 ge/executor/proto/dump_task.proto delete mode 100644 ge/executor/proto/ge_ir.proto delete mode 100644 ge/executor/proto/insert_op.proto delete mode 100644 ge/executor/proto/om.proto delete mode 100644 ge/executor/proto/op_mapping.proto delete mode 100644 ge/executor/proto/task.proto delete mode 100644 ge/ge_local_engine/proto/task.proto delete mode 100644 ge/offline/proto/ge_ir.proto delete mode 100644 ge/offline/proto/insert_op.proto delete mode 100644 ge/offline/proto/om.proto delete mode 100644 ge/offline/proto/task.proto delete mode 100644 ge/proto/caffe/caffe.proto delete mode 100644 ge/proto/dump_task.proto delete mode 100755 ge/proto/fusion_model.proto delete mode 100644 ge/proto/fwk_adapter.proto delete mode 100755 ge/proto/ge_api.proto delete mode 100644 ge/proto/ge_ir.proto delete mode 100644 ge/proto/insert_op.proto delete mode 100644 ge/proto/om.proto delete mode 100644 ge/proto/op_mapping.proto delete mode 100644 ge/proto/optimizer_priority.proto delete mode 100644 ge/proto/task.proto delete mode 100644 ge/proto/tensorflow/attr_value.proto delete mode 100644 ge/proto/tensorflow/function.proto delete mode 100644 ge/proto/tensorflow/graph.proto delete mode 100644 ge/proto/tensorflow/graph_library.proto delete mode 100644 ge/proto/tensorflow/node_def.proto delete mode 100644 ge/proto/tensorflow/op_def.proto delete mode 100644 ge/proto/tensorflow/resource_handle.proto delete mode 100644 ge/proto/tensorflow/tensor.proto delete mode 100644 ge/proto/tensorflow/tensor_shape.proto delete mode 100644 ge/proto/tensorflow/types.proto delete mode 100644 ge/proto/tensorflow/versions.proto diff --git a/ge/client/proto/ge_api.proto b/ge/client/proto/ge_api.proto deleted file mode 100644 index 26d705fe..00000000 --- a/ge/client/proto/ge_api.proto +++ /dev/null @@ -1 +0,0 @@ -../../proto/ge_api.proto \ No newline at end of file diff --git a/ge/client/proto/ge_ir.proto b/ge/client/proto/ge_ir.proto deleted file mode 100644 index c0ef3071..00000000 --- a/ge/client/proto/ge_ir.proto +++ /dev/null @@ -1,193 +0,0 @@ -syntax = "proto3"; - -package ge.proto; - -enum DataType -{ - DT_UNDEFINED = 0; // Used to indicate a DataType field has not been set. - DT_FLOAT = 1; // float type - DT_FLOAT16 = 2; // fp16 type - DT_INT8 = 3; // int8 type - DT_UINT8 = 4; // uint8 type - DT_INT16 = 5; // int16 type - DT_UINT16 = 6; // uint16 type - DT_INT32 = 7; // - DT_INT64 = 8; // int64 type - DT_UINT32 = 9; // unsigned int32 - DT_UINT64 = 10; // unsigned int64 - DT_BOOL = 11; // bool type - DT_DOUBLE = 12; // double type - DT_STRING = 13; // string type - DT_DUAL_SUB_INT8 = 14; /**< dual output int8 type */ - DT_DUAL_SUB_UINT8 = 15; /**< dual output uint8 type */ - DT_COMPLEX64 = 16; // complex64 type - DT_COMPLEX128 = 17; // complex128 type - DT_QINT8 = 18; // qint8 type - DT_QINT16 = 19; // qint16 type - DT_QINT32 = 20; // qint32 type - DT_QUINT8 = 21; // quint8 type - DT_QUINT16 = 22; // quint16 type - DT_RESOURCE = 23; // resource type - DT_STRING_REF = 24; // string_ref type - DT_DUAL = 25; /**< dual output type */ - DT_VARIANT = 26; // variant type - DT_BF16 = 27; // bf16 type - DT_INT4 = 28; // int4 type -} - -message AttrDef -{ - message ListValue - { - enum ListValueType{ - VT_LIST_NONE = 0; - VT_LIST_STRING = 1; - VT_LIST_INT = 2; - VT_LIST_FLOAT = 3; - VT_LIST_BOOL = 4; - VT_LIST_BYTES = 5; - VT_LIST_TENSOR_DESC = 6; - VT_LIST_TENSOR = 7; - VT_LIST_GRAPH = 8; - VT_LIST_NAMED_ATTRS = 9; - VT_LIST_DATA_TYPE = 10; - } - repeated bytes s = 2; // "list(string)" - repeated int64 i = 3; // "list(int)" - repeated float f = 4; // "list(float)" - repeated bool b = 5; // "list(bool)" - repeated bytes bt = 7; - repeated TensorDescriptor td = 8; - repeated TensorDef t = 9; - repeated GraphDef g = 10; - repeated NamedAttrs na = 11; - repeated int64 dt = 12; // list ge::DataType - - ListValueType val_type = 20; - } - - message ListListInt{ - message ListInt{ - repeated int64 list_i = 1; // list int - } - repeated ListInt list_list_i = 1; // list list int - } - - oneof value - { - bytes s = 2; // "string" - int64 i = 3; // "int" - float f = 4; // "float" - bool b = 5; // "bool" - bytes bt = 7; - ListValue list = 1; // any "list(...)" - NamedAttrs func = 10; // Used to support attr nesting - TensorDescriptor td = 11; // GeTensorDesc type - TensorDef t = 12; // GeTensor type - GraphDef g = 13; // Graph type - ListListInt list_list_int = 14; // List List Int type - int64 dt = 15; // ge::DataType - } -} - -// A list of attr names and their values. The whole list is attached -// with a string name. E.g., MatMul[T=float]. -message NamedAttrs -{ - string name = 1; - map attr = 2; -} - -// Shape / dimension description, using row-major order -message ShapeDef -{ - repeated int64 dim = 1; // Size of each dimension -} - -// Multidimensional data description -message TensorDescriptor -{ - string name = 1; // Optional parameter, tensor name - - DataType dtype = 2; // tensor datatype - ShapeDef shape = 3; // Shape / dimension - string layout = 4; // Tensor format, eg: "NCHW", "NHWC", "CHW", "ND" - - bool has_out_attr = 9; - int64 size = 10; - int64 weight_size = 11; - bool reuse_input = 12; - bool output_tensor = 13; - string device_type = 14; - bool input_tensor =15; - int64 real_dim_cnt = 16; - int64 reuse_input_index = 17; - int64 data_offset = 18; - int64 cmps_size = 19; - string cmps_tab = 20; - int64 cmps_tab_offset = 21; - - map attr = 5; // Set of extra parameter fields -} - -// GeTensor definition -message TensorDef -{ - TensorDescriptor desc = 1; // Tensor description - bytes data = 2; // Tensor data -} - - -// Operator description -message OpDef -{ - string name = 1; // name - string type = 2; // type - - repeated string input = 5; // input original op name + outgoing index. op_name锛歩ndex - - map attr = 10; // Set of operator parameter fields - - bool has_out_attr = 20; - int64 id = 21; - int64 stream_id =22; - repeated string input_name = 23; - repeated string src_name = 24; - repeated int64 src_index = 25; - repeated string dst_name = 26; - repeated int64 dst_index = 27; - repeated int64 input_i = 28; - repeated int64 output_i = 29; - repeated int64 workspace = 30; - repeated int64 workspace_bytes = 31; - repeated bool is_input_const = 32; - repeated TensorDescriptor input_desc = 33; - repeated TensorDescriptor output_desc = 34; - repeated string subgraph_name = 35; -} - -// Graph definition -message GraphDef -{ - string name = 1; // name - - repeated string input = 4; // Graph input - repeated string output = 5; // Graph output - - repeated OpDef op = 6; // List of operators - - map attr = 11; // Extended field -} - -// model definition -message ModelDef -{ - string name = 1; // name - uint32 version = 2; // IR Proto verion - string custom_version = 3; // User model version number, passed in by user - - repeated GraphDef graph = 7; // Graph definition锛実raph[0] represents the main diagram in modeldef - - map attr = 11; // Extended field -} - diff --git a/ge/client/proto/insert_op.proto b/ge/client/proto/insert_op.proto deleted file mode 100644 index 7d708865..00000000 --- a/ge/client/proto/insert_op.proto +++ /dev/null @@ -1,140 +0,0 @@ -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; - - // related_input_name is optional and the top name of data node which inserts aipp - string related_input_name = 6; - - // 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; - float padding_value = 72; - - 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 -} diff --git a/ge/client/proto/om.proto b/ge/client/proto/om.proto deleted file mode 100755 index e15e5f80..00000000 --- a/ge/client/proto/om.proto +++ /dev/null @@ -1,396 +0,0 @@ -/* Copyright (C) 2018. Huawei Technologies Co., Ltd. All rights reserved. - * - * This program is free software; you can redistribute it and/or modify - * it under the terms of the Apache License Version 2.0.You may not use this file except in compliance with the License. - * - * This program is distributed in the hope that it will be useful, - * but WITHOUT ANY WARRANTY; without even the implied warranty of - * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - * Apache License for more details at - * http://www.apache.org/licenses/LICENSE-2.0 - */ -syntax = "proto3"; - -package domi; - -enum TargetType -{ - MINI = 0; - TINY = 1; - LITE = 2; -} - -// offline model -message ModelDef { - string name = 1; - uint32 version = 2; - - uint64 memory_size = 10; - uint32 stream_num = 11; - uint32 event_num = 12; - uint64 weight_size = 13; - uint32 label_num = 15; - repeated OpDef op = 20; - TargetType target_type = 23; - - map attr = 30; -}; - -// operator define -message OpDef { - string name = 1; - string type = 2; - - uint32 id = 3; - uint32 stream_id = 4; - - repeated string input_name = 5; - - repeated string src_name = 8; - repeated int32 src_index = 9; - repeated int64 input = 10; - repeated int64 output = 11; - repeated TensorDescriptor input_desc = 12; - repeated TensorDescriptor output_desc = 13; - repeated WeightDef weights = 14; - repeated string dst_name = 15; - repeated int32 dst_index = 16; - - repeated int64 workspace = 20; - repeated uint32 workspace_bytes = 21; - - repeated string weight_name = 22; - repeated bool is_input_const = 23; - - map attr = 30; - - QuantizeFactorParams quantize_factor = 31; - - oneof op_params { - // start at 100 here - SendOpParams sender_param = 100; - RecvOpParams receiver_param = 200; - ConvolutionOpParams convolution_param = 300; - PoolingOpParams pooling_param = 400; - EltwiseOpParams eltwise_param = 500; - BatchNormOpParams batchnorm_param = 600; - ScaleOpParams scale_param = 700; - FullConnectionOpParams full_connection_param = 800; - SoftmaxOpParams softmax_param = 900; - ActivationOpParams activation_param = 1000; - ReshapeOpParams reshape_param = 1100; - } -}; - -message SendOpParams { - uint32 event_id = 1; -}; - -message RecvOpParams { - uint32 event_id = 1; -}; - -enum QuantizeScaleType -{ - VECTOR_SCALE = 0; - SCALAR_SCALE = 1; -} - -enum QuantizeScaleMode -{ - NORMAL_MODE = 0; - SQRT_MODE = 1; -} - -enum QuantizeAlgorithm -{ - NON_OFFSET_ALGO = 0; - HALF_OFFSET_ALGO = 1; - ALL_OFFSET_ALGO = 2; -} -message QuantizeFactor -{ - QuantizeScaleMode scale_mode = 1; - bytes scale_value = 2; - int64 scale_offset = 3; - bytes offset_data_value = 4; - int64 offset_data_offset = 5; - bytes offset_weight_value = 6; - int64 offset_weight_offset = 7; - bytes offset_pad_value = 8; - int64 offset_pad_offset = 9; -}; - -message QuantizeCalcFactor -{ - bytes offsetw = 1; - int64 offsetw_offset = 2; - bytes offsetd = 3; - int64 offsetd_offset = 4; - bytes scalereq = 5; - int64 scaledreq_offset = 6; - bytes offsetdnext = 7; - int64 offsetdnext_offset = 8; -} - -message QuantizeFactorParams -{ - QuantizeAlgorithm quantize_algo = 1; - QuantizeScaleType scale_type = 2; - QuantizeFactor quantize_param = 3; - QuantizeFactor dequantize_param = 4; - QuantizeFactor requantize_param = 5; - QuantizeCalcFactor quantizecalc_param = 6; -}; - -message ConvolutionOpParams { - int32 mode = 1; - int32 algo = 2; - int32 pad_mode = 3; - uint32 group = 4; - uint32 num_output = 5; - - repeated uint32 pad = 10; - repeated uint32 stride = 11; - repeated uint32 dilation = 12; - repeated uint32 kernel = 13; - - float alpha = 20; - float beta = 21; - - WeightDef filter = 40; - WeightDef bias = 41; - - bool relu_flag = 62; - repeated uint32 adj = 70; - repeated uint32 target_shape = 71; - repeated uint32 before_pad = 72; -}; - -message PoolingOpParams { - int32 mode = 1; - int32 nan_opt = 2; - int32 pad_mode = 3; - bool global_pooling = 4; - - repeated uint32 window = 10; - repeated uint32 pad = 11; - repeated uint32 stride = 12; - bool ceil_mode = 13; - int32 data_mode = 14; - - float alpha = 20; - float beta = 21; - repeated uint32 before_pad = 22; -}; - -message EltwiseOpParams { - int32 mode = 1; - repeated float coeff = 2; - float alpha = 3; - float beta = 4; - repeated WeightDef weight = 5; - bool relu_flag = 6; -}; - -message ActivationOpParams { - int32 mode = 1; - float coef = 2; - float alpha = 3; - float beta = 4; -}; - -message BatchNormOpParams { - int32 mode = 1; - - float alpha = 2; - float beta = 3; - double epsilon = 4;//optinal,[default = 1e-5] - bool use_global_stats = 5; //optinal,by default true,testing mode - float moving_average_fraction = 6; //optinal,[default = .999]; - - WeightDef estimated_mean = 7; - WeightDef estimated_variance = 8; - - WeightDef scale = 9; - WeightDef bias = 10; -}; - -message ScaleOpParams { - WeightDef scale = 1; - WeightDef bias = 2; -}; - -message ReshapeOpParams { - float alpha = 1; - float beta = 2; - ShapeDef shape = 3; - int32 axis = 4; - int32 num_axes = 5; - int32 format = 6; -}; - -message SoftmaxOpParams { - int32 algo = 1; - int32 mode = 2; - float alpha = 3; - float beta = 4; -}; - -message FullConnectionOpParams { - WeightDef filter = 1; - WeightDef bias = 2; - uint32 num_output = 3; - bool relu_flag = 12; -}; - -message FlattenOpParams { - float alpha = 1; - float beta = 2; - int32 start_axis = 3; - int32 end_axis = 4; -} - -message AddLimitedOpParams { - float alpha = 1; - float beta = 2; - int32 axis = 3; - bool broadcast = 4; - - repeated WeightDef weight = 10; -}; - -message MulLimitedOpParams { - float alpha = 1; - float beta = 2; - int32 axis = 3; - bool broadcast = 4; - - repeated WeightDef weight = 10; -}; - -message AddOpParams { - float alpha = 1; - float beta = 2; - - repeated WeightDef weight = 10; -}; - -message MulOpParams { - float alpha = 1; - float beta = 2; - - repeated WeightDef weight = 10; -}; - -message SubOpParams { - float alpha = 1; - float beta = 2; - - repeated WeightDef weight = 10; -}; - -message BiasAddOpParams { - float alpha = 1; - float beta = 2; - - WeightDef bias = 10; -}; - -message MatMulOpParams { - float alpha = 1; - float beta = 2; - bool transposeX = 3; - bool transposeW = 4; - - WeightDef filter = 10; - WeightDef bias = 12; -}; - -message RsqrtOpParams { - float alpha = 1; - float beta = 2; -}; - - -message WeightDef { - int32 format = 1; - int32 data_type = 2; - ShapeDef shape = 3; - bytes data = 4; - int64 data_offset = 5; - uint32 cmps_size = 6; - bytes cmps_tab = 7; - int64 cmps_tab_offset = 10; - CompressInfo cmps_info = 8; - AllOffsetQuantizeInfo alloffset_quantize_info = 11; -} - -message ShapeDef { - repeated int64 dim = 1; -} - -enum DeviceType { - NPU = 0; // In default, we will use NPU. - CPU = 1; // CPU -} - -message AllOffsetQuantizeInfo { - float scale = 1; - int32 offset = 2; -} - -message TensorDescriptor { - int32 format = 1; - int32 data_type = 2; - repeated int64 dim = 3; - uint32 size = 4; - bool reuse_input = 5; - bool output_tensor = 7; - DeviceType device_type = 8; - bool input_tensor = 9; - uint32 real_dim_cnt = 10; - uint32 reuse_input_index = 11; - AllOffsetQuantizeInfo alloffset_quantize_info = 12; -} - -message CompressInfo { - int32 blockRow = 1; // block row - int32 blockCol = 2; // block col - int32 fractalK = 3; // fractal K - int32 fractalN = 4; // fractal N - int32 lastFractalK = 5; // K of last fractal - int32 lastFractalN = 6; // N of last fractal - int32 cubeSize = 7; // cube's length - int32 loadDir = 8; // data load directtiono 0:col load 1:row load -} - -message AttrDef { - message ListValue { - repeated string s = 2; // "list(string)" - repeated int64 i = 3 [packed = true]; // "list(int)" - repeated float f = 4 [packed = true]; // "list(float)" - repeated bool b = 5 [packed = true]; // "list(bool)" - repeated uint32 u = 6 [packed = true]; // "list(uint)" - repeated bytes bt = 7; - } - - oneof value { - string s = 2; // "string" - int64 i = 3; // "int" - float f = 4; // "float" - bool b = 5; // "bool" - uint32 u = 6; // "uint32" - bytes bt = 7; - ListValue list = 1; // any "list(...)" - NamedAttrs func = 10; - } -} - -// A list of attr names and their values. The whole list is attached -// with a string name. E.g., MatMul[T=float]. -message NamedAttrs { - string name = 1; - map attr = 2; -} - diff --git a/ge/client/proto/task.proto b/ge/client/proto/task.proto deleted file mode 100644 index 0da5631e..00000000 --- a/ge/client/proto/task.proto +++ /dev/null @@ -1,179 +0,0 @@ -/* Copyright (C) 2018. Huawei Technologies Co., Ltd. All rights reserved. - * - * This program is free software; you can redistribute it and/or modify - * it under the terms of the Apache License Version 2.0.You may not use this file except in compliance with the License. - * - * This program is distributed in the hope that it will be useful, - * but WITHOUT ANY WARRANTY; without even the implied warranty of - * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - * Apache License for more details at - * http://www.apache.org/licenses/LICENSE-2.0 - */ -syntax = "proto3"; - -package domi; - -message ModelTaskDef { - string version = 1; - - map attr = 9; // Extended field - repeated TaskDef task = 10; - - uint64 memory_size = 11; - uint32 stream_num = 12; - uint32 event_num = 13; - uint64 weight_size = 14; - - repeated bytes op = 15; // input/output opdef in bytes - - uint64 base_addr = 16; // base addr - uint64 weight_addr = 17; // weight addr - uint32 batch_num = 18; -} - - -message TaskDef { - uint32 id = 1; - uint32 type = 2; - - uint32 stream_id = 10; - uint32 event_id = 11; - - KernelDef kernel = 20; - KernelExDef kernel_ex = 21; - KernelHcclDef kernel_hccl = 25; - EventExDef event_ex = 26; - LogTimeStampDef log_timestamp = 28; - - uint32 label_id = 30; - - MemcpyAsyncDef memcpy_async = 31; - StreamSwitchDef stream_switch = 32; - StreamActiveDef stream_active = 33; - bytes private_def = 34; - uint64 ops_kernel_store_ptr = 35; // adjustments to other fields in the future - StreamSwitchNDef stream_switch_n = 36; - - LabelSetDef label_set = 37; - LabelGotoExDef label_goto_ex = 38; - LabelSwitchByIndexDef label_switch_by_index = 39; - KernelDefWithHandle kernel_with_handle = 40; -} - -message KernelDef { - KernelContext context = 1; - - string stub_func = 10; - uint32 block_dim = 11; - uint32 args_size = 12; - bytes args = 13; - bytes sm_desc = 14; - bytes flowtable = 15; - string so_name = 16; - string kernel_name = 17; - bytes kernel_ext_info = 18; - uint32 kernel_ext_info_size = 19; -} - -message KernelDefWithHandle { - KernelContext context = 1; - - uint64 handle = 10; - string dev_func = 11; - uint32 block_dim = 12; - uint32 args_size = 13; - bytes args = 14; - bytes sm_desc = 15; - string original_kernel_key = 16; - string node_info = 17; -} - -message KernelContext { - uint32 kernel_type = 1; - uint32 op_id = 2; // OP type in CCE - uint32 kernel_func_id = 3; - uint32 op_index = 4; // TE/Custom operator - bool is_flowtable = 5; // Identify whether args is a flowtable structure - bytes args_offset = 6; // args offset information - uint32 args_count = 7; // args count - repeated uint32 origin_op_index = 8; -} - - -message KernelExDef { - uint32 flags = 1; - - uint32 op_index = 4; - uint32 args_size = 12; - bytes args = 13; - bytes task_info = 14; // serialized nodeDef, funcDef, inputoutput - uint32 task_info_size = 15; - bytes kernel_ext_info = 16; - uint32 kernel_ext_info_size = 17; -} - - -message KernelHcclDef { - uint32 op_index = 8; - string hccl_type = 9; -} - - -message EventExDef { - uint32 op_index = 1; - uint32 event_type = 2; -} - -message LogTimeStampDef { - uint64 logid = 1; - bool notify = 2; - uint32 flat = 3; -} - -message MemcpyAsyncDef { - uint64 dst = 1; - uint64 dst_max = 2; - uint64 src = 3; - uint64 count = 4; - uint32 kind = 5; - uint32 op_index = 6; -} - -message StreamSwitchDef { - uint32 op_index = 1; - uint32 true_stream_id = 2; - int64 value = 3; - uint64 value_ptr = 4; - uint32 data_type = 5; -} - -message StreamActiveDef { - uint32 op_index = 1; - uint32 active_stream_id = 2; -} - -message StreamSwitchNDef { - uint32 op_index = 1; - uint32 size = 2; - repeated int64 target_value = 3; - repeated uint32 true_stream_id = 4; - uint32 element_size = 5; - uint32 data_type = 6; -} - -message LabelSetDef { - uint32 op_index = 1; - uint32 label_id = 2; - uint32 model_id = 3; -} - -message LabelGotoExDef { - uint32 op_index = 1; - uint32 label_id = 2; - uint32 model_id = 3; -} - -message LabelSwitchByIndexDef { - uint32 op_index = 1; - uint32 label_max = 2; -} diff --git a/ge/common/proto/ge_ir.proto b/ge/common/proto/ge_ir.proto deleted file mode 100644 index c0ef3071..00000000 --- a/ge/common/proto/ge_ir.proto +++ /dev/null @@ -1,193 +0,0 @@ -syntax = "proto3"; - -package ge.proto; - -enum DataType -{ - DT_UNDEFINED = 0; // Used to indicate a DataType field has not been set. - DT_FLOAT = 1; // float type - DT_FLOAT16 = 2; // fp16 type - DT_INT8 = 3; // int8 type - DT_UINT8 = 4; // uint8 type - DT_INT16 = 5; // int16 type - DT_UINT16 = 6; // uint16 type - DT_INT32 = 7; // - DT_INT64 = 8; // int64 type - DT_UINT32 = 9; // unsigned int32 - DT_UINT64 = 10; // unsigned int64 - DT_BOOL = 11; // bool type - DT_DOUBLE = 12; // double type - DT_STRING = 13; // string type - DT_DUAL_SUB_INT8 = 14; /**< dual output int8 type */ - DT_DUAL_SUB_UINT8 = 15; /**< dual output uint8 type */ - DT_COMPLEX64 = 16; // complex64 type - DT_COMPLEX128 = 17; // complex128 type - DT_QINT8 = 18; // qint8 type - DT_QINT16 = 19; // qint16 type - DT_QINT32 = 20; // qint32 type - DT_QUINT8 = 21; // quint8 type - DT_QUINT16 = 22; // quint16 type - DT_RESOURCE = 23; // resource type - DT_STRING_REF = 24; // string_ref type - DT_DUAL = 25; /**< dual output type */ - DT_VARIANT = 26; // variant type - DT_BF16 = 27; // bf16 type - DT_INT4 = 28; // int4 type -} - -message AttrDef -{ - message ListValue - { - enum ListValueType{ - VT_LIST_NONE = 0; - VT_LIST_STRING = 1; - VT_LIST_INT = 2; - VT_LIST_FLOAT = 3; - VT_LIST_BOOL = 4; - VT_LIST_BYTES = 5; - VT_LIST_TENSOR_DESC = 6; - VT_LIST_TENSOR = 7; - VT_LIST_GRAPH = 8; - VT_LIST_NAMED_ATTRS = 9; - VT_LIST_DATA_TYPE = 10; - } - repeated bytes s = 2; // "list(string)" - repeated int64 i = 3; // "list(int)" - repeated float f = 4; // "list(float)" - repeated bool b = 5; // "list(bool)" - repeated bytes bt = 7; - repeated TensorDescriptor td = 8; - repeated TensorDef t = 9; - repeated GraphDef g = 10; - repeated NamedAttrs na = 11; - repeated int64 dt = 12; // list ge::DataType - - ListValueType val_type = 20; - } - - message ListListInt{ - message ListInt{ - repeated int64 list_i = 1; // list int - } - repeated ListInt list_list_i = 1; // list list int - } - - oneof value - { - bytes s = 2; // "string" - int64 i = 3; // "int" - float f = 4; // "float" - bool b = 5; // "bool" - bytes bt = 7; - ListValue list = 1; // any "list(...)" - NamedAttrs func = 10; // Used to support attr nesting - TensorDescriptor td = 11; // GeTensorDesc type - TensorDef t = 12; // GeTensor type - GraphDef g = 13; // Graph type - ListListInt list_list_int = 14; // List List Int type - int64 dt = 15; // ge::DataType - } -} - -// A list of attr names and their values. The whole list is attached -// with a string name. E.g., MatMul[T=float]. -message NamedAttrs -{ - string name = 1; - map attr = 2; -} - -// Shape / dimension description, using row-major order -message ShapeDef -{ - repeated int64 dim = 1; // Size of each dimension -} - -// Multidimensional data description -message TensorDescriptor -{ - string name = 1; // Optional parameter, tensor name - - DataType dtype = 2; // tensor datatype - ShapeDef shape = 3; // Shape / dimension - string layout = 4; // Tensor format, eg: "NCHW", "NHWC", "CHW", "ND" - - bool has_out_attr = 9; - int64 size = 10; - int64 weight_size = 11; - bool reuse_input = 12; - bool output_tensor = 13; - string device_type = 14; - bool input_tensor =15; - int64 real_dim_cnt = 16; - int64 reuse_input_index = 17; - int64 data_offset = 18; - int64 cmps_size = 19; - string cmps_tab = 20; - int64 cmps_tab_offset = 21; - - map attr = 5; // Set of extra parameter fields -} - -// GeTensor definition -message TensorDef -{ - TensorDescriptor desc = 1; // Tensor description - bytes data = 2; // Tensor data -} - - -// Operator description -message OpDef -{ - string name = 1; // name - string type = 2; // type - - repeated string input = 5; // input original op name + outgoing index. op_name锛歩ndex - - map attr = 10; // Set of operator parameter fields - - bool has_out_attr = 20; - int64 id = 21; - int64 stream_id =22; - repeated string input_name = 23; - repeated string src_name = 24; - repeated int64 src_index = 25; - repeated string dst_name = 26; - repeated int64 dst_index = 27; - repeated int64 input_i = 28; - repeated int64 output_i = 29; - repeated int64 workspace = 30; - repeated int64 workspace_bytes = 31; - repeated bool is_input_const = 32; - repeated TensorDescriptor input_desc = 33; - repeated TensorDescriptor output_desc = 34; - repeated string subgraph_name = 35; -} - -// Graph definition -message GraphDef -{ - string name = 1; // name - - repeated string input = 4; // Graph input - repeated string output = 5; // Graph output - - repeated OpDef op = 6; // List of operators - - map attr = 11; // Extended field -} - -// model definition -message ModelDef -{ - string name = 1; // name - uint32 version = 2; // IR Proto verion - string custom_version = 3; // User model version number, passed in by user - - repeated GraphDef graph = 7; // Graph definition锛実raph[0] represents the main diagram in modeldef - - map attr = 11; // Extended field -} - diff --git a/ge/common/proto/insert_op.proto b/ge/common/proto/insert_op.proto deleted file mode 100644 index 7d708865..00000000 --- a/ge/common/proto/insert_op.proto +++ /dev/null @@ -1,140 +0,0 @@ -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; - - // related_input_name is optional and the top name of data node which inserts aipp - string related_input_name = 6; - - // 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; - float padding_value = 72; - - 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 -} diff --git a/ge/common/proto/om.proto b/ge/common/proto/om.proto deleted file mode 100644 index e15e5f80..00000000 --- a/ge/common/proto/om.proto +++ /dev/null @@ -1,396 +0,0 @@ -/* Copyright (C) 2018. Huawei Technologies Co., Ltd. All rights reserved. - * - * This program is free software; you can redistribute it and/or modify - * it under the terms of the Apache License Version 2.0.You may not use this file except in compliance with the License. - * - * This program is distributed in the hope that it will be useful, - * but WITHOUT ANY WARRANTY; without even the implied warranty of - * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - * Apache License for more details at - * http://www.apache.org/licenses/LICENSE-2.0 - */ -syntax = "proto3"; - -package domi; - -enum TargetType -{ - MINI = 0; - TINY = 1; - LITE = 2; -} - -// offline model -message ModelDef { - string name = 1; - uint32 version = 2; - - uint64 memory_size = 10; - uint32 stream_num = 11; - uint32 event_num = 12; - uint64 weight_size = 13; - uint32 label_num = 15; - repeated OpDef op = 20; - TargetType target_type = 23; - - map attr = 30; -}; - -// operator define -message OpDef { - string name = 1; - string type = 2; - - uint32 id = 3; - uint32 stream_id = 4; - - repeated string input_name = 5; - - repeated string src_name = 8; - repeated int32 src_index = 9; - repeated int64 input = 10; - repeated int64 output = 11; - repeated TensorDescriptor input_desc = 12; - repeated TensorDescriptor output_desc = 13; - repeated WeightDef weights = 14; - repeated string dst_name = 15; - repeated int32 dst_index = 16; - - repeated int64 workspace = 20; - repeated uint32 workspace_bytes = 21; - - repeated string weight_name = 22; - repeated bool is_input_const = 23; - - map attr = 30; - - QuantizeFactorParams quantize_factor = 31; - - oneof op_params { - // start at 100 here - SendOpParams sender_param = 100; - RecvOpParams receiver_param = 200; - ConvolutionOpParams convolution_param = 300; - PoolingOpParams pooling_param = 400; - EltwiseOpParams eltwise_param = 500; - BatchNormOpParams batchnorm_param = 600; - ScaleOpParams scale_param = 700; - FullConnectionOpParams full_connection_param = 800; - SoftmaxOpParams softmax_param = 900; - ActivationOpParams activation_param = 1000; - ReshapeOpParams reshape_param = 1100; - } -}; - -message SendOpParams { - uint32 event_id = 1; -}; - -message RecvOpParams { - uint32 event_id = 1; -}; - -enum QuantizeScaleType -{ - VECTOR_SCALE = 0; - SCALAR_SCALE = 1; -} - -enum QuantizeScaleMode -{ - NORMAL_MODE = 0; - SQRT_MODE = 1; -} - -enum QuantizeAlgorithm -{ - NON_OFFSET_ALGO = 0; - HALF_OFFSET_ALGO = 1; - ALL_OFFSET_ALGO = 2; -} -message QuantizeFactor -{ - QuantizeScaleMode scale_mode = 1; - bytes scale_value = 2; - int64 scale_offset = 3; - bytes offset_data_value = 4; - int64 offset_data_offset = 5; - bytes offset_weight_value = 6; - int64 offset_weight_offset = 7; - bytes offset_pad_value = 8; - int64 offset_pad_offset = 9; -}; - -message QuantizeCalcFactor -{ - bytes offsetw = 1; - int64 offsetw_offset = 2; - bytes offsetd = 3; - int64 offsetd_offset = 4; - bytes scalereq = 5; - int64 scaledreq_offset = 6; - bytes offsetdnext = 7; - int64 offsetdnext_offset = 8; -} - -message QuantizeFactorParams -{ - QuantizeAlgorithm quantize_algo = 1; - QuantizeScaleType scale_type = 2; - QuantizeFactor quantize_param = 3; - QuantizeFactor dequantize_param = 4; - QuantizeFactor requantize_param = 5; - QuantizeCalcFactor quantizecalc_param = 6; -}; - -message ConvolutionOpParams { - int32 mode = 1; - int32 algo = 2; - int32 pad_mode = 3; - uint32 group = 4; - uint32 num_output = 5; - - repeated uint32 pad = 10; - repeated uint32 stride = 11; - repeated uint32 dilation = 12; - repeated uint32 kernel = 13; - - float alpha = 20; - float beta = 21; - - WeightDef filter = 40; - WeightDef bias = 41; - - bool relu_flag = 62; - repeated uint32 adj = 70; - repeated uint32 target_shape = 71; - repeated uint32 before_pad = 72; -}; - -message PoolingOpParams { - int32 mode = 1; - int32 nan_opt = 2; - int32 pad_mode = 3; - bool global_pooling = 4; - - repeated uint32 window = 10; - repeated uint32 pad = 11; - repeated uint32 stride = 12; - bool ceil_mode = 13; - int32 data_mode = 14; - - float alpha = 20; - float beta = 21; - repeated uint32 before_pad = 22; -}; - -message EltwiseOpParams { - int32 mode = 1; - repeated float coeff = 2; - float alpha = 3; - float beta = 4; - repeated WeightDef weight = 5; - bool relu_flag = 6; -}; - -message ActivationOpParams { - int32 mode = 1; - float coef = 2; - float alpha = 3; - float beta = 4; -}; - -message BatchNormOpParams { - int32 mode = 1; - - float alpha = 2; - float beta = 3; - double epsilon = 4;//optinal,[default = 1e-5] - bool use_global_stats = 5; //optinal,by default true,testing mode - float moving_average_fraction = 6; //optinal,[default = .999]; - - WeightDef estimated_mean = 7; - WeightDef estimated_variance = 8; - - WeightDef scale = 9; - WeightDef bias = 10; -}; - -message ScaleOpParams { - WeightDef scale = 1; - WeightDef bias = 2; -}; - -message ReshapeOpParams { - float alpha = 1; - float beta = 2; - ShapeDef shape = 3; - int32 axis = 4; - int32 num_axes = 5; - int32 format = 6; -}; - -message SoftmaxOpParams { - int32 algo = 1; - int32 mode = 2; - float alpha = 3; - float beta = 4; -}; - -message FullConnectionOpParams { - WeightDef filter = 1; - WeightDef bias = 2; - uint32 num_output = 3; - bool relu_flag = 12; -}; - -message FlattenOpParams { - float alpha = 1; - float beta = 2; - int32 start_axis = 3; - int32 end_axis = 4; -} - -message AddLimitedOpParams { - float alpha = 1; - float beta = 2; - int32 axis = 3; - bool broadcast = 4; - - repeated WeightDef weight = 10; -}; - -message MulLimitedOpParams { - float alpha = 1; - float beta = 2; - int32 axis = 3; - bool broadcast = 4; - - repeated WeightDef weight = 10; -}; - -message AddOpParams { - float alpha = 1; - float beta = 2; - - repeated WeightDef weight = 10; -}; - -message MulOpParams { - float alpha = 1; - float beta = 2; - - repeated WeightDef weight = 10; -}; - -message SubOpParams { - float alpha = 1; - float beta = 2; - - repeated WeightDef weight = 10; -}; - -message BiasAddOpParams { - float alpha = 1; - float beta = 2; - - WeightDef bias = 10; -}; - -message MatMulOpParams { - float alpha = 1; - float beta = 2; - bool transposeX = 3; - bool transposeW = 4; - - WeightDef filter = 10; - WeightDef bias = 12; -}; - -message RsqrtOpParams { - float alpha = 1; - float beta = 2; -}; - - -message WeightDef { - int32 format = 1; - int32 data_type = 2; - ShapeDef shape = 3; - bytes data = 4; - int64 data_offset = 5; - uint32 cmps_size = 6; - bytes cmps_tab = 7; - int64 cmps_tab_offset = 10; - CompressInfo cmps_info = 8; - AllOffsetQuantizeInfo alloffset_quantize_info = 11; -} - -message ShapeDef { - repeated int64 dim = 1; -} - -enum DeviceType { - NPU = 0; // In default, we will use NPU. - CPU = 1; // CPU -} - -message AllOffsetQuantizeInfo { - float scale = 1; - int32 offset = 2; -} - -message TensorDescriptor { - int32 format = 1; - int32 data_type = 2; - repeated int64 dim = 3; - uint32 size = 4; - bool reuse_input = 5; - bool output_tensor = 7; - DeviceType device_type = 8; - bool input_tensor = 9; - uint32 real_dim_cnt = 10; - uint32 reuse_input_index = 11; - AllOffsetQuantizeInfo alloffset_quantize_info = 12; -} - -message CompressInfo { - int32 blockRow = 1; // block row - int32 blockCol = 2; // block col - int32 fractalK = 3; // fractal K - int32 fractalN = 4; // fractal N - int32 lastFractalK = 5; // K of last fractal - int32 lastFractalN = 6; // N of last fractal - int32 cubeSize = 7; // cube's length - int32 loadDir = 8; // data load directtiono 0:col load 1:row load -} - -message AttrDef { - message ListValue { - repeated string s = 2; // "list(string)" - repeated int64 i = 3 [packed = true]; // "list(int)" - repeated float f = 4 [packed = true]; // "list(float)" - repeated bool b = 5 [packed = true]; // "list(bool)" - repeated uint32 u = 6 [packed = true]; // "list(uint)" - repeated bytes bt = 7; - } - - oneof value { - string s = 2; // "string" - int64 i = 3; // "int" - float f = 4; // "float" - bool b = 5; // "bool" - uint32 u = 6; // "uint32" - bytes bt = 7; - ListValue list = 1; // any "list(...)" - NamedAttrs func = 10; - } -} - -// A list of attr names and their values. The whole list is attached -// with a string name. E.g., MatMul[T=float]. -message NamedAttrs { - string name = 1; - map attr = 2; -} - diff --git a/ge/common/proto/op_mapping.proto b/ge/common/proto/op_mapping.proto deleted file mode 100644 index d626eb49..00000000 --- a/ge/common/proto/op_mapping.proto +++ /dev/null @@ -1,75 +0,0 @@ -syntax = "proto3"; -package toolkit.aicpu.dump; - -message Shape { - repeated uint64 dim = 1; -} - -message Output { - int32 data_type = 1; - int32 format = 2; - Shape shape = 3; - uint64 address = 4; - string original_name = 5; - int32 original_output_index = 6; - int32 original_output_data_type = 7; - int32 original_output_format = 8; - uint64 size = 9; - Shape origin_shape = 10; -} - -message Input { - int32 data_type =1; - int32 format = 2; - Shape shape = 3; - uint64 address = 4; - uint64 size = 5; - Shape origin_shape = 6; -} - -enum BufferType { - L1 = 0; -} - -message OpBuffer { - BufferType buffer_type = 1; - uint64 address = 2; - uint64 size = 3; -} - -message Op { - string op_name = 1; - string op_type = 2; -} - -message Task { - uint32 task_id = 1; - uint32 stream_id = 2; - Op op = 3; - repeated Output output = 4; - bool end_graph = 5; - repeated Input input = 6; - repeated OpBuffer buffer = 7; -} - -message OpMappingInfo { - string dump_path = 1; - oneof model_name_param { - string model_name = 2; - } - oneof model_id_param { - uint32 model_id = 3; - } - oneof step_id { - uint64 step_id_addr = 4; - } - oneof iterations_per_loop { - uint64 iterations_per_loop_addr = 5; - } - oneof loop_cond { - uint64 loop_cond_addr = 6; - } - uint32 flag = 7; // 0x01 load, 0x00 unload - repeated Task task = 8; - string dump_step = 9; -} \ No newline at end of file diff --git a/ge/common/proto/task.proto b/ge/common/proto/task.proto deleted file mode 100644 index 0da5631e..00000000 --- a/ge/common/proto/task.proto +++ /dev/null @@ -1,179 +0,0 @@ -/* Copyright (C) 2018. Huawei Technologies Co., Ltd. All rights reserved. - * - * This program is free software; you can redistribute it and/or modify - * it under the terms of the Apache License Version 2.0.You may not use this file except in compliance with the License. - * - * This program is distributed in the hope that it will be useful, - * but WITHOUT ANY WARRANTY; without even the implied warranty of - * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - * Apache License for more details at - * http://www.apache.org/licenses/LICENSE-2.0 - */ -syntax = "proto3"; - -package domi; - -message ModelTaskDef { - string version = 1; - - map attr = 9; // Extended field - repeated TaskDef task = 10; - - uint64 memory_size = 11; - uint32 stream_num = 12; - uint32 event_num = 13; - uint64 weight_size = 14; - - repeated bytes op = 15; // input/output opdef in bytes - - uint64 base_addr = 16; // base addr - uint64 weight_addr = 17; // weight addr - uint32 batch_num = 18; -} - - -message TaskDef { - uint32 id = 1; - uint32 type = 2; - - uint32 stream_id = 10; - uint32 event_id = 11; - - KernelDef kernel = 20; - KernelExDef kernel_ex = 21; - KernelHcclDef kernel_hccl = 25; - EventExDef event_ex = 26; - LogTimeStampDef log_timestamp = 28; - - uint32 label_id = 30; - - MemcpyAsyncDef memcpy_async = 31; - StreamSwitchDef stream_switch = 32; - StreamActiveDef stream_active = 33; - bytes private_def = 34; - uint64 ops_kernel_store_ptr = 35; // adjustments to other fields in the future - StreamSwitchNDef stream_switch_n = 36; - - LabelSetDef label_set = 37; - LabelGotoExDef label_goto_ex = 38; - LabelSwitchByIndexDef label_switch_by_index = 39; - KernelDefWithHandle kernel_with_handle = 40; -} - -message KernelDef { - KernelContext context = 1; - - string stub_func = 10; - uint32 block_dim = 11; - uint32 args_size = 12; - bytes args = 13; - bytes sm_desc = 14; - bytes flowtable = 15; - string so_name = 16; - string kernel_name = 17; - bytes kernel_ext_info = 18; - uint32 kernel_ext_info_size = 19; -} - -message KernelDefWithHandle { - KernelContext context = 1; - - uint64 handle = 10; - string dev_func = 11; - uint32 block_dim = 12; - uint32 args_size = 13; - bytes args = 14; - bytes sm_desc = 15; - string original_kernel_key = 16; - string node_info = 17; -} - -message KernelContext { - uint32 kernel_type = 1; - uint32 op_id = 2; // OP type in CCE - uint32 kernel_func_id = 3; - uint32 op_index = 4; // TE/Custom operator - bool is_flowtable = 5; // Identify whether args is a flowtable structure - bytes args_offset = 6; // args offset information - uint32 args_count = 7; // args count - repeated uint32 origin_op_index = 8; -} - - -message KernelExDef { - uint32 flags = 1; - - uint32 op_index = 4; - uint32 args_size = 12; - bytes args = 13; - bytes task_info = 14; // serialized nodeDef, funcDef, inputoutput - uint32 task_info_size = 15; - bytes kernel_ext_info = 16; - uint32 kernel_ext_info_size = 17; -} - - -message KernelHcclDef { - uint32 op_index = 8; - string hccl_type = 9; -} - - -message EventExDef { - uint32 op_index = 1; - uint32 event_type = 2; -} - -message LogTimeStampDef { - uint64 logid = 1; - bool notify = 2; - uint32 flat = 3; -} - -message MemcpyAsyncDef { - uint64 dst = 1; - uint64 dst_max = 2; - uint64 src = 3; - uint64 count = 4; - uint32 kind = 5; - uint32 op_index = 6; -} - -message StreamSwitchDef { - uint32 op_index = 1; - uint32 true_stream_id = 2; - int64 value = 3; - uint64 value_ptr = 4; - uint32 data_type = 5; -} - -message StreamActiveDef { - uint32 op_index = 1; - uint32 active_stream_id = 2; -} - -message StreamSwitchNDef { - uint32 op_index = 1; - uint32 size = 2; - repeated int64 target_value = 3; - repeated uint32 true_stream_id = 4; - uint32 element_size = 5; - uint32 data_type = 6; -} - -message LabelSetDef { - uint32 op_index = 1; - uint32 label_id = 2; - uint32 model_id = 3; -} - -message LabelGotoExDef { - uint32 op_index = 1; - uint32 label_id = 2; - uint32 model_id = 3; -} - -message LabelSwitchByIndexDef { - uint32 op_index = 1; - uint32 label_max = 2; -} diff --git a/ge/common/proto/tensorflow/attr_value.proto b/ge/common/proto/tensorflow/attr_value.proto deleted file mode 100644 index 438d7163..00000000 --- a/ge/common/proto/tensorflow/attr_value.proto +++ /dev/null @@ -1,70 +0,0 @@ -/** - * This file is part of Open Source Software TensorFlow, version 1.15.0 https://github.com/tensorflow/tensorflow - * - * This file is included by GraphEngine so as to support model format conversion from tensorflow model to GraphEngine model. - * This file in this distribution may have been modified by Huawei Technologies Co., Ltd ("Huawei Modifications"). - * All Huawei Modifications are Copyright 2019-2020 Huawei Technologies Co., Ltd. - */ - -syntax = "proto3"; - -package domi.tensorflow; -option cc_enable_arenas = true; -option java_outer_classname = "AttrValueProtos"; -option java_multiple_files = true; -option java_package = "org.tensorflow.framework"; - -import "tensor.proto"; -import "tensor_shape.proto"; -import "types.proto"; - -// Protocol buffer representing the value for an attr used to configure an Op. -// Comment indicates the corresponding attr type. Only the field matching the -// attr type may be filled. -message AttrValue { - // LINT.IfChange - message ListValue { - repeated bytes s = 2; // "list(string)" - repeated int64 i = 3 [packed = true]; // "list(int)" - repeated float f = 4 [packed = true]; // "list(float)" - repeated bool b = 5 [packed = true]; // "list(bool)" - repeated DataType type = 6 [packed = true]; // "list(type)" - repeated TensorShapeProto shape = 7; // "list(shape)" - repeated TensorProto tensor = 8; // "list(tensor)" - repeated NameAttrList func = 9; // "list(attr)" - } - // LINT.ThenChange(https://www.tensorflow.org/code/tensorflow/c/c_api.cc) - - oneof value { - bytes s = 2; // "string" - int64 i = 3; // "int" - float f = 4; // "float" - bool b = 5; // "bool" - DataType type = 6; // "type" - TensorShapeProto shape = 7; // "shape" - TensorProto tensor = 8; // "tensor" - ListValue list = 1; // any "list(...)" - - // "func" represents a function. func.name is a function's name or - // a primitive op's name. func.attr.first is the name of an attr - // defined for that function. func.attr.second is the value for - // that attr in the instantiation. - NameAttrList func = 10; - - // This is a placeholder only used in nodes defined inside a - // function. It indicates the attr value will be supplied when - // the function is instantiated. For example, let us suppose a - // node "N" in function "FN". "N" has an attr "A" with value - // placeholder = "foo". When FN is instantiated with attr "foo" - // set to "bar", the instantiated node N's attr A will have been - // given the value "bar". - string placeholder = 9; - } -} - -// A list of attr names and their values. The whole list is attached -// with a string name. E.g., MatMul[T=float]. -message NameAttrList { - string name = 1; - map attr = 2; -} diff --git a/ge/common/proto/tensorflow/function.proto b/ge/common/proto/tensorflow/function.proto deleted file mode 100644 index 44681e32..00000000 --- a/ge/common/proto/tensorflow/function.proto +++ /dev/null @@ -1,108 +0,0 @@ -/** - * This file is part of Open Source Software TensorFlow, version 1.15.0 https://github.com/tensorflow/tensorflow - * - * This file is included by GraphEngine so as to support model format conversion from tensorflow model to GraphEngine model. - * This file in this distribution may have been modified by Huawei Technologies Co., Ltd ("Huawei Modifications"). - * All Huawei Modifications are Copyright 2019-2020 Huawei Technologies Co., Ltd. - */ - -syntax = "proto3"; - -package domi.tensorflow; -option cc_enable_arenas = true; -option java_outer_classname = "FunctionProtos"; -option java_multiple_files = true; -option java_package = "org.tensorflow.framework"; - -import "attr_value.proto"; -import "node_def.proto"; -import "op_def.proto"; - -// A library is a set of named functions. -message FunctionDefLibrary { - repeated FunctionDef function = 1; - repeated GradientDef gradient = 2; -} - -// A function can be instantiated when the runtime can bind every attr -// with a value. When a GraphDef has a call to a function, it must -// have binding for every attr defined in the signature. -// * device spec, etc. -message FunctionDef { - // The definition of the function's name, arguments, return values, - // attrs etc. - OpDef signature = 1; - - // Attributes specific to this function definition. - map attr = 5; - - // NOTE: field id 2 deleted on Jan 11, 2017, GraphDef version 21. - reserved 2; - - // In both of the following fields, there is the need to specify an - // output that is used as either the input to another node (in - // `node_def`) or as a return value of the function (in `ret`). - // Unlike the NodeDefs in GraphDef, we need to be able to specify a - // list in some cases (instead of just single outputs). Also, we - // need to be able to deal with lists of unknown length (so the - // output index may not be known at function definition time). So - // we use the following format instead: - // * "fun_in" where "fun_in" is the name of a function input arg in - // the `signature` field above. This represents that input, whether - // it is a single tensor or a list. - // * "fun_in:0" gives the first element of a function input arg (a - // non-list input is considered a list of length 1 for these - // purposes). - // * "node:out" where "node" is the name of a node in `node_def` and - // "out" is the name one of its op's output arguments (the name - // comes from the OpDef of the node's op). This represents that - // node's output, whether it is a single tensor or a list. - // Note: We enforce that an op's output arguments are never - // renamed in the backwards-compatibility test. - // * "node:out:0" gives the first element of a node output arg (a - // non-list output is considered a list of length 1 for these - // purposes). - // - // NOT CURRENTLY SUPPORTED (but may be in the future): - // * "node:out:-1" gives last element in a node output list - // * "node:out:1:" gives a list with all but the first element in a - // node output list - // * "node:out::-1" gives a list with all but the last element in a - // node output list - - // The body of the function. Unlike the NodeDefs in a GraphDef, attrs - // may have values of type `placeholder` and the `input` field uses - // the "output" format above. - - // By convention, "op" in node_def is resolved by consulting with a - // user-defined library first. If not resolved, "func" is assumed to - // be a builtin op. - repeated NodeDef node_def = 3; - - // A mapping from the output arg names from `signature` to the - // outputs from `node_def` that should be returned by the function. - map ret = 4; -} - -// GradientDef defines the gradient function of a function defined in -// a function library. -// -// A gradient function g (specified by gradient_func) for a function f -// (specified by function_name) must follow the following: -// -// The function 'f' must be a numerical function which takes N inputs -// and produces M outputs. Its gradient function 'g', which is a -// function taking N + M inputs and produces N outputs. -// -// I.e. if we have -// (y1, y2, ..., y_M) = f(x1, x2, ..., x_N), -// then, g is -// (dL/dx1, dL/dx2, ..., dL/dx_N) = g(x1, x2, ..., x_N, -// dL/dy1, dL/dy2, ..., dL/dy_M), -// where L is a scalar-value function of (x1, x2, ..., xN) (e.g., the -// loss function). dL/dx_i is the partial derivative of L with respect -// to x_i. -message GradientDef { - string function_name = 1; // The function name. - string gradient_func = 2; // The gradient function's name. -} diff --git a/ge/common/proto/tensorflow/graph.proto b/ge/common/proto/tensorflow/graph.proto deleted file mode 100644 index 73bfc6ee..00000000 --- a/ge/common/proto/tensorflow/graph.proto +++ /dev/null @@ -1,64 +0,0 @@ -/** - * This file is part of Open Source Software TensorFlow, version 1.15.0 https://github.com/tensorflow/tensorflow - * - * This file is included by GraphEngine so as to support model format conversion from tensorflow model to GraphEngine model. - * This file in this distribution may have been modified by Huawei Technologies Co., Ltd ("Huawei Modifications"). - * All Huawei Modifications are Copyright 2019-2020 Huawei Technologies Co., Ltd. - */ - -syntax = "proto3"; - -package domi.tensorflow; -option cc_enable_arenas = true; -option java_outer_classname = "GraphProtos"; -option java_multiple_files = true; -option java_package = "org.tensorflow.framework"; - -import "node_def.proto"; -import "function.proto"; -import "versions.proto"; - -// Represents the graph of operations -message GraphDef { - repeated NodeDef node = 1; - - // Compatibility versions of the graph. See core/public/version.h for version - // history. The GraphDef version is distinct from the TensorFlow version, and - // each release of TensorFlow will support a range of GraphDef versions. - VersionDef versions = 4; - - // Deprecated single version field; use versions above instead. Since all - // GraphDef changes before "versions" was introduced were forward - // compatible, this field is entirely ignored. - int32 version = 3 [deprecated = true]; - - // EXPERIMENTAL. DO NOT USE OR DEPEND ON THIS YET. - // - // "library" provides user-defined functions. - // - // Naming: - // * library.function.name are in a flat namespace. - // NOTE: We may need to change it to be hierarchical to support - // different orgs. E.g., - // { "/google/nn", { ... }}, - // { "/google/vision", { ... }} - // { "/org_foo/module_bar", { ... }} - // map named_lib; - // * If node[i].op is the name of one function in "library", - // node[i] is deemed as a function call. Otherwise, node[i].op - // must be a primitive operation supported by the runtime. - // - // - // Function call semantics: - // - // * The callee may start execution as soon as some of its inputs - // are ready. The caller may want to use Tuple() mechanism to - // ensure all inputs are ready in the same time. - // - // * The consumer of return values may start executing as soon as - // the return values the consumer depends on are ready. The - // consumer may want to use Tuple() mechanism to ensure the - // consumer does not start until all return values of the callee - // function are ready. - FunctionDefLibrary library = 2; -}; diff --git a/ge/common/proto/tensorflow/graph_library.proto b/ge/common/proto/tensorflow/graph_library.proto deleted file mode 100644 index 7bca0838..00000000 --- a/ge/common/proto/tensorflow/graph_library.proto +++ /dev/null @@ -1,22 +0,0 @@ -/** - * This file is part of Open Source Software TensorFlow, version 1.15.0 https://github.com/tensorflow/tensorflow - * - * This file is included by GraphEngine so as to support model format conversion from tensorflow model to GraphEngine model. - * This file in this distribution may have been modified by Huawei Technologies Co., Ltd ("Huawei Modifications"). - * All Huawei Modifications are Copyright 2019-2020 Huawei Technologies Co., Ltd. - */ - -syntax = "proto3"; - -package domi.tensorflow; - -import "graph.proto"; - -message GeGraphDef { - string name = 1; - GraphDef graph = 2; -} - -message GraphDefLibrary { - repeated GeGraphDef graph_def = 1; -}; \ No newline at end of file diff --git a/ge/common/proto/tensorflow/node_def.proto b/ge/common/proto/tensorflow/node_def.proto deleted file mode 100644 index 50cf5cac..00000000 --- a/ge/common/proto/tensorflow/node_def.proto +++ /dev/null @@ -1,71 +0,0 @@ -/** - * This file is part of Open Source Software TensorFlow, version 1.15.0 https://github.com/tensorflow/tensorflow - * - * This file is included by GraphEngine so as to support model format conversion from tensorflow model to GraphEngine model. - * This file in this distribution may have been modified by Huawei Technologies Co., Ltd ("Huawei Modifications"). - * All Huawei Modifications are Copyright 2019-2020 Huawei Technologies Co., Ltd. - */ - -syntax = "proto3"; - -package domi.tensorflow; -option cc_enable_arenas = true; -option java_outer_classname = "NodeProto"; -option java_multiple_files = true; -option java_package = "org.tensorflow.framework"; - -import "attr_value.proto"; - -message NodeDef { - // The name given to this operator. Used for naming inputs, - // logging, visualization, etc. Unique within a single GraphDef. - // Must match the regexp "[A-Za-z0-9.][A-Za-z0-9_./]*". - string name = 1; - - // The operation name. There may be custom parameters in attrs. - // Op names starting with an underscore are reserved for internal use. - string op = 2; - - // Each input is "node:src_output" with "node" being a string name and - // "src_output" indicating which output tensor to use from "node". If - // "src_output" is 0 the ":0" suffix can be omitted. Regular inputs - // may optionally be followed by control inputs that have the format - // "^node". - repeated string input = 3; - - // A (possibly partial) specification for the device on which this - // node should be placed. - // The expected syntax for this string is as follows: - // - // DEVICE_SPEC ::= PARTIAL_SPEC - // - // PARTIAL_SPEC ::= ("/" CONSTRAINT) * - // CONSTRAINT ::= ("job:" JOB_NAME) - // | ("replica:" [1-9][0-9]*) - // | ("task:" [1-9][0-9]*) - // | ("device:" [A-Za-z]* ":" ([1-9][0-9]* | "*") ) - // - // Valid values for this string include: - // * "/job:worker/replica:0/task:1/device:GPU:3" (full specification) - // * "/job:worker/device:GPU:3" (partial specification) - // * "" (no specification) - // - // If the constraints do not resolve to a single device (or if this - // field is empty or not present), the runtime will attempt to - // choose a device automatically. - string device = 4; - - // Operation-specific graph-construction-time configuration. - // Note that this should include all attrs defined in the - // corresponding OpDef, including those with a value matching - // the default -- this allows the default to change and makes - // NodeDefs easier to interpret on their own. However, if - // an attr with a default is not specified in this list, the - // default will be used. - // The "names" (keys) must match the regexp "[a-z][a-z0-9_]+" (and - // one of the names from the corresponding OpDef's attr field). - // The values must have a type matching the corresponding OpDef - // attr's type field. - // Add some examples here showing best practices. - map attr = 5; -}; diff --git a/ge/common/proto/tensorflow/op_def.proto b/ge/common/proto/tensorflow/op_def.proto deleted file mode 100644 index 7f0e8ce2..00000000 --- a/ge/common/proto/tensorflow/op_def.proto +++ /dev/null @@ -1,172 +0,0 @@ -/** - * This file is part of Open Source Software TensorFlow, version 1.15.0 https://github.com/tensorflow/tensorflow - * - * This file is included by GraphEngine so as to support model format conversion from tensorflow model to GraphEngine model. - * This file in this distribution may have been modified by Huawei Technologies Co., Ltd ("Huawei Modifications"). - * All Huawei Modifications are Copyright 2019-2020 Huawei Technologies Co., Ltd. - */ - -syntax = "proto3"; - -package domi.tensorflow; -option cc_enable_arenas = true; -option java_outer_classname = "OpDefProtos"; -option java_multiple_files = true; -option java_package = "org.tensorflow.framework"; - -import "attr_value.proto"; -import "types.proto"; - -// Defines an operation. A NodeDef in a GraphDef specifies an Op by -// using the "op" field which should match the name of a OpDef. -// LINT.IfChange -message OpDef { - // Op names starting with an underscore are reserved for internal use. - // Names should be CamelCase and match the regexp "[A-Z][a-zA-Z0-9_]*". - string name = 1; - - // For describing inputs and outputs. - message ArgDef { - // Name for the input/output. Should match the regexp "[a-z][a-z0-9_]*". - string name = 1; - - // Human readable description. - string description = 2; - - // Describes the type of one or more tensors that are accepted/produced - // by this input/output arg. The only legal combinations are: - // * For a single tensor: either the "type" field is set or the - // "type_attr" field is set to the name of an attr with type "type". - // * For a sequence of tensors with the same type: the "number_attr" - // field will be set to the name of an attr with type "int", and - // either the "type" or "type_attr" field will be set as for - // single tensors. - // * For a sequence of tensors, the "type_list_attr" field will be set - // to the name of an attr with type "list(type)". - DataType type = 3; - string type_attr = 4; // if specified, attr must have type "type" - string number_attr = 5; // if specified, attr must have type "int" - // If specified, attr must have type "list(type)", and none of - // type, type_attr, and number_attr may be specified. - string type_list_attr = 6; - - // For inputs: if true, the inputs are required to be refs. - // By default, inputs can be either refs or non-refs. - // For outputs: if true, outputs are refs, otherwise they are not. - bool is_ref = 16; - }; - - // Description of the input(s). - repeated ArgDef input_arg = 2; - - // Description of the output(s). - repeated ArgDef output_arg = 3; - - // Description of the graph-construction-time configuration of this - // Op. That is to say, this describes the attr fields that will - // be specified in the NodeDef. - message AttrDef { - // A descriptive name for the argument. May be used, e.g. by the - // Python client, as a keyword argument name, and so should match - // the regexp "[a-z][a-z0-9_]+". - string name = 1; - - // One of the type names from attr_value.proto ("string", "list(string)", - // "int", etc.). - string type = 2; - - // A reasonable default for this attribute if the user does not supply - // a value. If not specified, the user must supply a value. - AttrValue default_value = 3; - - // Human-readable description. - string description = 4; - - - // --- Constraints --- - // These constraints are only in effect if specified. Default is no - // constraints. - - // For type == "int", this is a minimum value. For "list(___)" - // types, this is the minimum length. - bool has_minimum = 5; - int64 minimum = 6; - - // The set of allowed values. Has type that is the "list" version - // of the "type" field above (uses the "list" field of AttrValue). - // If type == "type" or "list(type)" above, then the "type" field - // of "allowed_values.list" has the set of allowed DataTypes. - // If type == "string" or "list(string)", then the "s" field of - // "allowed_values.list" has the set of allowed strings. - AttrValue allowed_values = 7; - } - repeated AttrDef attr = 4; - - // Optional deprecation based on GraphDef versions. - OpDeprecation deprecation = 8; - - // One-line human-readable description of what the Op does. - string summary = 5; - - // Additional, longer human-readable description of what the Op does. - string description = 6; - - // ------------------------------------------------------------------------- - // Which optimizations this operation can participate in. - - // True if the operation is commutative ("op(a,b) == op(b,a)" for all inputs) - bool is_commutative = 18; - - // If is_aggregate is true, then this operation accepts N >= 2 - // inputs and produces 1 output all of the same type. Should be - // associative and commutative, and produce output with the same - // shape as the input. The optimizer may replace an aggregate op - // taking input from multiple devices with a tree of aggregate ops - // that aggregate locally within each device (and possibly within - // groups of nearby devices) before communicating. - bool is_aggregate = 16; // for things like add - - // Other optimizations go here, like - // can_alias_input, rewrite_when_output_unused, partitioning_strategy, etc. - - // ------------------------------------------------------------------------- - // Optimization constraints. - - // Ops are marked as stateful if their behavior depends on some state beyond - // their input tensors (e.g. variable reading op) or if they have - // a side-effect (e.g. printing or asserting ops). Equivalently, stateless ops - // must always produce the same output for the same input and have - // no side-effects. - // - // By default Ops may be moved between devices. Stateful ops should - // either not be moved, or should only be moved if that state can also - // be moved (e.g. via some sort of save / restore). - // Stateful ops are guaranteed to never be optimized away by Common - // Subexpression Elimination (CSE). - bool is_stateful = 17; // for things like variables, queue - - // ------------------------------------------------------------------------- - // Non-standard options. - - // By default, all inputs to an Op must be initialized Tensors. Ops - // that may initialize tensors for the first time should set this - // field to true, to allow the Op to take an uninitialized Tensor as - // input. - bool allows_uninitialized_input = 19; // for Assign, etc. -}; -// LINT.ThenChange( -// https://www.tensorflow.org/code/tensorflow/core/framework/op_def_util.cc) - -// Information about version-dependent deprecation of an op -message OpDeprecation { - // First GraphDef version at which the op is disallowed. - int32 version = 1; - - // Explanation of why it was deprecated and what to use instead. - string explanation = 2; -}; - -// A collection of OpDefs -message OpList { - repeated OpDef op = 1; -}; diff --git a/ge/common/proto/tensorflow/resource_handle.proto b/ge/common/proto/tensorflow/resource_handle.proto deleted file mode 100644 index 91c46c9a..00000000 --- a/ge/common/proto/tensorflow/resource_handle.proto +++ /dev/null @@ -1,37 +0,0 @@ -/** - * This file is part of Open Source Software TensorFlow, version 1.15.0 https://github.com/tensorflow/tensorflow - * - * This file is included by GraphEngine so as to support model format conversion from tensorflow model to GraphEngine model. - * This file in this distribution may have been modified by Huawei Technologies Co., Ltd ("Huawei Modifications"). - * All Huawei Modifications are Copyright 2019-2020 Huawei Technologies Co., Ltd. - */ - -syntax = "proto3"; - -package domi.tensorflow; -option cc_enable_arenas = true; -option java_outer_classname = "ResourceHandle"; -option java_multiple_files = true; -option java_package = "org.tensorflow.framework"; - -// Protocol buffer representing a handle to a tensorflow resource. Handles are -// not valid across executions, but can be serialized back and forth from within -// a single run. -message ResourceHandleProto { - // Unique name for the device containing the resource. - string device = 1; - - // Container in which this resource is placed. - string container = 2; - - // Unique name of this resource. - string name = 3; - - // Hash code for the type of the resource. Is only valid in the same device - // and in the same execution. - uint64 hash_code = 4; - - // For debug-only, the name of the type pointed to by this handle, if - // available. - string maybe_type_name = 5; -}; diff --git a/ge/common/proto/tensorflow/tensor.proto b/ge/common/proto/tensorflow/tensor.proto deleted file mode 100644 index 48eeb6c4..00000000 --- a/ge/common/proto/tensorflow/tensor.proto +++ /dev/null @@ -1,102 +0,0 @@ -/** - * This file is part of Open Source Software TensorFlow, version 1.15.0 https://github.com/tensorflow/tensorflow - * - * This file is included by GraphEngine so as to support model format conversion from tensorflow model to GraphEngine model. - * This file in this distribution may have been modified by Huawei Technologies Co., Ltd ("Huawei Modifications"). - * All Huawei Modifications are Copyright 2019-2020 Huawei Technologies Co., Ltd. - */ - -syntax = "proto3"; - -package domi.tensorflow; -option cc_enable_arenas = true; -option java_outer_classname = "TensorProtos"; -option java_multiple_files = true; -option java_package = "org.tensorflow.framework"; - -import "resource_handle.proto"; -import "tensor_shape.proto"; -import "types.proto"; - -// Protocol buffer representing a tensor. -message TensorProto { - DataType dtype = 1; - - // Shape of the tensor. - TensorShapeProto tensor_shape = 2; - - // Only one of the representations below is set, one of "tensor_contents" and - // the "xxx_val" attributes. We are not using oneof because as oneofs cannot - // contain repeated fields it would require another extra set of messages. - - // Version number. - // - // In version 0, if the "repeated xxx" representations contain only one - // element, that element is repeated to fill the shape. This makes it easy - // to represent a constant Tensor with a single value. - int32 version_number = 3; - - // Serialized raw tensor content from either Tensor::AsProtoTensorContent or - // memcpy in tensorflow::grpc::EncodeTensorToByteBuffer. This representation - // can be used for all tensor types. The purpose of this representation is to - // reduce serialization overhead during RPC call by avoiding serialization of - // many repeated small items. - bytes tensor_content = 4; - - // Type specific representations that make it easy to create tensor protos in - // all languages. Only the representation corresponding to "dtype" can - // be set. The values hold the flattened representation of the tensor in - // row major order. - - // DT_HALF, DT_BFLOAT16. Note that since protobuf has no int16 type, we'll - // have some pointless zero padding for each value here. - repeated int32 half_val = 13 [packed = true]; - - // DT_FLOAT. - repeated float float_val = 5 [packed = true]; - - // DT_DOUBLE. - repeated double double_val = 6 [packed = true]; - - // DT_INT32, DT_INT16, DT_INT8, DT_UINT8. - repeated int32 int_val = 7 [packed = true]; - - // DT_STRING - repeated bytes string_val = 8; - - // DT_COMPLEX64. scomplex_val(2*i) and scomplex_val(2*i+1) are real - // and imaginary parts of i-th single precision complex. - repeated float scomplex_val = 9 [packed = true]; - - // DT_INT64 - repeated int64 int64_val = 10 [packed = true]; - - // DT_BOOL - repeated bool bool_val = 11 [packed = true]; - - // DT_COMPLEX128. dcomplex_val(2*i) and dcomplex_val(2*i+1) are real - // and imaginary parts of i-th double precision complex. - repeated double dcomplex_val = 12 [packed = true]; - - // DT_RESOURCE - repeated ResourceHandleProto resource_handle_val = 14; - - // DT_VARIANT - repeated VariantTensorDataProto variant_val = 15; - - // DT_UINT32 - repeated uint32 uint32_val = 16 [packed = true]; - - // DT_UINT64 - repeated uint64 uint64_val = 17 [packed = true]; -}; - -// Protocol buffer representing the serialization format of DT_VARIANT tensors. -message VariantTensorDataProto { - // Name of the type of objects being serialized. - string type_name = 1; - // Portions of the object that are not Tensors. - bytes metadata = 2; - // Tensors contained within objects being serialized. - repeated TensorProto tensors = 3; -} diff --git a/ge/common/proto/tensorflow/tensor_shape.proto b/ge/common/proto/tensorflow/tensor_shape.proto deleted file mode 100644 index 3a6d8c5a..00000000 --- a/ge/common/proto/tensorflow/tensor_shape.proto +++ /dev/null @@ -1,53 +0,0 @@ -/** - * This file is part of Open Source Software TensorFlow, version 1.15.0 https://github.com/tensorflow/tensorflow - * - * This file is included by GraphEngine so as to support model format conversion from tensorflow model to GraphEngine model. - * This file in this distribution may have been modified by Huawei Technologies Co., Ltd ("Huawei Modifications"). - * All Huawei Modifications are Copyright 2019-2020 Huawei Technologies Co., Ltd. - */ - -// Protocol buffer representing the shape of tensors. - -syntax = "proto3"; -option cc_enable_arenas = true; -option java_outer_classname = "TensorShapeProtos"; -option java_multiple_files = true; -option java_package = "org.tensorflow.framework"; - -package domi.tensorflow; - -// Dimensions of a tensor. -message TensorShapeProto { - // One dimension of the tensor. - message Dim { - // Size of the tensor in that dimension. - // This value must be >= -1, but values of -1 are reserved for "unknown" - // shapes (values of -1 mean "unknown" dimension). Certain wrappers - // that work with TensorShapeProto may fail at runtime when deserializing - // a TensorShapeProto containing a dim value of -1. - int64 size = 1; - - // Optional name of the tensor dimension. - string name = 2; - }; - - // Dimensions of the tensor, such as {"input", 30}, {"output", 40} - // for a 30 x 40 2D tensor. If an entry has size -1, this - // corresponds to a dimension of unknown size. The names are - // optional. - // - // The order of entries in "dim" matters: It indicates the layout of the - // values in the tensor in-memory representation. - // - // The first entry in "dim" is the outermost dimension used to layout the - // values, the last entry is the innermost dimension. This matches the - // in-memory layout of RowMajor Eigen tensors. - // - // If "dim.size()" > 0, "unknown_rank" must be false. - repeated Dim dim = 2; - - // If true, the number of dimensions in the shape is unknown. - // - // If true, "dim.size()" must be 0. - bool unknown_rank = 3; -}; diff --git a/ge/common/proto/tensorflow/types.proto b/ge/common/proto/tensorflow/types.proto deleted file mode 100644 index f40e49cb..00000000 --- a/ge/common/proto/tensorflow/types.proto +++ /dev/null @@ -1,82 +0,0 @@ -/** - * This file is part of Open Source Software TensorFlow, version 1.15.0 https://github.com/tensorflow/tensorflow - * - * This file is included by GraphEngine so as to support model format conversion from tensorflow model to GraphEngine model. - * This file in this distribution may have been modified by Huawei Technologies Co., Ltd ("Huawei Modifications"). - * All Huawei Modifications are Copyright 2019-2020 Huawei Technologies Co., Ltd. - */ - -syntax = "proto3"; - -package domi.tensorflow; -option cc_enable_arenas = true; -option java_outer_classname = "TypesProtos"; -option java_multiple_files = true; -option java_package = "org.tensorflow.framework"; - -// LINT.IfChange -enum DataType { - // Not a legal value for DataType. Used to indicate a DataType field - // has not been set. - DT_INVALID = 0; - - // Data types that all computation devices are expected to be - // capable to support. - DT_FLOAT = 1; - DT_DOUBLE = 2; - DT_INT32 = 3; - DT_UINT8 = 4; - DT_INT16 = 5; - DT_INT8 = 6; - DT_STRING = 7; - DT_COMPLEX64 = 8; // Single-precision complex - DT_INT64 = 9; - DT_BOOL = 10; - DT_QINT8 = 11; // Quantized int8 - DT_QUINT8 = 12; // Quantized uint8 - DT_QINT32 = 13; // Quantized int32 - DT_BFLOAT16 = 14; // Float32 truncated to 16 bits. Only for cast ops. - DT_QINT16 = 15; // Quantized int16 - DT_QUINT16 = 16; // Quantized uint16 - DT_UINT16 = 17; - DT_COMPLEX128 = 18; // Double-precision complex - DT_HALF = 19; - DT_RESOURCE = 20; - DT_VARIANT = 21; // Arbitrary C++ data types - DT_UINT32 = 22; - DT_UINT64 = 23; - - // Do not use! These are only for parameters. Every enum above - // should have a corresponding value below (verified by types_test). - DT_FLOAT_REF = 101; - DT_DOUBLE_REF = 102; - DT_INT32_REF = 103; - DT_UINT8_REF = 104; - DT_INT16_REF = 105; - DT_INT8_REF = 106; - DT_STRING_REF = 107; - DT_COMPLEX64_REF = 108; - DT_INT64_REF = 109; - DT_BOOL_REF = 110; - DT_QINT8_REF = 111; - DT_QUINT8_REF = 112; - DT_QINT32_REF = 113; - DT_BFLOAT16_REF = 114; - DT_QINT16_REF = 115; - DT_QUINT16_REF = 116; - DT_UINT16_REF = 117; - DT_COMPLEX128_REF = 118; - DT_HALF_REF = 119; - DT_RESOURCE_REF = 120; - DT_VARIANT_REF = 121; - DT_UINT32_REF = 122; - DT_UINT64_REF = 123; -} -// LINT.ThenChange( -// https://www.tensorflow.org/code/tensorflow/c/c_api.h, -// https://www.tensorflow.org/code/tensorflow/go/tensor.go, -// https://www.tensorflow.org/code/tensorflow/core/framework/tensor.cc, -// https://www.tensorflow.org/code/tensorflow/core/framework/types.h, -// https://www.tensorflow.org/code/tensorflow/core/framework/types.cc, -// https://www.tensorflow.org/code/tensorflow/python/framework/dtypes.py, -// https://www.tensorflow.org/code/tensorflow/python/framework/function.py) diff --git a/ge/common/proto/tensorflow/versions.proto b/ge/common/proto/tensorflow/versions.proto deleted file mode 100644 index 4e81548f..00000000 --- a/ge/common/proto/tensorflow/versions.proto +++ /dev/null @@ -1,39 +0,0 @@ -/** - * This file is part of Open Source Software TensorFlow, version 1.15.0 https://github.com/tensorflow/tensorflow - * - * This file is included by GraphEngine so as to support model format conversion from tensorflow model to GraphEngine model. - * This file in this distribution may have been modified by Huawei Technologies Co., Ltd ("Huawei Modifications"). - * All Huawei Modifications are Copyright 2019-2020 Huawei Technologies Co., Ltd. - */ - -syntax = "proto3"; - -package domi.tensorflow; -option cc_enable_arenas = true; -option java_outer_classname = "VersionsProtos"; -option java_multiple_files = true; -option java_package = "org.tensorflow.framework"; - -// Version information for a piece of serialized data -// -// There are different types of versions for each type of data -// (GraphDef, etc.), but they all have the same common shape -// described here. -// -// Each consumer has "consumer" and "min_producer" versions (specified -// elsewhere). A consumer is allowed to consume this data if -// -// producer >= min_producer -// consumer >= min_consumer -// consumer not in bad_consumers -// -message VersionDef { - // The version of the code that produced this data. - int32 producer = 1; - - // Any consumer below this version is not allowed to consume this data. - int32 min_consumer = 2; - - // Specific consumer versions which are disallowed (e.g. due to bugs). - repeated int32 bad_consumers = 3; -}; diff --git a/ge/executor/proto/dump_task.proto b/ge/executor/proto/dump_task.proto deleted file mode 100644 index a2411ddb..00000000 --- a/ge/executor/proto/dump_task.proto +++ /dev/null @@ -1,113 +0,0 @@ -syntax = "proto3"; -package toolkit.dump; - -enum OutputDataType { - DT_UNDEFINED = 0; - DT_FLOAT = 1; - DT_FLOAT16 = 2; - DT_INT8 = 3; - DT_UINT8 = 4; - DT_INT16 = 5; - DT_UINT16 = 6; - DT_INT32 = 7; - DT_INT64 = 8; - DT_UINT32 = 9; - DT_UINT64 = 10; - DT_BOOL = 11; - DT_DOUBLE = 12; - DT_STRING = 13; - DT_DUAL_SUB_INT8 = 14; - DT_DUAL_SUB_UINT8 = 15; - DT_COMPLEX64 = 16; - DT_COMPLEX128 = 17; - DT_QINT8 = 18; - DT_QINT16 = 19; - DT_QINT32 = 20; - DT_QUINT8 = 21; - DT_QUINT16 = 22; - DT_RESOURCE = 23; - DT_STRING_REF = 24; - DT_DUAL = 25; - DT_VARIANT = 26; -} - -enum OutputFormat { - FORMAT_NCHW = 0; - FORMAT_NHWC = 1; - FORMAT_ND = 2; - FORMAT_NC1HWC0 = 3; - FORMAT_FRACTAL_Z = 4; - FORMAT_NC1C0HWPAD = 5; - FORMAT_NHWC1C0 = 6; - FORMAT_FSR_NCHW = 7; - FORMAT_FRACTAL_DECONV = 8; - FORMAT_C1HWNC0 = 9; - FORMAT_FRACTAL_DECONV_TRANSPOSE = 10; - FORMAT_FRACTAL_DECONV_SP_STRIDE_TRANS = 11; - FORMAT_NC1HWC0_C04 = 12; - FORMAT_FRACTAL_Z_C04 = 13; - FORMAT_CHWN = 14; - FORMAT_FRACTAL_DECONV_SP_STRIDE8_TRANS = 15; - FORMAT_HWCN = 16; - FORMAT_NC1KHKWHWC0 = 17; - FORMAT_BN_WEIGHT = 18; - FORMAT_FILTER_HWCK = 19; - FORMAT_HASHTABLE_LOOKUP_LOOKUPS=20; - FORMAT_HASHTABLE_LOOKUP_KEYS = 21; - FORMAT_HASHTABLE_LOOKUP_VALUE = 22; - FORMAT_HASHTABLE_LOOKUP_OUTPUT = 23; - FORMAT_HASHTABLE_LOOKUP_HITS=24; - FORMAT_C1HWNCoC0 = 25; - FORMAT_MD = 26; - FORMAT_NDHWC = 27; - FORMAT_FRACTAL_ZZ = 28; - FORMAT_FRACTAL_NZ = 29; - FORMAT_RESERVED = 30; -} - -message OriginalOp { - string name = 1; - uint32 output_index = 2; - OutputDataType data_type = 3; - OutputFormat format = 4; -} - -message Shape { - repeated uint64 dim = 1; -} - -message OpOutput { - OutputDataType data_type = 1; - OutputFormat format = 2; - Shape shape = 3; - OriginalOp original_op = 4; // the original op corresponding to the output - bytes data = 5; - uint64 size = 6; -} - -message OpInput { - OutputDataType data_type = 1; - OutputFormat format = 2; - Shape shape = 3; - bytes data = 4; - uint64 size = 5; -} - -enum BufferType { - L1 = 0; -} - -message OpBuffer { - BufferType buffer_type = 1; - bytes data = 2; - uint64 size = 3; -} - -message DumpData{ - string version = 1; - uint64 dump_time = 2; - repeated OpOutput output = 3; - repeated OpInput input = 4; - repeated OpBuffer buffer = 5; - string op_name = 6; -} diff --git a/ge/executor/proto/ge_ir.proto b/ge/executor/proto/ge_ir.proto deleted file mode 100644 index c0ef3071..00000000 --- a/ge/executor/proto/ge_ir.proto +++ /dev/null @@ -1,193 +0,0 @@ -syntax = "proto3"; - -package ge.proto; - -enum DataType -{ - DT_UNDEFINED = 0; // Used to indicate a DataType field has not been set. - DT_FLOAT = 1; // float type - DT_FLOAT16 = 2; // fp16 type - DT_INT8 = 3; // int8 type - DT_UINT8 = 4; // uint8 type - DT_INT16 = 5; // int16 type - DT_UINT16 = 6; // uint16 type - DT_INT32 = 7; // - DT_INT64 = 8; // int64 type - DT_UINT32 = 9; // unsigned int32 - DT_UINT64 = 10; // unsigned int64 - DT_BOOL = 11; // bool type - DT_DOUBLE = 12; // double type - DT_STRING = 13; // string type - DT_DUAL_SUB_INT8 = 14; /**< dual output int8 type */ - DT_DUAL_SUB_UINT8 = 15; /**< dual output uint8 type */ - DT_COMPLEX64 = 16; // complex64 type - DT_COMPLEX128 = 17; // complex128 type - DT_QINT8 = 18; // qint8 type - DT_QINT16 = 19; // qint16 type - DT_QINT32 = 20; // qint32 type - DT_QUINT8 = 21; // quint8 type - DT_QUINT16 = 22; // quint16 type - DT_RESOURCE = 23; // resource type - DT_STRING_REF = 24; // string_ref type - DT_DUAL = 25; /**< dual output type */ - DT_VARIANT = 26; // variant type - DT_BF16 = 27; // bf16 type - DT_INT4 = 28; // int4 type -} - -message AttrDef -{ - message ListValue - { - enum ListValueType{ - VT_LIST_NONE = 0; - VT_LIST_STRING = 1; - VT_LIST_INT = 2; - VT_LIST_FLOAT = 3; - VT_LIST_BOOL = 4; - VT_LIST_BYTES = 5; - VT_LIST_TENSOR_DESC = 6; - VT_LIST_TENSOR = 7; - VT_LIST_GRAPH = 8; - VT_LIST_NAMED_ATTRS = 9; - VT_LIST_DATA_TYPE = 10; - } - repeated bytes s = 2; // "list(string)" - repeated int64 i = 3; // "list(int)" - repeated float f = 4; // "list(float)" - repeated bool b = 5; // "list(bool)" - repeated bytes bt = 7; - repeated TensorDescriptor td = 8; - repeated TensorDef t = 9; - repeated GraphDef g = 10; - repeated NamedAttrs na = 11; - repeated int64 dt = 12; // list ge::DataType - - ListValueType val_type = 20; - } - - message ListListInt{ - message ListInt{ - repeated int64 list_i = 1; // list int - } - repeated ListInt list_list_i = 1; // list list int - } - - oneof value - { - bytes s = 2; // "string" - int64 i = 3; // "int" - float f = 4; // "float" - bool b = 5; // "bool" - bytes bt = 7; - ListValue list = 1; // any "list(...)" - NamedAttrs func = 10; // Used to support attr nesting - TensorDescriptor td = 11; // GeTensorDesc type - TensorDef t = 12; // GeTensor type - GraphDef g = 13; // Graph type - ListListInt list_list_int = 14; // List List Int type - int64 dt = 15; // ge::DataType - } -} - -// A list of attr names and their values. The whole list is attached -// with a string name. E.g., MatMul[T=float]. -message NamedAttrs -{ - string name = 1; - map attr = 2; -} - -// Shape / dimension description, using row-major order -message ShapeDef -{ - repeated int64 dim = 1; // Size of each dimension -} - -// Multidimensional data description -message TensorDescriptor -{ - string name = 1; // Optional parameter, tensor name - - DataType dtype = 2; // tensor datatype - ShapeDef shape = 3; // Shape / dimension - string layout = 4; // Tensor format, eg: "NCHW", "NHWC", "CHW", "ND" - - bool has_out_attr = 9; - int64 size = 10; - int64 weight_size = 11; - bool reuse_input = 12; - bool output_tensor = 13; - string device_type = 14; - bool input_tensor =15; - int64 real_dim_cnt = 16; - int64 reuse_input_index = 17; - int64 data_offset = 18; - int64 cmps_size = 19; - string cmps_tab = 20; - int64 cmps_tab_offset = 21; - - map attr = 5; // Set of extra parameter fields -} - -// GeTensor definition -message TensorDef -{ - TensorDescriptor desc = 1; // Tensor description - bytes data = 2; // Tensor data -} - - -// Operator description -message OpDef -{ - string name = 1; // name - string type = 2; // type - - repeated string input = 5; // input original op name + outgoing index. op_name锛歩ndex - - map attr = 10; // Set of operator parameter fields - - bool has_out_attr = 20; - int64 id = 21; - int64 stream_id =22; - repeated string input_name = 23; - repeated string src_name = 24; - repeated int64 src_index = 25; - repeated string dst_name = 26; - repeated int64 dst_index = 27; - repeated int64 input_i = 28; - repeated int64 output_i = 29; - repeated int64 workspace = 30; - repeated int64 workspace_bytes = 31; - repeated bool is_input_const = 32; - repeated TensorDescriptor input_desc = 33; - repeated TensorDescriptor output_desc = 34; - repeated string subgraph_name = 35; -} - -// Graph definition -message GraphDef -{ - string name = 1; // name - - repeated string input = 4; // Graph input - repeated string output = 5; // Graph output - - repeated OpDef op = 6; // List of operators - - map attr = 11; // Extended field -} - -// model definition -message ModelDef -{ - string name = 1; // name - uint32 version = 2; // IR Proto verion - string custom_version = 3; // User model version number, passed in by user - - repeated GraphDef graph = 7; // Graph definition锛実raph[0] represents the main diagram in modeldef - - map attr = 11; // Extended field -} - diff --git a/ge/executor/proto/insert_op.proto b/ge/executor/proto/insert_op.proto deleted file mode 100644 index 7d708865..00000000 --- a/ge/executor/proto/insert_op.proto +++ /dev/null @@ -1,140 +0,0 @@ -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; - - // related_input_name is optional and the top name of data node which inserts aipp - string related_input_name = 6; - - // 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; - float padding_value = 72; - - 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 -} diff --git a/ge/executor/proto/om.proto b/ge/executor/proto/om.proto deleted file mode 100644 index e15e5f80..00000000 --- a/ge/executor/proto/om.proto +++ /dev/null @@ -1,396 +0,0 @@ -/* Copyright (C) 2018. Huawei Technologies Co., Ltd. All rights reserved. - * - * This program is free software; you can redistribute it and/or modify - * it under the terms of the Apache License Version 2.0.You may not use this file except in compliance with the License. - * - * This program is distributed in the hope that it will be useful, - * but WITHOUT ANY WARRANTY; without even the implied warranty of - * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - * Apache License for more details at - * http://www.apache.org/licenses/LICENSE-2.0 - */ -syntax = "proto3"; - -package domi; - -enum TargetType -{ - MINI = 0; - TINY = 1; - LITE = 2; -} - -// offline model -message ModelDef { - string name = 1; - uint32 version = 2; - - uint64 memory_size = 10; - uint32 stream_num = 11; - uint32 event_num = 12; - uint64 weight_size = 13; - uint32 label_num = 15; - repeated OpDef op = 20; - TargetType target_type = 23; - - map attr = 30; -}; - -// operator define -message OpDef { - string name = 1; - string type = 2; - - uint32 id = 3; - uint32 stream_id = 4; - - repeated string input_name = 5; - - repeated string src_name = 8; - repeated int32 src_index = 9; - repeated int64 input = 10; - repeated int64 output = 11; - repeated TensorDescriptor input_desc = 12; - repeated TensorDescriptor output_desc = 13; - repeated WeightDef weights = 14; - repeated string dst_name = 15; - repeated int32 dst_index = 16; - - repeated int64 workspace = 20; - repeated uint32 workspace_bytes = 21; - - repeated string weight_name = 22; - repeated bool is_input_const = 23; - - map attr = 30; - - QuantizeFactorParams quantize_factor = 31; - - oneof op_params { - // start at 100 here - SendOpParams sender_param = 100; - RecvOpParams receiver_param = 200; - ConvolutionOpParams convolution_param = 300; - PoolingOpParams pooling_param = 400; - EltwiseOpParams eltwise_param = 500; - BatchNormOpParams batchnorm_param = 600; - ScaleOpParams scale_param = 700; - FullConnectionOpParams full_connection_param = 800; - SoftmaxOpParams softmax_param = 900; - ActivationOpParams activation_param = 1000; - ReshapeOpParams reshape_param = 1100; - } -}; - -message SendOpParams { - uint32 event_id = 1; -}; - -message RecvOpParams { - uint32 event_id = 1; -}; - -enum QuantizeScaleType -{ - VECTOR_SCALE = 0; - SCALAR_SCALE = 1; -} - -enum QuantizeScaleMode -{ - NORMAL_MODE = 0; - SQRT_MODE = 1; -} - -enum QuantizeAlgorithm -{ - NON_OFFSET_ALGO = 0; - HALF_OFFSET_ALGO = 1; - ALL_OFFSET_ALGO = 2; -} -message QuantizeFactor -{ - QuantizeScaleMode scale_mode = 1; - bytes scale_value = 2; - int64 scale_offset = 3; - bytes offset_data_value = 4; - int64 offset_data_offset = 5; - bytes offset_weight_value = 6; - int64 offset_weight_offset = 7; - bytes offset_pad_value = 8; - int64 offset_pad_offset = 9; -}; - -message QuantizeCalcFactor -{ - bytes offsetw = 1; - int64 offsetw_offset = 2; - bytes offsetd = 3; - int64 offsetd_offset = 4; - bytes scalereq = 5; - int64 scaledreq_offset = 6; - bytes offsetdnext = 7; - int64 offsetdnext_offset = 8; -} - -message QuantizeFactorParams -{ - QuantizeAlgorithm quantize_algo = 1; - QuantizeScaleType scale_type = 2; - QuantizeFactor quantize_param = 3; - QuantizeFactor dequantize_param = 4; - QuantizeFactor requantize_param = 5; - QuantizeCalcFactor quantizecalc_param = 6; -}; - -message ConvolutionOpParams { - int32 mode = 1; - int32 algo = 2; - int32 pad_mode = 3; - uint32 group = 4; - uint32 num_output = 5; - - repeated uint32 pad = 10; - repeated uint32 stride = 11; - repeated uint32 dilation = 12; - repeated uint32 kernel = 13; - - float alpha = 20; - float beta = 21; - - WeightDef filter = 40; - WeightDef bias = 41; - - bool relu_flag = 62; - repeated uint32 adj = 70; - repeated uint32 target_shape = 71; - repeated uint32 before_pad = 72; -}; - -message PoolingOpParams { - int32 mode = 1; - int32 nan_opt = 2; - int32 pad_mode = 3; - bool global_pooling = 4; - - repeated uint32 window = 10; - repeated uint32 pad = 11; - repeated uint32 stride = 12; - bool ceil_mode = 13; - int32 data_mode = 14; - - float alpha = 20; - float beta = 21; - repeated uint32 before_pad = 22; -}; - -message EltwiseOpParams { - int32 mode = 1; - repeated float coeff = 2; - float alpha = 3; - float beta = 4; - repeated WeightDef weight = 5; - bool relu_flag = 6; -}; - -message ActivationOpParams { - int32 mode = 1; - float coef = 2; - float alpha = 3; - float beta = 4; -}; - -message BatchNormOpParams { - int32 mode = 1; - - float alpha = 2; - float beta = 3; - double epsilon = 4;//optinal,[default = 1e-5] - bool use_global_stats = 5; //optinal,by default true,testing mode - float moving_average_fraction = 6; //optinal,[default = .999]; - - WeightDef estimated_mean = 7; - WeightDef estimated_variance = 8; - - WeightDef scale = 9; - WeightDef bias = 10; -}; - -message ScaleOpParams { - WeightDef scale = 1; - WeightDef bias = 2; -}; - -message ReshapeOpParams { - float alpha = 1; - float beta = 2; - ShapeDef shape = 3; - int32 axis = 4; - int32 num_axes = 5; - int32 format = 6; -}; - -message SoftmaxOpParams { - int32 algo = 1; - int32 mode = 2; - float alpha = 3; - float beta = 4; -}; - -message FullConnectionOpParams { - WeightDef filter = 1; - WeightDef bias = 2; - uint32 num_output = 3; - bool relu_flag = 12; -}; - -message FlattenOpParams { - float alpha = 1; - float beta = 2; - int32 start_axis = 3; - int32 end_axis = 4; -} - -message AddLimitedOpParams { - float alpha = 1; - float beta = 2; - int32 axis = 3; - bool broadcast = 4; - - repeated WeightDef weight = 10; -}; - -message MulLimitedOpParams { - float alpha = 1; - float beta = 2; - int32 axis = 3; - bool broadcast = 4; - - repeated WeightDef weight = 10; -}; - -message AddOpParams { - float alpha = 1; - float beta = 2; - - repeated WeightDef weight = 10; -}; - -message MulOpParams { - float alpha = 1; - float beta = 2; - - repeated WeightDef weight = 10; -}; - -message SubOpParams { - float alpha = 1; - float beta = 2; - - repeated WeightDef weight = 10; -}; - -message BiasAddOpParams { - float alpha = 1; - float beta = 2; - - WeightDef bias = 10; -}; - -message MatMulOpParams { - float alpha = 1; - float beta = 2; - bool transposeX = 3; - bool transposeW = 4; - - WeightDef filter = 10; - WeightDef bias = 12; -}; - -message RsqrtOpParams { - float alpha = 1; - float beta = 2; -}; - - -message WeightDef { - int32 format = 1; - int32 data_type = 2; - ShapeDef shape = 3; - bytes data = 4; - int64 data_offset = 5; - uint32 cmps_size = 6; - bytes cmps_tab = 7; - int64 cmps_tab_offset = 10; - CompressInfo cmps_info = 8; - AllOffsetQuantizeInfo alloffset_quantize_info = 11; -} - -message ShapeDef { - repeated int64 dim = 1; -} - -enum DeviceType { - NPU = 0; // In default, we will use NPU. - CPU = 1; // CPU -} - -message AllOffsetQuantizeInfo { - float scale = 1; - int32 offset = 2; -} - -message TensorDescriptor { - int32 format = 1; - int32 data_type = 2; - repeated int64 dim = 3; - uint32 size = 4; - bool reuse_input = 5; - bool output_tensor = 7; - DeviceType device_type = 8; - bool input_tensor = 9; - uint32 real_dim_cnt = 10; - uint32 reuse_input_index = 11; - AllOffsetQuantizeInfo alloffset_quantize_info = 12; -} - -message CompressInfo { - int32 blockRow = 1; // block row - int32 blockCol = 2; // block col - int32 fractalK = 3; // fractal K - int32 fractalN = 4; // fractal N - int32 lastFractalK = 5; // K of last fractal - int32 lastFractalN = 6; // N of last fractal - int32 cubeSize = 7; // cube's length - int32 loadDir = 8; // data load directtiono 0:col load 1:row load -} - -message AttrDef { - message ListValue { - repeated string s = 2; // "list(string)" - repeated int64 i = 3 [packed = true]; // "list(int)" - repeated float f = 4 [packed = true]; // "list(float)" - repeated bool b = 5 [packed = true]; // "list(bool)" - repeated uint32 u = 6 [packed = true]; // "list(uint)" - repeated bytes bt = 7; - } - - oneof value { - string s = 2; // "string" - int64 i = 3; // "int" - float f = 4; // "float" - bool b = 5; // "bool" - uint32 u = 6; // "uint32" - bytes bt = 7; - ListValue list = 1; // any "list(...)" - NamedAttrs func = 10; - } -} - -// A list of attr names and their values. The whole list is attached -// with a string name. E.g., MatMul[T=float]. -message NamedAttrs { - string name = 1; - map attr = 2; -} - diff --git a/ge/executor/proto/op_mapping.proto b/ge/executor/proto/op_mapping.proto deleted file mode 100644 index d626eb49..00000000 --- a/ge/executor/proto/op_mapping.proto +++ /dev/null @@ -1,75 +0,0 @@ -syntax = "proto3"; -package toolkit.aicpu.dump; - -message Shape { - repeated uint64 dim = 1; -} - -message Output { - int32 data_type = 1; - int32 format = 2; - Shape shape = 3; - uint64 address = 4; - string original_name = 5; - int32 original_output_index = 6; - int32 original_output_data_type = 7; - int32 original_output_format = 8; - uint64 size = 9; - Shape origin_shape = 10; -} - -message Input { - int32 data_type =1; - int32 format = 2; - Shape shape = 3; - uint64 address = 4; - uint64 size = 5; - Shape origin_shape = 6; -} - -enum BufferType { - L1 = 0; -} - -message OpBuffer { - BufferType buffer_type = 1; - uint64 address = 2; - uint64 size = 3; -} - -message Op { - string op_name = 1; - string op_type = 2; -} - -message Task { - uint32 task_id = 1; - uint32 stream_id = 2; - Op op = 3; - repeated Output output = 4; - bool end_graph = 5; - repeated Input input = 6; - repeated OpBuffer buffer = 7; -} - -message OpMappingInfo { - string dump_path = 1; - oneof model_name_param { - string model_name = 2; - } - oneof model_id_param { - uint32 model_id = 3; - } - oneof step_id { - uint64 step_id_addr = 4; - } - oneof iterations_per_loop { - uint64 iterations_per_loop_addr = 5; - } - oneof loop_cond { - uint64 loop_cond_addr = 6; - } - uint32 flag = 7; // 0x01 load, 0x00 unload - repeated Task task = 8; - string dump_step = 9; -} \ No newline at end of file diff --git a/ge/executor/proto/task.proto b/ge/executor/proto/task.proto deleted file mode 100644 index 0da5631e..00000000 --- a/ge/executor/proto/task.proto +++ /dev/null @@ -1,179 +0,0 @@ -/* Copyright (C) 2018. Huawei Technologies Co., Ltd. All rights reserved. - * - * This program is free software; you can redistribute it and/or modify - * it under the terms of the Apache License Version 2.0.You may not use this file except in compliance with the License. - * - * This program is distributed in the hope that it will be useful, - * but WITHOUT ANY WARRANTY; without even the implied warranty of - * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - * Apache License for more details at - * http://www.apache.org/licenses/LICENSE-2.0 - */ -syntax = "proto3"; - -package domi; - -message ModelTaskDef { - string version = 1; - - map attr = 9; // Extended field - repeated TaskDef task = 10; - - uint64 memory_size = 11; - uint32 stream_num = 12; - uint32 event_num = 13; - uint64 weight_size = 14; - - repeated bytes op = 15; // input/output opdef in bytes - - uint64 base_addr = 16; // base addr - uint64 weight_addr = 17; // weight addr - uint32 batch_num = 18; -} - - -message TaskDef { - uint32 id = 1; - uint32 type = 2; - - uint32 stream_id = 10; - uint32 event_id = 11; - - KernelDef kernel = 20; - KernelExDef kernel_ex = 21; - KernelHcclDef kernel_hccl = 25; - EventExDef event_ex = 26; - LogTimeStampDef log_timestamp = 28; - - uint32 label_id = 30; - - MemcpyAsyncDef memcpy_async = 31; - StreamSwitchDef stream_switch = 32; - StreamActiveDef stream_active = 33; - bytes private_def = 34; - uint64 ops_kernel_store_ptr = 35; // adjustments to other fields in the future - StreamSwitchNDef stream_switch_n = 36; - - LabelSetDef label_set = 37; - LabelGotoExDef label_goto_ex = 38; - LabelSwitchByIndexDef label_switch_by_index = 39; - KernelDefWithHandle kernel_with_handle = 40; -} - -message KernelDef { - KernelContext context = 1; - - string stub_func = 10; - uint32 block_dim = 11; - uint32 args_size = 12; - bytes args = 13; - bytes sm_desc = 14; - bytes flowtable = 15; - string so_name = 16; - string kernel_name = 17; - bytes kernel_ext_info = 18; - uint32 kernel_ext_info_size = 19; -} - -message KernelDefWithHandle { - KernelContext context = 1; - - uint64 handle = 10; - string dev_func = 11; - uint32 block_dim = 12; - uint32 args_size = 13; - bytes args = 14; - bytes sm_desc = 15; - string original_kernel_key = 16; - string node_info = 17; -} - -message KernelContext { - uint32 kernel_type = 1; - uint32 op_id = 2; // OP type in CCE - uint32 kernel_func_id = 3; - uint32 op_index = 4; // TE/Custom operator - bool is_flowtable = 5; // Identify whether args is a flowtable structure - bytes args_offset = 6; // args offset information - uint32 args_count = 7; // args count - repeated uint32 origin_op_index = 8; -} - - -message KernelExDef { - uint32 flags = 1; - - uint32 op_index = 4; - uint32 args_size = 12; - bytes args = 13; - bytes task_info = 14; // serialized nodeDef, funcDef, inputoutput - uint32 task_info_size = 15; - bytes kernel_ext_info = 16; - uint32 kernel_ext_info_size = 17; -} - - -message KernelHcclDef { - uint32 op_index = 8; - string hccl_type = 9; -} - - -message EventExDef { - uint32 op_index = 1; - uint32 event_type = 2; -} - -message LogTimeStampDef { - uint64 logid = 1; - bool notify = 2; - uint32 flat = 3; -} - -message MemcpyAsyncDef { - uint64 dst = 1; - uint64 dst_max = 2; - uint64 src = 3; - uint64 count = 4; - uint32 kind = 5; - uint32 op_index = 6; -} - -message StreamSwitchDef { - uint32 op_index = 1; - uint32 true_stream_id = 2; - int64 value = 3; - uint64 value_ptr = 4; - uint32 data_type = 5; -} - -message StreamActiveDef { - uint32 op_index = 1; - uint32 active_stream_id = 2; -} - -message StreamSwitchNDef { - uint32 op_index = 1; - uint32 size = 2; - repeated int64 target_value = 3; - repeated uint32 true_stream_id = 4; - uint32 element_size = 5; - uint32 data_type = 6; -} - -message LabelSetDef { - uint32 op_index = 1; - uint32 label_id = 2; - uint32 model_id = 3; -} - -message LabelGotoExDef { - uint32 op_index = 1; - uint32 label_id = 2; - uint32 model_id = 3; -} - -message LabelSwitchByIndexDef { - uint32 op_index = 1; - uint32 label_max = 2; -} diff --git a/ge/ge_local_engine/proto/task.proto b/ge/ge_local_engine/proto/task.proto deleted file mode 100644 index 0da5631e..00000000 --- a/ge/ge_local_engine/proto/task.proto +++ /dev/null @@ -1,179 +0,0 @@ -/* Copyright (C) 2018. Huawei Technologies Co., Ltd. All rights reserved. - * - * This program is free software; you can redistribute it and/or modify - * it under the terms of the Apache License Version 2.0.You may not use this file except in compliance with the License. - * - * This program is distributed in the hope that it will be useful, - * but WITHOUT ANY WARRANTY; without even the implied warranty of - * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - * Apache License for more details at - * http://www.apache.org/licenses/LICENSE-2.0 - */ -syntax = "proto3"; - -package domi; - -message ModelTaskDef { - string version = 1; - - map attr = 9; // Extended field - repeated TaskDef task = 10; - - uint64 memory_size = 11; - uint32 stream_num = 12; - uint32 event_num = 13; - uint64 weight_size = 14; - - repeated bytes op = 15; // input/output opdef in bytes - - uint64 base_addr = 16; // base addr - uint64 weight_addr = 17; // weight addr - uint32 batch_num = 18; -} - - -message TaskDef { - uint32 id = 1; - uint32 type = 2; - - uint32 stream_id = 10; - uint32 event_id = 11; - - KernelDef kernel = 20; - KernelExDef kernel_ex = 21; - KernelHcclDef kernel_hccl = 25; - EventExDef event_ex = 26; - LogTimeStampDef log_timestamp = 28; - - uint32 label_id = 30; - - MemcpyAsyncDef memcpy_async = 31; - StreamSwitchDef stream_switch = 32; - StreamActiveDef stream_active = 33; - bytes private_def = 34; - uint64 ops_kernel_store_ptr = 35; // adjustments to other fields in the future - StreamSwitchNDef stream_switch_n = 36; - - LabelSetDef label_set = 37; - LabelGotoExDef label_goto_ex = 38; - LabelSwitchByIndexDef label_switch_by_index = 39; - KernelDefWithHandle kernel_with_handle = 40; -} - -message KernelDef { - KernelContext context = 1; - - string stub_func = 10; - uint32 block_dim = 11; - uint32 args_size = 12; - bytes args = 13; - bytes sm_desc = 14; - bytes flowtable = 15; - string so_name = 16; - string kernel_name = 17; - bytes kernel_ext_info = 18; - uint32 kernel_ext_info_size = 19; -} - -message KernelDefWithHandle { - KernelContext context = 1; - - uint64 handle = 10; - string dev_func = 11; - uint32 block_dim = 12; - uint32 args_size = 13; - bytes args = 14; - bytes sm_desc = 15; - string original_kernel_key = 16; - string node_info = 17; -} - -message KernelContext { - uint32 kernel_type = 1; - uint32 op_id = 2; // OP type in CCE - uint32 kernel_func_id = 3; - uint32 op_index = 4; // TE/Custom operator - bool is_flowtable = 5; // Identify whether args is a flowtable structure - bytes args_offset = 6; // args offset information - uint32 args_count = 7; // args count - repeated uint32 origin_op_index = 8; -} - - -message KernelExDef { - uint32 flags = 1; - - uint32 op_index = 4; - uint32 args_size = 12; - bytes args = 13; - bytes task_info = 14; // serialized nodeDef, funcDef, inputoutput - uint32 task_info_size = 15; - bytes kernel_ext_info = 16; - uint32 kernel_ext_info_size = 17; -} - - -message KernelHcclDef { - uint32 op_index = 8; - string hccl_type = 9; -} - - -message EventExDef { - uint32 op_index = 1; - uint32 event_type = 2; -} - -message LogTimeStampDef { - uint64 logid = 1; - bool notify = 2; - uint32 flat = 3; -} - -message MemcpyAsyncDef { - uint64 dst = 1; - uint64 dst_max = 2; - uint64 src = 3; - uint64 count = 4; - uint32 kind = 5; - uint32 op_index = 6; -} - -message StreamSwitchDef { - uint32 op_index = 1; - uint32 true_stream_id = 2; - int64 value = 3; - uint64 value_ptr = 4; - uint32 data_type = 5; -} - -message StreamActiveDef { - uint32 op_index = 1; - uint32 active_stream_id = 2; -} - -message StreamSwitchNDef { - uint32 op_index = 1; - uint32 size = 2; - repeated int64 target_value = 3; - repeated uint32 true_stream_id = 4; - uint32 element_size = 5; - uint32 data_type = 6; -} - -message LabelSetDef { - uint32 op_index = 1; - uint32 label_id = 2; - uint32 model_id = 3; -} - -message LabelGotoExDef { - uint32 op_index = 1; - uint32 label_id = 2; - uint32 model_id = 3; -} - -message LabelSwitchByIndexDef { - uint32 op_index = 1; - uint32 label_max = 2; -} diff --git a/ge/offline/proto/ge_ir.proto b/ge/offline/proto/ge_ir.proto deleted file mode 100644 index c0ef3071..00000000 --- a/ge/offline/proto/ge_ir.proto +++ /dev/null @@ -1,193 +0,0 @@ -syntax = "proto3"; - -package ge.proto; - -enum DataType -{ - DT_UNDEFINED = 0; // Used to indicate a DataType field has not been set. - DT_FLOAT = 1; // float type - DT_FLOAT16 = 2; // fp16 type - DT_INT8 = 3; // int8 type - DT_UINT8 = 4; // uint8 type - DT_INT16 = 5; // int16 type - DT_UINT16 = 6; // uint16 type - DT_INT32 = 7; // - DT_INT64 = 8; // int64 type - DT_UINT32 = 9; // unsigned int32 - DT_UINT64 = 10; // unsigned int64 - DT_BOOL = 11; // bool type - DT_DOUBLE = 12; // double type - DT_STRING = 13; // string type - DT_DUAL_SUB_INT8 = 14; /**< dual output int8 type */ - DT_DUAL_SUB_UINT8 = 15; /**< dual output uint8 type */ - DT_COMPLEX64 = 16; // complex64 type - DT_COMPLEX128 = 17; // complex128 type - DT_QINT8 = 18; // qint8 type - DT_QINT16 = 19; // qint16 type - DT_QINT32 = 20; // qint32 type - DT_QUINT8 = 21; // quint8 type - DT_QUINT16 = 22; // quint16 type - DT_RESOURCE = 23; // resource type - DT_STRING_REF = 24; // string_ref type - DT_DUAL = 25; /**< dual output type */ - DT_VARIANT = 26; // variant type - DT_BF16 = 27; // bf16 type - DT_INT4 = 28; // int4 type -} - -message AttrDef -{ - message ListValue - { - enum ListValueType{ - VT_LIST_NONE = 0; - VT_LIST_STRING = 1; - VT_LIST_INT = 2; - VT_LIST_FLOAT = 3; - VT_LIST_BOOL = 4; - VT_LIST_BYTES = 5; - VT_LIST_TENSOR_DESC = 6; - VT_LIST_TENSOR = 7; - VT_LIST_GRAPH = 8; - VT_LIST_NAMED_ATTRS = 9; - VT_LIST_DATA_TYPE = 10; - } - repeated bytes s = 2; // "list(string)" - repeated int64 i = 3; // "list(int)" - repeated float f = 4; // "list(float)" - repeated bool b = 5; // "list(bool)" - repeated bytes bt = 7; - repeated TensorDescriptor td = 8; - repeated TensorDef t = 9; - repeated GraphDef g = 10; - repeated NamedAttrs na = 11; - repeated int64 dt = 12; // list ge::DataType - - ListValueType val_type = 20; - } - - message ListListInt{ - message ListInt{ - repeated int64 list_i = 1; // list int - } - repeated ListInt list_list_i = 1; // list list int - } - - oneof value - { - bytes s = 2; // "string" - int64 i = 3; // "int" - float f = 4; // "float" - bool b = 5; // "bool" - bytes bt = 7; - ListValue list = 1; // any "list(...)" - NamedAttrs func = 10; // Used to support attr nesting - TensorDescriptor td = 11; // GeTensorDesc type - TensorDef t = 12; // GeTensor type - GraphDef g = 13; // Graph type - ListListInt list_list_int = 14; // List List Int type - int64 dt = 15; // ge::DataType - } -} - -// A list of attr names and their values. The whole list is attached -// with a string name. E.g., MatMul[T=float]. -message NamedAttrs -{ - string name = 1; - map attr = 2; -} - -// Shape / dimension description, using row-major order -message ShapeDef -{ - repeated int64 dim = 1; // Size of each dimension -} - -// Multidimensional data description -message TensorDescriptor -{ - string name = 1; // Optional parameter, tensor name - - DataType dtype = 2; // tensor datatype - ShapeDef shape = 3; // Shape / dimension - string layout = 4; // Tensor format, eg: "NCHW", "NHWC", "CHW", "ND" - - bool has_out_attr = 9; - int64 size = 10; - int64 weight_size = 11; - bool reuse_input = 12; - bool output_tensor = 13; - string device_type = 14; - bool input_tensor =15; - int64 real_dim_cnt = 16; - int64 reuse_input_index = 17; - int64 data_offset = 18; - int64 cmps_size = 19; - string cmps_tab = 20; - int64 cmps_tab_offset = 21; - - map attr = 5; // Set of extra parameter fields -} - -// GeTensor definition -message TensorDef -{ - TensorDescriptor desc = 1; // Tensor description - bytes data = 2; // Tensor data -} - - -// Operator description -message OpDef -{ - string name = 1; // name - string type = 2; // type - - repeated string input = 5; // input original op name + outgoing index. op_name锛歩ndex - - map attr = 10; // Set of operator parameter fields - - bool has_out_attr = 20; - int64 id = 21; - int64 stream_id =22; - repeated string input_name = 23; - repeated string src_name = 24; - repeated int64 src_index = 25; - repeated string dst_name = 26; - repeated int64 dst_index = 27; - repeated int64 input_i = 28; - repeated int64 output_i = 29; - repeated int64 workspace = 30; - repeated int64 workspace_bytes = 31; - repeated bool is_input_const = 32; - repeated TensorDescriptor input_desc = 33; - repeated TensorDescriptor output_desc = 34; - repeated string subgraph_name = 35; -} - -// Graph definition -message GraphDef -{ - string name = 1; // name - - repeated string input = 4; // Graph input - repeated string output = 5; // Graph output - - repeated OpDef op = 6; // List of operators - - map attr = 11; // Extended field -} - -// model definition -message ModelDef -{ - string name = 1; // name - uint32 version = 2; // IR Proto verion - string custom_version = 3; // User model version number, passed in by user - - repeated GraphDef graph = 7; // Graph definition锛実raph[0] represents the main diagram in modeldef - - map attr = 11; // Extended field -} - diff --git a/ge/offline/proto/insert_op.proto b/ge/offline/proto/insert_op.proto deleted file mode 100644 index 7d708865..00000000 --- a/ge/offline/proto/insert_op.proto +++ /dev/null @@ -1,140 +0,0 @@ -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; - - // related_input_name is optional and the top name of data node which inserts aipp - string related_input_name = 6; - - // 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; - float padding_value = 72; - - 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 -} diff --git a/ge/offline/proto/om.proto b/ge/offline/proto/om.proto deleted file mode 100644 index e15e5f80..00000000 --- a/ge/offline/proto/om.proto +++ /dev/null @@ -1,396 +0,0 @@ -/* Copyright (C) 2018. Huawei Technologies Co., Ltd. All rights reserved. - * - * This program is free software; you can redistribute it and/or modify - * it under the terms of the Apache License Version 2.0.You may not use this file except in compliance with the License. - * - * This program is distributed in the hope that it will be useful, - * but WITHOUT ANY WARRANTY; without even the implied warranty of - * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - * Apache License for more details at - * http://www.apache.org/licenses/LICENSE-2.0 - */ -syntax = "proto3"; - -package domi; - -enum TargetType -{ - MINI = 0; - TINY = 1; - LITE = 2; -} - -// offline model -message ModelDef { - string name = 1; - uint32 version = 2; - - uint64 memory_size = 10; - uint32 stream_num = 11; - uint32 event_num = 12; - uint64 weight_size = 13; - uint32 label_num = 15; - repeated OpDef op = 20; - TargetType target_type = 23; - - map attr = 30; -}; - -// operator define -message OpDef { - string name = 1; - string type = 2; - - uint32 id = 3; - uint32 stream_id = 4; - - repeated string input_name = 5; - - repeated string src_name = 8; - repeated int32 src_index = 9; - repeated int64 input = 10; - repeated int64 output = 11; - repeated TensorDescriptor input_desc = 12; - repeated TensorDescriptor output_desc = 13; - repeated WeightDef weights = 14; - repeated string dst_name = 15; - repeated int32 dst_index = 16; - - repeated int64 workspace = 20; - repeated uint32 workspace_bytes = 21; - - repeated string weight_name = 22; - repeated bool is_input_const = 23; - - map attr = 30; - - QuantizeFactorParams quantize_factor = 31; - - oneof op_params { - // start at 100 here - SendOpParams sender_param = 100; - RecvOpParams receiver_param = 200; - ConvolutionOpParams convolution_param = 300; - PoolingOpParams pooling_param = 400; - EltwiseOpParams eltwise_param = 500; - BatchNormOpParams batchnorm_param = 600; - ScaleOpParams scale_param = 700; - FullConnectionOpParams full_connection_param = 800; - SoftmaxOpParams softmax_param = 900; - ActivationOpParams activation_param = 1000; - ReshapeOpParams reshape_param = 1100; - } -}; - -message SendOpParams { - uint32 event_id = 1; -}; - -message RecvOpParams { - uint32 event_id = 1; -}; - -enum QuantizeScaleType -{ - VECTOR_SCALE = 0; - SCALAR_SCALE = 1; -} - -enum QuantizeScaleMode -{ - NORMAL_MODE = 0; - SQRT_MODE = 1; -} - -enum QuantizeAlgorithm -{ - NON_OFFSET_ALGO = 0; - HALF_OFFSET_ALGO = 1; - ALL_OFFSET_ALGO = 2; -} -message QuantizeFactor -{ - QuantizeScaleMode scale_mode = 1; - bytes scale_value = 2; - int64 scale_offset = 3; - bytes offset_data_value = 4; - int64 offset_data_offset = 5; - bytes offset_weight_value = 6; - int64 offset_weight_offset = 7; - bytes offset_pad_value = 8; - int64 offset_pad_offset = 9; -}; - -message QuantizeCalcFactor -{ - bytes offsetw = 1; - int64 offsetw_offset = 2; - bytes offsetd = 3; - int64 offsetd_offset = 4; - bytes scalereq = 5; - int64 scaledreq_offset = 6; - bytes offsetdnext = 7; - int64 offsetdnext_offset = 8; -} - -message QuantizeFactorParams -{ - QuantizeAlgorithm quantize_algo = 1; - QuantizeScaleType scale_type = 2; - QuantizeFactor quantize_param = 3; - QuantizeFactor dequantize_param = 4; - QuantizeFactor requantize_param = 5; - QuantizeCalcFactor quantizecalc_param = 6; -}; - -message ConvolutionOpParams { - int32 mode = 1; - int32 algo = 2; - int32 pad_mode = 3; - uint32 group = 4; - uint32 num_output = 5; - - repeated uint32 pad = 10; - repeated uint32 stride = 11; - repeated uint32 dilation = 12; - repeated uint32 kernel = 13; - - float alpha = 20; - float beta = 21; - - WeightDef filter = 40; - WeightDef bias = 41; - - bool relu_flag = 62; - repeated uint32 adj = 70; - repeated uint32 target_shape = 71; - repeated uint32 before_pad = 72; -}; - -message PoolingOpParams { - int32 mode = 1; - int32 nan_opt = 2; - int32 pad_mode = 3; - bool global_pooling = 4; - - repeated uint32 window = 10; - repeated uint32 pad = 11; - repeated uint32 stride = 12; - bool ceil_mode = 13; - int32 data_mode = 14; - - float alpha = 20; - float beta = 21; - repeated uint32 before_pad = 22; -}; - -message EltwiseOpParams { - int32 mode = 1; - repeated float coeff = 2; - float alpha = 3; - float beta = 4; - repeated WeightDef weight = 5; - bool relu_flag = 6; -}; - -message ActivationOpParams { - int32 mode = 1; - float coef = 2; - float alpha = 3; - float beta = 4; -}; - -message BatchNormOpParams { - int32 mode = 1; - - float alpha = 2; - float beta = 3; - double epsilon = 4;//optinal,[default = 1e-5] - bool use_global_stats = 5; //optinal,by default true,testing mode - float moving_average_fraction = 6; //optinal,[default = .999]; - - WeightDef estimated_mean = 7; - WeightDef estimated_variance = 8; - - WeightDef scale = 9; - WeightDef bias = 10; -}; - -message ScaleOpParams { - WeightDef scale = 1; - WeightDef bias = 2; -}; - -message ReshapeOpParams { - float alpha = 1; - float beta = 2; - ShapeDef shape = 3; - int32 axis = 4; - int32 num_axes = 5; - int32 format = 6; -}; - -message SoftmaxOpParams { - int32 algo = 1; - int32 mode = 2; - float alpha = 3; - float beta = 4; -}; - -message FullConnectionOpParams { - WeightDef filter = 1; - WeightDef bias = 2; - uint32 num_output = 3; - bool relu_flag = 12; -}; - -message FlattenOpParams { - float alpha = 1; - float beta = 2; - int32 start_axis = 3; - int32 end_axis = 4; -} - -message AddLimitedOpParams { - float alpha = 1; - float beta = 2; - int32 axis = 3; - bool broadcast = 4; - - repeated WeightDef weight = 10; -}; - -message MulLimitedOpParams { - float alpha = 1; - float beta = 2; - int32 axis = 3; - bool broadcast = 4; - - repeated WeightDef weight = 10; -}; - -message AddOpParams { - float alpha = 1; - float beta = 2; - - repeated WeightDef weight = 10; -}; - -message MulOpParams { - float alpha = 1; - float beta = 2; - - repeated WeightDef weight = 10; -}; - -message SubOpParams { - float alpha = 1; - float beta = 2; - - repeated WeightDef weight = 10; -}; - -message BiasAddOpParams { - float alpha = 1; - float beta = 2; - - WeightDef bias = 10; -}; - -message MatMulOpParams { - float alpha = 1; - float beta = 2; - bool transposeX = 3; - bool transposeW = 4; - - WeightDef filter = 10; - WeightDef bias = 12; -}; - -message RsqrtOpParams { - float alpha = 1; - float beta = 2; -}; - - -message WeightDef { - int32 format = 1; - int32 data_type = 2; - ShapeDef shape = 3; - bytes data = 4; - int64 data_offset = 5; - uint32 cmps_size = 6; - bytes cmps_tab = 7; - int64 cmps_tab_offset = 10; - CompressInfo cmps_info = 8; - AllOffsetQuantizeInfo alloffset_quantize_info = 11; -} - -message ShapeDef { - repeated int64 dim = 1; -} - -enum DeviceType { - NPU = 0; // In default, we will use NPU. - CPU = 1; // CPU -} - -message AllOffsetQuantizeInfo { - float scale = 1; - int32 offset = 2; -} - -message TensorDescriptor { - int32 format = 1; - int32 data_type = 2; - repeated int64 dim = 3; - uint32 size = 4; - bool reuse_input = 5; - bool output_tensor = 7; - DeviceType device_type = 8; - bool input_tensor = 9; - uint32 real_dim_cnt = 10; - uint32 reuse_input_index = 11; - AllOffsetQuantizeInfo alloffset_quantize_info = 12; -} - -message CompressInfo { - int32 blockRow = 1; // block row - int32 blockCol = 2; // block col - int32 fractalK = 3; // fractal K - int32 fractalN = 4; // fractal N - int32 lastFractalK = 5; // K of last fractal - int32 lastFractalN = 6; // N of last fractal - int32 cubeSize = 7; // cube's length - int32 loadDir = 8; // data load directtiono 0:col load 1:row load -} - -message AttrDef { - message ListValue { - repeated string s = 2; // "list(string)" - repeated int64 i = 3 [packed = true]; // "list(int)" - repeated float f = 4 [packed = true]; // "list(float)" - repeated bool b = 5 [packed = true]; // "list(bool)" - repeated uint32 u = 6 [packed = true]; // "list(uint)" - repeated bytes bt = 7; - } - - oneof value { - string s = 2; // "string" - int64 i = 3; // "int" - float f = 4; // "float" - bool b = 5; // "bool" - uint32 u = 6; // "uint32" - bytes bt = 7; - ListValue list = 1; // any "list(...)" - NamedAttrs func = 10; - } -} - -// A list of attr names and their values. The whole list is attached -// with a string name. E.g., MatMul[T=float]. -message NamedAttrs { - string name = 1; - map attr = 2; -} - diff --git a/ge/offline/proto/task.proto b/ge/offline/proto/task.proto deleted file mode 100644 index 0da5631e..00000000 --- a/ge/offline/proto/task.proto +++ /dev/null @@ -1,179 +0,0 @@ -/* Copyright (C) 2018. Huawei Technologies Co., Ltd. All rights reserved. - * - * This program is free software; you can redistribute it and/or modify - * it under the terms of the Apache License Version 2.0.You may not use this file except in compliance with the License. - * - * This program is distributed in the hope that it will be useful, - * but WITHOUT ANY WARRANTY; without even the implied warranty of - * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - * Apache License for more details at - * http://www.apache.org/licenses/LICENSE-2.0 - */ -syntax = "proto3"; - -package domi; - -message ModelTaskDef { - string version = 1; - - map attr = 9; // Extended field - repeated TaskDef task = 10; - - uint64 memory_size = 11; - uint32 stream_num = 12; - uint32 event_num = 13; - uint64 weight_size = 14; - - repeated bytes op = 15; // input/output opdef in bytes - - uint64 base_addr = 16; // base addr - uint64 weight_addr = 17; // weight addr - uint32 batch_num = 18; -} - - -message TaskDef { - uint32 id = 1; - uint32 type = 2; - - uint32 stream_id = 10; - uint32 event_id = 11; - - KernelDef kernel = 20; - KernelExDef kernel_ex = 21; - KernelHcclDef kernel_hccl = 25; - EventExDef event_ex = 26; - LogTimeStampDef log_timestamp = 28; - - uint32 label_id = 30; - - MemcpyAsyncDef memcpy_async = 31; - StreamSwitchDef stream_switch = 32; - StreamActiveDef stream_active = 33; - bytes private_def = 34; - uint64 ops_kernel_store_ptr = 35; // adjustments to other fields in the future - StreamSwitchNDef stream_switch_n = 36; - - LabelSetDef label_set = 37; - LabelGotoExDef label_goto_ex = 38; - LabelSwitchByIndexDef label_switch_by_index = 39; - KernelDefWithHandle kernel_with_handle = 40; -} - -message KernelDef { - KernelContext context = 1; - - string stub_func = 10; - uint32 block_dim = 11; - uint32 args_size = 12; - bytes args = 13; - bytes sm_desc = 14; - bytes flowtable = 15; - string so_name = 16; - string kernel_name = 17; - bytes kernel_ext_info = 18; - uint32 kernel_ext_info_size = 19; -} - -message KernelDefWithHandle { - KernelContext context = 1; - - uint64 handle = 10; - string dev_func = 11; - uint32 block_dim = 12; - uint32 args_size = 13; - bytes args = 14; - bytes sm_desc = 15; - string original_kernel_key = 16; - string node_info = 17; -} - -message KernelContext { - uint32 kernel_type = 1; - uint32 op_id = 2; // OP type in CCE - uint32 kernel_func_id = 3; - uint32 op_index = 4; // TE/Custom operator - bool is_flowtable = 5; // Identify whether args is a flowtable structure - bytes args_offset = 6; // args offset information - uint32 args_count = 7; // args count - repeated uint32 origin_op_index = 8; -} - - -message KernelExDef { - uint32 flags = 1; - - uint32 op_index = 4; - uint32 args_size = 12; - bytes args = 13; - bytes task_info = 14; // serialized nodeDef, funcDef, inputoutput - uint32 task_info_size = 15; - bytes kernel_ext_info = 16; - uint32 kernel_ext_info_size = 17; -} - - -message KernelHcclDef { - uint32 op_index = 8; - string hccl_type = 9; -} - - -message EventExDef { - uint32 op_index = 1; - uint32 event_type = 2; -} - -message LogTimeStampDef { - uint64 logid = 1; - bool notify = 2; - uint32 flat = 3; -} - -message MemcpyAsyncDef { - uint64 dst = 1; - uint64 dst_max = 2; - uint64 src = 3; - uint64 count = 4; - uint32 kind = 5; - uint32 op_index = 6; -} - -message StreamSwitchDef { - uint32 op_index = 1; - uint32 true_stream_id = 2; - int64 value = 3; - uint64 value_ptr = 4; - uint32 data_type = 5; -} - -message StreamActiveDef { - uint32 op_index = 1; - uint32 active_stream_id = 2; -} - -message StreamSwitchNDef { - uint32 op_index = 1; - uint32 size = 2; - repeated int64 target_value = 3; - repeated uint32 true_stream_id = 4; - uint32 element_size = 5; - uint32 data_type = 6; -} - -message LabelSetDef { - uint32 op_index = 1; - uint32 label_id = 2; - uint32 model_id = 3; -} - -message LabelGotoExDef { - uint32 op_index = 1; - uint32 label_id = 2; - uint32 model_id = 3; -} - -message LabelSwitchByIndexDef { - uint32 op_index = 1; - uint32 label_max = 2; -} diff --git a/ge/proto/caffe/caffe.proto b/ge/proto/caffe/caffe.proto deleted file mode 100644 index 20615fed..00000000 --- a/ge/proto/caffe/caffe.proto +++ /dev/null @@ -1,1829 +0,0 @@ -/** - * This file is part of Open Source Software caffe, version 1.0 https://github.com/BVLC/caffe - * - * This file is included by GraphEngine so as to support model format conversion from caffe model to GraphEngine model. - * This file in this distribution may have been modified by Huawei Technologies Co., Ltd ("Huawei Modifications"). - * All Huawei Modifications are Copyright 2019-2020 Huawei Technologies Co., Ltd. - */ - -syntax = "proto2"; - -package domi.caffe; - -// Specifies the shape (dimensions) of a Blob. -message BlobShape { - repeated int64 dim = 1 [packed = true]; -} - -message BlobProto { - optional BlobShape shape = 7; - repeated float data = 5 [packed = true]; - repeated float diff = 6 [packed = true]; - repeated double double_data = 8 [packed = true]; - repeated double double_diff = 9 [packed = true]; - optional bytes int8_data = 10; - repeated int32 int32_data = 11 [packed = true]; - repeated uint64 uint64_data = 12 [packed = true]; - // 4D dimensions -- deprecated. Use "shape" instead. - optional int32 num = 1 [default = 0]; - optional int32 channels = 2 [default = 0]; - optional int32 height = 3 [default = 0]; - optional int32 width = 4 [default = 0]; -} - -// The BlobProtoVector is simply a way to pass multiple blobproto instances -// around. -message BlobProtoVector { - repeated BlobProto blobs = 1; -} - -message Datum { - optional int32 channels = 1; - optional int32 height = 2; - optional int32 width = 3; - // the actual image data, in bytes - optional bytes data = 4; - optional int32 label = 5; - // Optionally, the datum could also hold float data. - repeated float float_data = 6; - // If true data contains an encoded image that need to be decoded - optional bool encoded = 7 [default = false]; -} - -message FillerParameter { - // The filler type. - optional string type = 1 [default = 'constant']; - optional float value = 2 [default = 0]; // the value in constant filler - optional float min = 3 [default = 0]; // the min value in uniform filler - optional float max = 4 [default = 1]; // the max value in uniform filler - optional float mean = 5 [default = 0]; // the mean value in Gaussian filler - optional float std = 6 [default = 1]; // the std value in Gaussian filler - // The expected number of non-zero output weights for a given input in - // Gaussian filler -- the default -1 means don't perform sparsification. - optional int32 sparse = 7 [default = -1]; - // Normalize the filler variance by fan_in, fan_out, or their average. - // Applies to 'xavier' and 'msra' fillers. - enum VarianceNorm { - FAN_IN = 0; - FAN_OUT = 1; - AVERAGE = 2; - } - optional VarianceNorm variance_norm = 8 [default = FAN_IN]; -} - -message NetParameter { - optional string name = 1; // consider giving the network a name - // DEPRECATED. See InputParameter. The input blobs to the network. - repeated string input = 3; - // DEPRECATED. See InputParameter. The shape of the input blobs. - repeated BlobShape input_shape = 8; - - // 4D input dimensions -- deprecated. Use "input_shape" instead. - // If specified, for each input blob there should be four - // values specifying the num, channels, height and width of the input blob. - // Thus, there should be a total of (4 * #input) numbers. - repeated int32 input_dim = 4; - - // Whether the network will force every layer to carry out backward operation. - // If set False, then whether to carry out backward is determined - // automatically according to the net structure and learning rates. - optional bool force_backward = 5 [default = false]; - // The current "state" of the network, including the phase, level, and stage. - // Some layers may be included/excluded depending on this state and the states - // specified in the layers' include and exclude fields. - optional NetState state = 6; - - // Print debugging information about results while running Net::Forward, - // Net::Backward, and Net::Update. - optional bool debug_info = 7 [default = false]; - - // The layers that make up the net. Each of their configurations, including - // connectivity and behavior, is specified as a LayerParameter. - repeated LayerParameter layer = 100; // ID 100 so layers are printed last. - - // DEPRECATED: use 'layer' instead. - repeated V1LayerParameter layers = 2; -} - -// NOTE -// Update the next available ID when you add a new SolverParameter field. -// -// SolverParameter next available ID: 42 (last added: layer_wise_reduce) -message SolverParameter { - ////////////////////////////////////////////////////////////////////////////// - // Specifying the train and test networks - // - // Exactly one train net must be specified using one of the following fields: - // train_net_param, train_net, net_param, net - // One or more test nets may be specified using any of the following fields: - // test_net_param, test_net, net_param, net - // If more than one test net field is specified (e.g., both net and - // test_net are specified), they will be evaluated in the field order given - // above: (1) test_net_param, (2) test_net, (3) net_param/net. - // A test_iter must be specified for each test_net. - // A test_level and/or a test_stage may also be specified for each test_net. - ////////////////////////////////////////////////////////////////////////////// - - // Proto filename for the train net, possibly combined with one or more - // test nets. - optional string net = 24; - // Inline train net param, possibly combined with one or more test nets. - optional NetParameter net_param = 25; - - optional string train_net = 1; // Proto filename for the train net. - repeated string test_net = 2; // Proto filenames for the test nets. - optional NetParameter train_net_param = 21; // Inline train net params. - repeated NetParameter test_net_param = 22; // Inline test net params. - - // The states for the train/test nets. Must be unspecified or - // specified once per net. - // - // By default, all states will have solver = true; - // train_state will have phase = TRAIN, - // and all test_state's will have phase = TEST. - // Other defaults are set according to the NetState defaults. - optional NetState train_state = 26; - repeated NetState test_state = 27; - - // The number of iterations for each test net. - repeated int32 test_iter = 3; - - // The number of iterations between two testing phases. - optional int32 test_interval = 4 [default = 0]; - optional bool test_compute_loss = 19 [default = false]; - // If true, run an initial test pass before the first iteration, - // ensuring memory availability and printing the starting value of the loss. - optional bool test_initialization = 32 [default = true]; - optional float base_lr = 5; // The base learning rate - // the number of iterations between displaying info. If display = 0, no info - // will be displayed. - optional int32 display = 6; - // Display the loss averaged over the last average_loss iterations - optional int32 average_loss = 33 [default = 1]; - optional int32 max_iter = 7; // the maximum number of iterations - // accumulate gradients over `iter_size` x `batch_size` instances - optional int32 iter_size = 36 [default = 1]; - - // The learning rate decay policy. The currently implemented learning rate - // policies are as follows: - // - fixed: always return base_lr. - // - step: return base_lr * gamma ^ (floor(iter / step)) - // - exp: return base_lr * gamma ^ iter - // - inv: return base_lr * (1 + gamma * iter) ^ (- power) - // - multistep: similar to step but it allows non uniform steps defined by - // stepvalue - // - poly: the effective learning rate follows a polynomial decay, to be - // zero by the max_iter. return base_lr (1 - iter/max_iter) ^ (power) - // - sigmoid: the effective learning rate follows a sigmod decay - // return base_lr ( 1/(1 + exp(-gamma * (iter - stepsize)))) - // - // where base_lr, max_iter, gamma, step, stepvalue and power are defined - // in the solver parameter protocol buffer, and iter is the current iteration. - optional string lr_policy = 8; - optional float gamma = 9; // The parameter to compute the learning rate. - optional float power = 10; // The parameter to compute the learning rate. - optional float momentum = 11; // The momentum value. - optional float weight_decay = 12; // The weight decay. - // regularization types supported: L1 and L2 - // controlled by weight_decay - optional string regularization_type = 29 [default = "L2"]; - // the stepsize for learning rate policy "step" - optional int32 stepsize = 13; - // the stepsize for learning rate policy "multistep" - repeated int32 stepvalue = 34; - - // Set clip_gradients to >= 0 to clip parameter gradients to that L2 norm, - // whenever their actual L2 norm is larger. - optional float clip_gradients = 35 [default = -1]; - - optional int32 snapshot = 14 [default = 0]; // The snapshot interval - optional string snapshot_prefix = 15; // The prefix for the snapshot. - // whether to snapshot diff in the results or not. Snapshotting diff will help - // debugging but the final protocol buffer size will be much larger. - optional bool snapshot_diff = 16 [default = false]; - enum SnapshotFormat { - HDF5 = 0; - BINARYPROTO = 1; - } - optional SnapshotFormat snapshot_format = 37 [default = BINARYPROTO]; - // the mode solver will use: 0 for CPU and 1 for GPU. Use GPU in default. - enum SolverMode { - CPU = 0; - GPU = 1; - } - optional SolverMode solver_mode = 17 [default = GPU]; - // the device_id will that be used in GPU mode. Use device_id = 0 in default. - optional int32 device_id = 18 [default = 0]; - // If non-negative, the seed with which the Solver will initialize the Caffe - // random number generator -- useful for reproducible results. Otherwise, - // (and by default) initialize using a seed derived from the system clock. - optional int64 random_seed = 20 [default = -1]; - - // type of the solver - optional string type = 40 [default = "SGD"]; - - // numerical stability for RMSProp, AdaGrad and AdaDelta and Adam - optional float delta = 31 [default = 1e-8]; - // parameters for the Adam solver - optional float momentum2 = 39 [default = 0.999]; - - // RMSProp decay value - // MeanSquare(t) = rms_decay*MeanSquare(t-1) + (1-rms_decay)*SquareGradient(t) - optional float rms_decay = 38 [default = 0.99]; - - // If true, print information about the state of the net that may help with - // debugging learning problems. - optional bool debug_info = 23 [default = false]; - - // If false, don't save a snapshot after training finishes. - optional bool snapshot_after_train = 28 [default = true]; - - // DEPRECATED: old solver enum types, use string instead - enum SolverType { - SGD = 0; - NESTEROV = 1; - ADAGRAD = 2; - RMSPROP = 3; - ADADELTA = 4; - ADAM = 5; - } - // DEPRECATED: use type instead of solver_type - optional SolverType solver_type = 30 [default = SGD]; - - // Overlap compute and communication for data parallel training - optional bool layer_wise_reduce = 41 [default = true]; -} - -// A message that stores the solver snapshots -message SolverState { - optional int32 iter = 1; // The current iteration - optional string learned_net = 2; // The file that stores the learned net. - repeated BlobProto history = 3; // The history for sgd solvers - optional int32 current_step = 4 [default = 0]; // The current step for learning rate -} - -enum Phase { - TRAIN = 0; - TEST = 1; -} - -message NetState { - optional Phase phase = 1 [default = TEST]; - optional int32 level = 2 [default = 0]; - repeated string stage = 3; -} - -message NetStateRule { - // Set phase to require the NetState have a particular phase (TRAIN or TEST) - // to meet this rule. - optional Phase phase = 1; - - // Set the minimum and/or maximum levels in which the layer should be used. - // Leave undefined to meet the rule regardless of level. - optional int32 min_level = 2; - optional int32 max_level = 3; - - // Customizable sets of stages to include or exclude. - // The net must have ALL of the specified stages and NONE of the specified - // "not_stage"s to meet the rule. - // (Use multiple NetStateRules to specify conjunctions of stages.) - repeated string stage = 4; - repeated string not_stage = 5; -} - -// Specifies training parameters (multipliers on global learning constants, -// and the name and other settings used for weight sharing). -message ParamSpec { - // The names of the parameter blobs -- useful for sharing parameters among - // layers, but never required otherwise. To share a parameter between two - // layers, give it a (non-empty) name. - optional string name = 1; - - // Whether to require shared weights to have the same shape, or just the same - // count -- defaults to STRICT if unspecified. - optional DimCheckMode share_mode = 2; - enum DimCheckMode { - // STRICT (default) requires that num, channels, height, width each match. - STRICT = 0; - // PERMISSIVE requires only the count (num*channels*height*width) to match. - PERMISSIVE = 1; - } - - // The multiplier on the global learning rate for this parameter. - optional float lr_mult = 3 [default = 1.0]; - - // The multiplier on the global weight decay for this parameter. - optional float decay_mult = 4 [default = 1.0]; -} - -// NOTE -// Update the next available ID when you add a new LayerParameter field. -// -// LayerParameter next available layer-specific ID: 151 (last added: smooth_l1_loss_param) -message LayerParameter { - optional string name = 1; // the layer name - optional string type = 2; // the layer type - repeated string bottom = 3; // the name of each bottom blob - repeated string top = 4; // the name of each top blob - - // The train / test phase for computation. - optional Phase phase = 10; - - // The amount of weight to assign each top blob in the objective. - // Each layer assigns a default value, usually of either 0 or 1, - // to each top blob. - repeated float loss_weight = 5; - - // Specifies training parameters (multipliers on global learning constants, - // and the name and other settings used for weight sharing). - repeated ParamSpec param = 6; - - // The blobs containing the numeric parameters of the layer. - repeated BlobProto blobs = 7; - - // Specifies whether to backpropagate to each bottom. If unspecified, - // Caffe will automatically infer whether each input needs backpropagation - // to compute parameter gradients. If set to true for some inputs, - // backpropagation to those inputs is forced; if set false for some inputs, - // backpropagation to those inputs is skipped. - // - // The size must be either 0 or equal to the number of bottoms. - repeated bool propagate_down = 11; - - // Rules controlling whether and when a layer is included in the network, - // based on the current NetState. You may specify a non-zero number of rules - // to include OR exclude, but not both. If no include or exclude rules are - // specified, the layer is always included. If the current NetState meets - // ANY (i.e., one or more) of the specified rules, the layer is - // included/excluded. - repeated NetStateRule include = 8; - repeated NetStateRule exclude = 9; - - // Parameters for data pre-processing. - optional TransformationParameter transform_param = 100; - - // Parameters shared by loss layers. - optional LossParameter loss_param = 101; - - // Layer type-specific parameters. - // - // Note: certain layers may have more than one computational engine - // for their implementation. These layers include an Engine type and - // engine parameter for selecting the implementation. - // The default for the engine is set by the ENGINE switch at compile-time. - optional AccuracyParameter accuracy_param = 102; - optional ArgMaxParameter argmax_param = 103; - optional BatchNormParameter batch_norm_param = 139; - optional BiasParameter bias_param = 141; - optional ConcatParameter concat_param = 104; - optional ContrastiveLossParameter contrastive_loss_param = 105; - optional ConvolutionParameter convolution_param = 106; - optional CropParameter crop_param = 144; - optional DataParameter data_param = 107; - optional DetectionOutputParameter detection_output_param = 150; - optional DropoutParameter dropout_param = 108; - optional DummyDataParameter dummy_data_param = 109; - optional EltwiseParameter eltwise_param = 110; - optional ELUParameter elu_param = 140; - optional EmbedParameter embed_param = 137; - optional ExpParameter exp_param = 111; - optional FlattenParameter flatten_param = 135; - optional HDF5DataParameter hdf5_data_param = 112; - optional HDF5OutputParameter hdf5_output_param = 113; - optional HingeLossParameter hinge_loss_param = 114; - optional ImageDataParameter image_data_param = 115; - optional InfogainLossParameter infogain_loss_param = 116; - optional InnerProductParameter inner_product_param = 117; - optional InputParameter input_param = 143; - optional LogParameter log_param = 134; - optional LRNParameter lrn_param = 118; - optional MemoryDataParameter memory_data_param = 119; - optional MVNParameter mvn_param = 120; - optional ParameterParameter parameter_param = 145; - optional PoolingParameter pooling_param = 121; - optional PowerParameter power_param = 122; - optional PReLUParameter prelu_param = 131; - optional PythonParameter python_param = 130; - optional RecurrentParameter recurrent_param = 146; - optional ReductionParameter reduction_param = 136; - optional ReLUParameter relu_param = 123; - optional ReshapeParameter reshape_param = 133; - optional ScaleParameter scale_param = 142; - optional SigmoidParameter sigmoid_param = 124; - optional SmoothL1LossParameter smooth_l1_loss_param = 148; - optional SoftmaxParameter softmax_param = 125; - optional SPPParameter spp_param = 132; - optional SliceParameter slice_param = 126; - optional TanHParameter tanh_param = 127; - optional ThresholdParameter threshold_param = 128; - optional TileParameter tile_param = 138; - optional WindowDataParameter window_data_param = 129; - optional PermuteParameter permute_param = 202; - optional PriorBoxParameter prior_box_param = 203; - optional NormalizeParameter norm_param = 206; - optional PSROIPoolingParameter psroi_pooling_param = 207; - optional FreespaceExtractParameter freespace_extract_param = 151; - optional PostprocessParameter postprocess_param = 152; - optional SpatialTransformParameter spatial_transform_param = 153; - optional ROIAlignParameter roi_align_param = 154; - optional ReorgParameter reorg_param = 155; - optional RegionParameter region_param = 156; - optional ReverseParameter reverse_param = 157; - optional InterpParameter interp_param = 158; - optional ShuffleChannelParameter shuffle_channel_param = 159; - optional UpsampleParameter upsample_param = 160; - optional ROIPoolingParameter roi_pooling_param = 161; - optional YoloParameter yolo_param = 199; - optional YoloV3DetectionOutputParameter yolov3_detection_output_param = 200; - optional ProposalParameter proposal_param = 201; - optional FSRDetectionOutputParameter fsrdetectionoutput_param = 222; - optional SSDDetectionOutputParameter ssddetectionoutput_param = 232; - optional YoloV2DetectionOutputParameter yolov2_detection_output_param = 204; - optional QuantParameter quant_param = 208; - optional CondTakeParameter condtake_param = 233; - optional MatrixInverseParameter matrix_inverse_param = 210; - optional WarpPerspectiveParameter warp_perspective_param = 234; - optional BatchMatMulParameter batch_matmul_param = 235; - optional SpatialTransformerParameter st_param = 5000; - optional YoloV3DetectionOutputV2Parameter yolov3_detection_output_v2_param = 5001; -} - -// Message that stores parameters used to apply transformation -// to the data layer's data -message TransformationParameter { - // For data pre-processing, we can do simple scaling and subtracting the - // data mean, if provided. Note that the mean subtraction is always carried - // out before scaling. - optional float scale = 1 [default = 1]; - // Specify if we want to randomly mirror data. - optional bool mirror = 2 [default = false]; - // Specify if we would like to randomly crop an image. - optional uint32 crop_size = 3 [default = 0]; - // mean_file and mean_value cannot be specified at the same time - optional string mean_file = 4; - // if specified can be repeated once (would substract it from all the channels) - // or can be repeated the same number of times as channels - // (would subtract them from the corresponding channel) - repeated float mean_value = 5; - // Force the decoded image to have 3 color channels. - optional bool force_color = 6 [default = false]; - // Force the decoded image to have 1 color channels. - optional bool force_gray = 7 [default = false]; -} - -// Message that stores parameters shared by loss layers -message LossParameter { - // If specified, ignore instances with the given label. - optional int32 ignore_label = 1; - // How to normalize the loss for loss layers that aggregate across batches, - // spatial dimensions, or other dimensions. Currently only implemented in - // SoftmaxWithLoss and SigmoidCrossEntropyLoss layers. - enum NormalizationMode { - // Divide by the number of examples in the batch times spatial dimensions. - // Outputs that receive the ignore label will NOT be ignored in computing - // the normalization factor. - FULL = 0; - // Divide by the total number of output locations that do not take the - // ignore_label. If ignore_label is not set, this behaves like FULL. - VALID = 1; - // Divide by the batch size. - BATCH_SIZE = 2; - // Do not normalize the loss. - NONE = 3; - } - // For historical reasons, the default normalization for - // SigmoidCrossEntropyLoss is BATCH_SIZE and *not* VALID. - optional NormalizationMode normalization = 3 [default = VALID]; - // Deprecated. Ignored if normalization is specified. If normalization - // is not specified, then setting this to false will be equivalent to - // normalization = BATCH_SIZE to be consistent with previous behavior. - optional bool normalize = 2; -} - -// Messages that store parameters used by individual layer types follow, in -// alphabetical order. - -message AccuracyParameter { - // When computing accuracy, count as correct by comparing the true label to - // the top k scoring classes. By default, only compare to the top scoring - // class (i.e. argmax). - optional uint32 top_k = 1 [default = 1]; - - // The "label" axis of the prediction blob, whose argmax corresponds to the - // predicted label -- may be negative to index from the end (e.g., -1 for the - // last axis). For example, if axis == 1 and the predictions are - // (N x C x H x W), the label blob is expected to contain N*H*W ground truth - // labels with integer values in {0, 1, ..., C-1}. - optional int32 axis = 2 [default = 1]; - - // If specified, ignore instances with the given label. - optional int32 ignore_label = 3; -} - -message ArgMaxParameter { - // If true produce pairs (argmax, maxval) - optional bool out_max_val = 1 [default = false]; - optional uint32 top_k = 2 [default = 1]; - // The axis along which to maximise -- may be negative to index from the - // end (e.g., -1 for the last axis). - // By default ArgMaxLayer maximizes over the flattened trailing dimensions - // for each index of the first / num dimension. - optional int32 axis = 3; -} - -message ConcatParameter { - // The axis along which to concatenate -- may be negative to index from the - // end (e.g., -1 for the last axis). Other axes must have the - // same dimension for all the bottom blobs. - // By default, ConcatLayer concatenates blobs along the "channels" axis (1). - optional int32 axis = 2 [default = 1]; - - // DEPRECATED: alias for "axis" -- does not support negative indexing. - optional uint32 concat_dim = 1 [default = 1]; -} - -message BatchNormParameter { - // If false, normalization is performed over the current mini-batch - // and global statistics are accumulated (but not yet used) by a moving - // average. - // If true, those accumulated mean and variance values are used for the - // normalization. - // By default, it is set to false when the network is in the training - // phase and true when the network is in the testing phase. - optional bool use_global_stats = 1; - // What fraction of the moving average remains each iteration? - // Smaller values make the moving average decay faster, giving more - // weight to the recent values. - // Each iteration updates the moving average @f$S_{t-1}@f$ with the - // current mean @f$ Y_t @f$ by - // @f$ S_t = (1-\beta)Y_t + \beta \cdot S_{t-1} @f$, where @f$ \beta @f$ - // is the moving_average_fraction parameter. - optional float moving_average_fraction = 2 [default = .999]; - // Small value to add to the variance estimate so that we don't divide by - // zero. - optional float eps = 3 [default = 1e-5]; -} - -message BiasParameter { - // The first axis of bottom[0] (the first input Blob) along which to apply - // bottom[1] (the second input Blob). May be negative to index from the end - // (e.g., -1 for the last axis). - // - // For example, if bottom[0] is 4D with shape 100x3x40x60, the output - // top[0] will have the same shape, and bottom[1] may have any of the - // following shapes (for the given value of axis): - // (axis == 0 == -4) 100; 100x3; 100x3x40; 100x3x40x60 - // (axis == 1 == -3) 3; 3x40; 3x40x60 - // (axis == 2 == -2) 40; 40x60 - // (axis == 3 == -1) 60 - // Furthermore, bottom[1] may have the empty shape (regardless of the value of - // "axis") -- a scalar bias. - optional int32 axis = 1 [default = 1]; - - // (num_axes is ignored unless just one bottom is given and the bias is - // a learned parameter of the layer. Otherwise, num_axes is determined by the - // number of axes by the second bottom.) - // The number of axes of the input (bottom[0]) covered by the bias - // parameter, or -1 to cover all axes of bottom[0] starting from `axis`. - // Set num_axes := 0, to add a zero-axis Blob: a scalar. - optional int32 num_axes = 2 [default = 1]; - - // (filler is ignored unless just one bottom is given and the bias is - // a learned parameter of the layer.) - // The initialization for the learned bias parameter. - // Default is the zero (0) initialization, resulting in the BiasLayer - // initially performing the identity operation. - optional FillerParameter filler = 3; - optional bool bias_from_blob = 4 [default = true]; -} - -message ContrastiveLossParameter { - // margin for dissimilar pair - optional float margin = 1 [default = 1.0]; - // The first implementation of this cost did not exactly match the cost of - // Hadsell et al 2006 -- using (margin - d^2) instead of (margin - d)^2. - // legacy_version = false (the default) uses (margin - d)^2 as proposed in the - // Hadsell paper. New models should probably use this version. - // legacy_version = true uses (margin - d^2). This is kept to support / - // reproduce existing models and results - optional bool legacy_version = 2 [default = false]; -} - -message ConvolutionParameter { - optional uint32 num_output = 1; // The number of outputs for the layer - optional bool bias_term = 2 [default = true]; // whether to have bias terms - - // Pad, kernel size, and stride are all given as a single value for equal - // dimensions in all spatial dimensions, or once per spatial dimension. - repeated uint32 pad = 3; // The padding size; defaults to 0 - repeated uint32 kernel_size = 4; // The kernel size - repeated uint32 stride = 6; // The stride; defaults to 1 - // Factor used to dilate the kernel, (implicitly) zero-filling the resulting - // holes. (Kernel dilation is sometimes referred to by its use in the - // algorithme 脿 trous from Holschneider et al. 1987.) - repeated uint32 dilation = 18; // The dilation; defaults to 1 - - // For 2D convolution only, the *_h and *_w versions may also be used to - // specify both spatial dimensions. - optional uint32 pad_h = 9 [default = 0]; // The padding height (2D only) - optional uint32 pad_w = 10 [default = 0]; // The padding width (2D only) - optional uint32 kernel_h = 11; // The kernel height (2D only) - optional uint32 kernel_w = 12; // The kernel width (2D only) - optional uint32 stride_h = 13; // The stride height (2D only) - optional uint32 stride_w = 14; // The stride width (2D only) - - optional uint32 group = 5 [default = 1]; // The group size for group conv - - optional FillerParameter weight_filler = 7; // The filler for the weight - optional FillerParameter bias_filler = 8; // The filler for the bias - enum Engine { - DEFAULT = 0; - CAFFE = 1; - CUDNN = 2; - } - optional Engine engine = 15 [default = DEFAULT]; - - // The axis to interpret as "channels" when performing convolution. - // Preceding dimensions are treated as independent inputs; - // succeeding dimensions are treated as "spatial". - // With (N, C, H, W) inputs, and axis == 1 (the default), we perform - // N independent 2D convolutions, sliding C-channel (or (C/g)-channels, for - // groups g>1) filters across the spatial axes (H, W) of the input. - // With (N, C, D, H, W) inputs, and axis == 1, we perform - // N independent 3D convolutions, sliding (C/g)-channels - // filters across the spatial axes (D, H, W) of the input. - optional int32 axis = 16 [default = 1]; - - // Whether to force use of the general ND convolution, even if a specific - // implementation for blobs of the appropriate number of spatial dimensions - // is available. (Currently, there is only a 2D-specific convolution - // implementation; for input blobs with num_axes != 2, this option is - // ignored and the ND implementation will be used.) - optional bool force_nd_im2col = 17 [default = false]; -} - -message CropParameter { - // To crop, elements of the first bottom are selected to fit the dimensions - // of the second, reference bottom. The crop is configured by - // - the crop `axis` to pick the dimensions for cropping - // - the crop `offset` to set the shift for all/each dimension - // to align the cropped bottom with the reference bottom. - // All dimensions up to but excluding `axis` are preserved, while - // the dimensions including and trailing `axis` are cropped. - // If only one `offset` is set, then all dimensions are offset by this amount. - // Otherwise, the number of offsets must equal the number of cropped axes to - // shift the crop in each dimension accordingly. - // Note: standard dimensions are N,C,H,W so the default is a spatial crop, - // and `axis` may be negative to index from the end (e.g., -1 for the last - // axis). - optional int32 axis = 1 [default = 2]; - repeated uint32 offset = 2; -} - -message DataParameter { - enum DB { - LEVELDB = 0; - LMDB = 1; - } - // Specify the data source. - optional string source = 1; - // Specify the batch size. - optional uint32 batch_size = 4; - // The rand_skip variable is for the data layer to skip a few data points - // to avoid all asynchronous sgd clients to start at the same point. The skip - // point would be set as rand_skip * rand(0,1). Note that rand_skip should not - // be larger than the number of keys in the database. - // DEPRECATED. Each solver accesses a different subset of the database. - optional uint32 rand_skip = 7 [default = 0]; - optional DB backend = 8 [default = LEVELDB]; - // DEPRECATED. See TransformationParameter. For data pre-processing, we can do - // simple scaling and subtracting the data mean, if provided. Note that the - // mean subtraction is always carried out before scaling. - optional float scale = 2 [default = 1]; - optional string mean_file = 3; - // DEPRECATED. See TransformationParameter. Specify if we would like to randomly - // crop an image. - optional uint32 crop_size = 5 [default = 0]; - // DEPRECATED. See TransformationParameter. Specify if we want to randomly mirror - // data. - optional bool mirror = 6 [default = false]; - // Force the encoded image to have 3 color channels - optional bool force_encoded_color = 9 [default = false]; - // Prefetch queue (Increase if data feeding bandwidth varies, within the - // limit of device memory for GPU training) - optional uint32 prefetch = 10 [default = 4]; -} - -message DropoutParameter { - optional float dropout_ratio = 1 [default = 0.5]; // dropout ratio - optional bool scale_train = 2 [default = true]; // scale train or test phase -} - -// DummyDataLayer fills any number of arbitrarily shaped blobs with random -// (or constant) data generated by "Fillers" (see "message FillerParameter"). -message DummyDataParameter { - // This layer produces N >= 1 top blobs. DummyDataParameter must specify 1 or N - // shape fields, and 0, 1 or N data_fillers. - // - // If 0 data_fillers are specified, ConstantFiller with a value of 0 is used. - // If 1 data_filler is specified, it is applied to all top blobs. If N are - // specified, the ith is applied to the ith top blob. - repeated FillerParameter data_filler = 1; - repeated BlobShape shape = 6; - - // 4D dimensions -- deprecated. Use "shape" instead. - repeated uint32 num = 2; - repeated uint32 channels = 3; - repeated uint32 height = 4; - repeated uint32 width = 5; -} - -message EltwiseParameter { - enum EltwiseOp { - PROD = 0; - SUM = 1; - MAX = 2; - } - optional EltwiseOp operation = 1 [default = SUM]; // element-wise operation - repeated float coeff = 2; // blob-wise coefficient for SUM operation - - // Whether to use an asymptotically slower (for >2 inputs) but stabler method - // of computing the gradient for the PROD operation. (No effect for SUM op.) - optional bool stable_prod_grad = 3 [default = true]; -} - -// Message that stores parameters used by ELULayer -message ELUParameter { - // Described in: - // Clevert, D.-A., Unterthiner, T., & Hochreiter, S. (2015). Fast and Accurate - // Deep Network Learning by Exponential Linear Units (ELUs). arXiv - optional float alpha = 1 [default = 1]; -} - -// Message that stores parameters used by EmbedLayer -message EmbedParameter { - optional uint32 num_output = 1; // The number of outputs for the layer - // The input is given as integers to be interpreted as one-hot - // vector indices with dimension num_input. Hence num_input should be - // 1 greater than the maximum possible input value. - optional uint32 input_dim = 2; - - optional bool bias_term = 3 [default = true]; // Whether to use a bias term - optional FillerParameter weight_filler = 4; // The filler for the weight - optional FillerParameter bias_filler = 5; // The filler for the bias - -} - -// Message that stores parameters used by ExpLayer -message ExpParameter { - // ExpLayer computes outputs y = base ^ (shift + scale * x), for base > 0. - // Or if base is set to the default (-1), base is set to e, - // so y = exp(shift + scale * x). - optional float base = 1 [default = -1.0]; - optional float scale = 2 [default = 1.0]; - optional float shift = 3 [default = 0.0]; -} - -/// Message that stores parameters used by FlattenLayer -message FlattenParameter { - // The first axis to flatten: all preceding axes are retained in the output. - // May be negative to index from the end (e.g., -1 for the last axis). - optional int32 axis = 1 [default = 1]; - - // The last axis to flatten: all following axes are retained in the output. - // May be negative to index from the end (e.g., the default -1 for the last - // axis). - optional int32 end_axis = 2 [default = -1]; -} - -// Message that stores parameters used by HDF5DataLayer -message HDF5DataParameter { - // Specify the data source. - optional string source = 1; - // Specify the batch size. - optional uint32 batch_size = 2; - - // Specify whether to shuffle the data. - // If shuffle == true, the ordering of the HDF5 files is shuffled, - // and the ordering of data within any given HDF5 file is shuffled, - // but data between different files are not interleaved; all of a file's - // data are output (in a random order) before moving onto another file. - optional bool shuffle = 3 [default = false]; -} - -message HDF5OutputParameter { - optional string file_name = 1; -} - -message HingeLossParameter { - enum Norm { - L1 = 1; - L2 = 2; - } - // Specify the Norm to use L1 or L2 - optional Norm norm = 1 [default = L1]; -} - -message ImageDataParameter { - // Specify the data source. - optional string source = 1; - // Specify the batch size. - optional uint32 batch_size = 4 [default = 1]; - // The rand_skip variable is for the data layer to skip a few data points - // to avoid all asynchronous sgd clients to start at the same point. The skip - // point would be set as rand_skip * rand(0,1). Note that rand_skip should not - // be larger than the number of keys in the database. - optional uint32 rand_skip = 7 [default = 0]; - // Whether or not ImageLayer should shuffle the list of files at every epoch. - optional bool shuffle = 8 [default = false]; - // It will also resize images if new_height or new_width are not zero. - optional uint32 new_height = 9 [default = 0]; - optional uint32 new_width = 10 [default = 0]; - // Specify if the images are color or gray - optional bool is_color = 11 [default = true]; - // DEPRECATED. See TransformationParameter. For data pre-processing, we can do - // simple scaling and subtracting the data mean, if provided. Note that the - // mean subtraction is always carried out before scaling. - optional float scale = 2 [default = 1]; - optional string mean_file = 3; - // DEPRECATED. See TransformationParameter. Specify if we would like to randomly - // crop an image. - optional uint32 crop_size = 5 [default = 0]; - // DEPRECATED. See TransformationParameter. Specify if we want to randomly mirror - // data. - optional bool mirror = 6 [default = false]; - optional string root_folder = 12 [default = ""]; -} - -message InfogainLossParameter { - // Specify the infogain matrix source. - optional string source = 1; - optional int32 axis = 2 [default = 1]; // axis of prob -} - -message InnerProductParameter { - optional uint32 num_output = 1; // The number of outputs for the layer - optional bool bias_term = 2 [default = true]; // whether to have bias terms - optional FillerParameter weight_filler = 3; // The filler for the weight - optional FillerParameter bias_filler = 4; // The filler for the bias - - // The first axis to be lumped into a single inner product computation; - // all preceding axes are retained in the output. - // May be negative to index from the end (e.g., -1 for the last axis). - optional int32 axis = 5 [default = 1]; - // Specify whether to transpose the weight matrix or not. - // If transpose == true, any operations will be performed on the transpose - // of the weight matrix. The weight matrix itself is not going to be transposed - // but rather the transfer flag of operations will be toggled accordingly. - optional bool transpose = 6 [default = false]; -} - -message InputParameter { - // This layer produces N >= 1 top blob(s) to be assigned manually. - // Define N shapes to set a shape for each top. - // Define 1 shape to set the same shape for every top. - // Define no shape to defer to reshaping manually. - repeated BlobShape shape = 1; -} - -// Message that stores parameters used by LogLayer -message LogParameter { - // LogLayer computes outputs y = log_base(shift + scale * x), for base > 0. - // Or if base is set to the default (-1), base is set to e, - // so y = ln(shift + scale * x) = log_e(shift + scale * x) - optional float base = 1 [default = -1.0]; - optional float scale = 2 [default = 1.0]; - optional float shift = 3 [default = 0.0]; -} - -// Message that stores parameters used by LRNLayer -message LRNParameter { - optional uint32 local_size = 1 [default = 5]; - optional float alpha = 2 [default = 1.]; - optional float beta = 3 [default = 0.75]; - enum NormRegion { - ACROSS_CHANNELS = 0; - WITHIN_CHANNEL = 1; - } - optional NormRegion norm_region = 4 [default = ACROSS_CHANNELS]; - optional float k = 5 [default = 1.]; - enum Engine { - DEFAULT = 0; - CAFFE = 1; - CUDNN = 2; - } - optional Engine engine = 6 [default = DEFAULT]; -} - -message MemoryDataParameter { - optional uint32 batch_size = 1; - optional uint32 channels = 2; - optional uint32 height = 3; - optional uint32 width = 4; -} - -message MVNParameter { - // This parameter can be set to false to normalize mean only - optional bool normalize_variance = 1 [default = true]; - - // This parameter can be set to true to perform DNN-like MVN - optional bool across_channels = 2 [default = false]; - - // Epsilon for not dividing by zero while normalizing variance - optional float eps = 3 [default = 1e-9]; -} - -message ParameterParameter { - optional BlobShape shape = 1; -} - -message PoolingParameter { - enum PoolMethod { - MAX = 0; - AVE = 1; - STOCHASTIC = 2; - } - optional PoolMethod pool = 1 [default = MAX]; // The pooling method - // Pad, kernel size, and stride are all given as a single value for equal - // dimensions in height and width or as Y, X pairs. - optional uint32 pad = 4 [default = 0]; // The padding size (equal in Y, X) - optional uint32 pad_h = 9 [default = 0]; // The padding height - optional uint32 pad_w = 10 [default = 0]; // The padding width - optional uint32 kernel_size = 2; // The kernel size (square) - optional uint32 kernel_h = 5; // The kernel height - optional uint32 kernel_w = 6; // The kernel width - optional uint32 stride = 3 [default = 1]; // The stride (equal in Y, X) - optional uint32 stride_h = 7; // The stride height - optional uint32 stride_w = 8; // The stride width - enum Engine { - DEFAULT = 0; - CAFFE = 1; - CUDNN = 2; - } - optional Engine engine = 11 [default = DEFAULT]; - // If global_pooling then it will pool over the size of the bottom by doing - // kernel_h = bottom->height and kernel_w = bottom->width - optional bool global_pooling = 12 [default = false]; - optional bool ceil_mode = 13 [default = true]; - // How to calculate the output size - using ceil (default) or floor rounding. - enum RoundMode { - CEIL = 0; - FLOOR = 1; - } - optional RoundMode round_mode = 14 [default = CEIL]; -} - -message PowerParameter { - // PowerLayer computes outputs y = (shift + scale * x) ^ power. - optional float power = 1 [default = 1.0]; - optional float scale = 2 [default = 1.0]; - optional float shift = 3 [default = 0.0]; -} - -message PythonParameter { - optional string module = 1; - optional string layer = 2; - // This value is set to the attribute `param_str` of the `PythonLayer` object - // in Python before calling the `setup()` method. This could be a number, - // string, dictionary in Python dict format, JSON, etc. You may parse this - // string in `setup` method and use it in `forward` and `backward`. - optional string param_str = 3 [default = '']; - // Whether this PythonLayer is shared among worker solvers during data parallelism. - // If true, each worker solver sequentially run forward from this layer. - // This value should be set true if you are using it as a data layer. - optional bool share_in_parallel = 4 [default = false]; -} - -// Message that stores parameters used by RecurrentLayer -message RecurrentParameter { - // The dimension of the output (and usually hidden state) representation -- - // must be explicitly set to non-zero. - optional uint32 num_output = 1 [default = 0]; - - optional FillerParameter weight_filler = 2; // The filler for the weight - optional FillerParameter bias_filler = 3; // The filler for the bias - - // Whether to enable displaying debug_info in the unrolled recurrent net. - optional bool debug_info = 4 [default = false]; - - // Whether to add as additional inputs (bottoms) the initial hidden state - // blobs, and add as additional outputs (tops) the final timestep hidden state - // blobs. The number of additional bottom/top blobs required depends on the - // recurrent architecture -- e.g., 1 for RNNs, 2 for LSTMs. - optional bool expose_hidden = 5 [default = false]; -} - -// Message that stores parameters used by ReductionLayer -message ReductionParameter { - enum ReductionOp { - SUM = 1; - ASUM = 2; - SUMSQ = 3; - MEAN = 4; - } - - optional ReductionOp operation = 1 [default = SUM]; // reduction operation - - // The first axis to reduce to a scalar -- may be negative to index from the - // end (e.g., -1 for the last axis). - // (Currently, only reduction along ALL "tail" axes is supported; reduction - // of axis M through N, where N < num_axes - 1, is unsupported.) - // Suppose we have an n-axis bottom Blob with shape: - // (d0, d1, d2, ..., d(m-1), dm, d(m+1), ..., d(n-1)). - // If axis == m, the output Blob will have shape - // (d0, d1, d2, ..., d(m-1)), - // and the ReductionOp operation is performed (d0 * d1 * d2 * ... * d(m-1)) - // times, each including (dm * d(m+1) * ... * d(n-1)) individual data. - // If axis == 0 (the default), the output Blob always has the empty shape - // (count 1), performing reduction across the entire input -- - // often useful for creating new loss functions. - optional int32 axis = 2 [default = 0]; - - optional float coeff = 3 [default = 1.0]; // coefficient for output -} - -// Message that stores parameters used by ReLULayer -message ReLUParameter { - // Allow non-zero slope for negative inputs to speed up optimization - // Described in: - // Maas, A. L., Hannun, A. Y., & Ng, A. Y. (2013). Rectifier nonlinearities - // improve neural network acoustic models. In ICML Workshop on Deep Learning - // for Audio, Speech, and Language Processing. - optional float negative_slope = 1 [default = 0]; - enum Engine { - DEFAULT = 0; - CAFFE = 1; - CUDNN = 2; - } - optional Engine engine = 2 [default = DEFAULT]; -} - -message ReshapeParameter { - // Specify the output dimensions. If some of the dimensions are set to 0, - // the corresponding dimension from the bottom layer is used (unchanged). - // Exactly one dimension may be set to -1, in which case its value is - // inferred from the count of the bottom blob and the remaining dimensions. - // For example, suppose we want to reshape a 2D blob "input" with shape 2 x 8: - // - // layer { - // type: "Reshape" bottom: "input" top: "output" - // reshape_param { ... } - // } - // - // If "input" is 2D with shape 2 x 8, then the following reshape_param - // specifications are all equivalent, producing a 3D blob "output" with shape - // 2 x 2 x 4: - // - // reshape_param { shape { dim: 2 dim: 2 dim: 4 } } - // reshape_param { shape { dim: 0 dim: 2 dim: 4 } } - // reshape_param { shape { dim: 0 dim: 2 dim: -1 } } - // reshape_param { shape { dim: 0 dim:-1 dim: 4 } } - // - optional BlobShape shape = 1; - - // axis and num_axes control the portion of the bottom blob's shape that are - // replaced by (included in) the reshape. By default (axis == 0 and - // num_axes == -1), the entire bottom blob shape is included in the reshape, - // and hence the shape field must specify the entire output shape. - // - // axis may be non-zero to retain some portion of the beginning of the input - // shape (and may be negative to index from the end; e.g., -1 to begin the - // reshape after the last axis, including nothing in the reshape, - // -2 to include only the last axis, etc.). - // - // For example, suppose "input" is a 2D blob with shape 2 x 8. - // Then the following ReshapeLayer specifications are all equivalent, - // producing a blob "output" with shape 2 x 2 x 4: - // - // reshape_param { shape { dim: 2 dim: 2 dim: 4 } } - // reshape_param { shape { dim: 2 dim: 4 } axis: 1 } - // reshape_param { shape { dim: 2 dim: 4 } axis: -3 } - // - // num_axes specifies the extent of the reshape. - // If num_axes >= 0 (and axis >= 0), the reshape will be performed only on - // input axes in the range [axis, axis+num_axes]. - // num_axes may also be -1, the default, to include all remaining axes - // (starting from axis). - // - // For example, suppose "input" is a 2D blob with shape 2 x 8. - // Then the following ReshapeLayer specifications are equivalent, - // producing a blob "output" with shape 1 x 2 x 8. - // - // reshape_param { shape { dim: 1 dim: 2 dim: 8 } } - // reshape_param { shape { dim: 1 dim: 2 } num_axes: 1 } - // reshape_param { shape { dim: 1 } num_axes: 0 } - // - // On the other hand, these would produce output blob shape 2 x 1 x 8: - // - // reshape_param { shape { dim: 2 dim: 1 dim: 8 } } - // reshape_param { shape { dim: 1 } axis: 1 num_axes: 0 } - // - optional int32 axis = 2 [default = 0]; - optional int32 num_axes = 3 [default = -1]; -} - - -message ScaleParameter { - // The first axis of bottom[0] (the first input Blob) along which to apply - // bottom[1] (the second input Blob). May be negative to index from the end - // (e.g., -1 for the last axis). - // - // For example, if bottom[0] is 4D with shape 100x3x40x60, the output - // top[0] will have the same shape, and bottom[1] may have any of the - // following shapes (for the given value of axis): - // (axis == 0 == -4) 100; 100x3; 100x3x40; 100x3x40x60 - // (axis == 1 == -3) 3; 3x40; 3x40x60 - // (axis == 2 == -2) 40; 40x60 - // (axis == 3 == -1) 60 - // Furthermore, bottom[1] may have the empty shape (regardless of the value of - // "axis") -- a scalar multiplier. - optional int32 axis = 1 [default = 1]; - - // (num_axes is ignored unless just one bottom is given and the scale is - // a learned parameter of the layer. Otherwise, num_axes is determined by the - // number of axes by the second bottom.) - // The number of axes of the input (bottom[0]) covered by the scale - // parameter, or -1 to cover all axes of bottom[0] starting from `axis`. - // Set num_axes := 0, to multiply with a zero-axis Blob: a scalar. - optional int32 num_axes = 2 [default = 1]; - - // (filler is ignored unless just one bottom is given and the scale is - // a learned parameter of the layer.) - // The initialization for the learned scale parameter. - // Default is the unit (1) initialization, resulting in the ScaleLayer - // initially performing the identity operation. - optional FillerParameter filler = 3; - - // Whether to also learn a bias (equivalent to a ScaleLayer+BiasLayer, but - // may be more efficient). Initialized with bias_filler (defaults to 0). - optional bool bias_term = 4 [default = false]; - optional FillerParameter bias_filler = 5; - optional bool scale_from_blob = 6 [default = true]; -} - -message SigmoidParameter { - enum Engine { - DEFAULT = 0; - CAFFE = 1; - CUDNN = 2; - } - optional Engine engine = 1 [default = DEFAULT]; -} - -message SliceParameter { - // The axis along which to slice -- may be negative to index from the end - // (e.g., -1 for the last axis). - // By default, SliceLayer concatenates blobs along the "channels" axis (1). - optional int32 axis = 3 [default = 1]; - repeated uint32 slice_point = 2; - - // DEPRECATED: alias for "axis" -- does not support negative indexing. - optional uint32 slice_dim = 1 [default = 1]; -} - -message SmoothL1LossParameter { - // SmoothL1Loss(x) = - // 0.5 * (sigma * x) ** 2 -- if x < 1.0 / sigma / sigma - // |x| - 0.5 / sigma / sigma -- otherwise - optional float sigma = 1 [default = 1]; -} - -// Message that stores parameters used by SoftmaxLayer, SoftmaxWithLossLayer -message SoftmaxParameter { - enum Engine { - DEFAULT = 0; - CAFFE = 1; - CUDNN = 2; - } - optional Engine engine = 1 [default = DEFAULT]; - - // The axis along which to perform the softmax -- may be negative to index - // from the end (e.g., -1 for the last axis). - // Any other axes will be evaluated as independent softmaxes. - optional int32 axis = 2 [default = 1]; -} - -message TanHParameter { - enum Engine { - DEFAULT = 0; - CAFFE = 1; - CUDNN = 2; - } - optional Engine engine = 1 [default = DEFAULT]; -} - -// Message that stores parameters used by TileLayer -message TileParameter { - // The index of the axis to tile. - optional int32 axis = 1 [default = 1]; - - // The number of copies (tiles) of the blob to output. - optional int32 tiles = 2; -} - -// Message that stores parameters used by ThresholdLayer -message ThresholdParameter { - optional float threshold = 1 [default = 0]; // Strictly positive values -} - -message WindowDataParameter { - // Specify the data source. - optional string source = 1; - // For data pre-processing, we can do simple scaling and subtracting the - // data mean, if provided. Note that the mean subtraction is always carried - // out before scaling. - optional float scale = 2 [default = 1]; - optional string mean_file = 3; - // Specify the batch size. - optional uint32 batch_size = 4; - // Specify if we would like to randomly crop an image. - optional uint32 crop_size = 5 [default = 0]; - // Specify if we want to randomly mirror data. - optional bool mirror = 6 [default = false]; - // Foreground (object) overlap threshold - optional float fg_threshold = 7 [default = 0.5]; - // Background (non-object) overlap threshold - optional float bg_threshold = 8 [default = 0.5]; - // Fraction of batch that should be foreground objects - optional float fg_fraction = 9 [default = 0.25]; - // Amount of contextual padding to add around a window - // (used only by the window_data_layer) - optional uint32 context_pad = 10 [default = 0]; - // Mode for cropping out a detection window - // warp: cropped window is warped to a fixed size and aspect ratio - // square: the tightest square around the window is cropped - optional string crop_mode = 11 [default = "warp"]; - // cache_images: will load all images in memory for faster access - optional bool cache_images = 12 [default = false]; - // append root_folder to locate images - optional string root_folder = 13 [default = ""]; -} - -message SPPParameter { - enum PoolMethod { - MAX = 0; - AVE = 1; - STOCHASTIC = 2; - } - optional uint32 pyramid_height = 1; - optional PoolMethod pool = 2 [default = MAX]; // The pooling method - enum Engine { - DEFAULT = 0; - CAFFE = 1; - CUDNN = 2; - } - optional Engine engine = 6 [default = DEFAULT]; -} - -// DEPRECATED: use LayerParameter. -message V1LayerParameter { - repeated string bottom = 2; - repeated string top = 3; - optional string name = 4; - repeated NetStateRule include = 32; - repeated NetStateRule exclude = 33; - enum LayerType { - NONE = 0; - ABSVAL = 35; - ACCURACY = 1; - ARGMAX = 30; - BNLL = 2; - CONCAT = 3; - CONTRASTIVE_LOSS = 37; - CONVOLUTION = 4; - DATA = 5; - DECONVOLUTION = 39; - DROPOUT = 6; - DUMMY_DATA = 32; - EUCLIDEAN_LOSS = 7; - ELTWISE = 25; - EXP = 38; - FLATTEN = 8; - HDF5_DATA = 9; - HDF5_OUTPUT = 10; - HINGE_LOSS = 28; - IM2COL = 11; - IMAGE_DATA = 12; - INFOGAIN_LOSS = 13; - INNER_PRODUCT = 14; - LRN = 15; - MEMORY_DATA = 29; - MULTINOMIAL_LOGISTIC_LOSS = 16; - MVN = 34; - POOLING = 17; - POWER = 26; - RELU = 18; - SIGMOID = 19; - SIGMOID_CROSS_ENTROPY_LOSS = 27; - SILENCE = 36; - SOFTMAX = 20; - SOFTMAX_LOSS = 21; - SPLIT = 22; - SLICE = 33; - TANH = 23; - WINDOW_DATA = 24; - THRESHOLD = 31; - QUANT = 208; - DEQUANT = 209; - } - optional LayerType type = 5; - repeated BlobProto blobs = 6; - repeated string param = 1001; - repeated DimCheckMode blob_share_mode = 1002; - enum DimCheckMode { - STRICT = 0; - PERMISSIVE = 1; - } - repeated float blobs_lr = 7; - repeated float weight_decay = 8; - repeated float loss_weight = 35; - optional AccuracyParameter accuracy_param = 27; - optional ArgMaxParameter argmax_param = 23; - optional ConcatParameter concat_param = 9; - optional ContrastiveLossParameter contrastive_loss_param = 40; - optional ConvolutionParameter convolution_param = 10; - optional DataParameter data_param = 11; - optional DropoutParameter dropout_param = 12; - optional DummyDataParameter dummy_data_param = 26; - optional EltwiseParameter eltwise_param = 24; - optional ExpParameter exp_param = 41; - optional HDF5DataParameter hdf5_data_param = 13; - optional HDF5OutputParameter hdf5_output_param = 14; - optional HingeLossParameter hinge_loss_param = 29; - optional ImageDataParameter image_data_param = 15; - optional InfogainLossParameter infogain_loss_param = 16; - optional InnerProductParameter inner_product_param = 17; - optional LRNParameter lrn_param = 18; - optional MemoryDataParameter memory_data_param = 22; - optional MVNParameter mvn_param = 34; - optional PoolingParameter pooling_param = 19; - optional PowerParameter power_param = 21; - optional ReLUParameter relu_param = 30; - optional SigmoidParameter sigmoid_param = 38; - optional SoftmaxParameter softmax_param = 39; - optional SliceParameter slice_param = 31; - optional TanHParameter tanh_param = 37; - optional ThresholdParameter threshold_param = 25; - optional WindowDataParameter window_data_param = 20; - optional TransformationParameter transform_param = 36; - optional LossParameter loss_param = 42; - optional V0LayerParameter layer = 1; -} - -// DEPRECATED: V0LayerParameter is the old way of specifying layer parameters -// in Caffe. We keep this message type around for legacy support. -message V0LayerParameter { - optional string name = 1; // the layer name - optional string type = 2; // the string to specify the layer type - - // Parameters to specify layers with inner products. - optional uint32 num_output = 3; // The number of outputs for the layer - optional bool biasterm = 4 [default = true]; // whether to have bias terms - optional FillerParameter weight_filler = 5; // The filler for the weight - optional FillerParameter bias_filler = 6; // The filler for the bias - - optional uint32 pad = 7 [default = 0]; // The padding size - optional uint32 kernelsize = 8; // The kernel size - optional uint32 group = 9 [default = 1]; // The group size for group conv - optional uint32 stride = 10 [default = 1]; // The stride - enum PoolMethod { - MAX = 0; - AVE = 1; - STOCHASTIC = 2; - } - optional PoolMethod pool = 11 [default = MAX]; // The pooling method - optional float dropout_ratio = 12 [default = 0.5]; // dropout ratio - - optional uint32 local_size = 13 [default = 5]; // for local response norm - optional float alpha = 14 [default = 1.]; // for local response norm - optional float beta = 15 [default = 0.75]; // for local response norm - optional float k = 22 [default = 1.]; - - // For data layers, specify the data source - optional string source = 16; - // For data pre-processing, we can do simple scaling and subtracting the - // data mean, if provided. Note that the mean subtraction is always carried - // out before scaling. - optional float scale = 17 [default = 1]; - optional string meanfile = 18; - // For data layers, specify the batch size. - optional uint32 batchsize = 19; - // For data layers, specify if we would like to randomly crop an image. - optional uint32 cropsize = 20 [default = 0]; - // For data layers, specify if we want to randomly mirror data. - optional bool mirror = 21 [default = false]; - - // The blobs containing the numeric parameters of the layer - repeated BlobProto blobs = 50; - // The ratio that is multiplied on the global learning rate. If you want to - // set the learning ratio for one blob, you need to set it for all blobs. - repeated float blobs_lr = 51; - // The weight decay that is multiplied on the global weight decay. - repeated float weight_decay = 52; - - // The rand_skip variable is for the data layer to skip a few data points - // to avoid all asynchronous sgd clients to start at the same point. The skip - // point would be set as rand_skip * rand(0,1). Note that rand_skip should not - // be larger than the number of keys in the database. - optional uint32 rand_skip = 53 [default = 0]; - - // Fields related to detection (det_*) - // foreground (object) overlap threshold - optional float det_fg_threshold = 54 [default = 0.5]; - // background (non-object) overlap threshold - optional float det_bg_threshold = 55 [default = 0.5]; - // Fraction of batch that should be foreground objects - optional float det_fg_fraction = 56 [default = 0.25]; - - // optional bool OBSOLETE_can_clobber = 57 [default = true]; - - // Amount of contextual padding to add around a window - // (used only by the window_data_layer) - optional uint32 det_context_pad = 58 [default = 0]; - - // Mode for cropping out a detection window - // warp: cropped window is warped to a fixed size and aspect ratio - // square: the tightest square around the window is cropped - optional string det_crop_mode = 59 [default = "warp"]; - - // For ReshapeLayer, one needs to specify the new dimensions. - optional int32 new_num = 60 [default = 0]; - optional int32 new_channels = 61 [default = 0]; - optional int32 new_height = 62 [default = 0]; - optional int32 new_width = 63 [default = 0]; - - // Whether or not ImageLayer should shuffle the list of files at every epoch. - // It will also resize images if new_height or new_width are not zero. - optional bool shuffle_images = 64 [default = false]; - - // For ConcatLayer, one needs to specify the dimension for concatenation, and - // the other dimensions must be the same for all the bottom blobs. - // By default it will concatenate blobs along the channels dimension. - optional uint32 concat_dim = 65 [default = 1]; - - optional HDF5OutputParameter hdf5_output_param = 1001; -} - -message PReLUParameter { - // Parametric ReLU described in K. He et al, Delving Deep into Rectifiers: - // Surpassing Human-Level Performance on ImageNet Classification, 2015. - - // Initial value of a_i. Default is a_i=0.25 for all i. - optional FillerParameter filler = 1; - // Whether or not slope parameters are shared across channels. - optional bool channel_shared = 2 [default = false]; -} - -// Message that stores parameters used by DetectionOutputLayer -//message DetectionOutputParameter { -// optional int32 num_classes = 1 [default = 21]; -// optional float nms_threshold = 2 [default = 0.3]; -// optional int32 top_k = 3; -// optional float confidence_threshold = 4 [default = 0.8]; -//} - -// Message that store parameters used by PriorBoxLayer -message PriorBoxParameter { - // Encode/decode type. - enum CodeType { - CORNER = 1; - CENTER_SIZE = 2; - CORNER_SIZE = 3; - } - // Minimum box size (in pixels). Required! - repeated float min_size = 1; - // Maximum box size (in pixels). Required! - repeated float max_size = 2; - // Various of aspect ratios. Duplicate ratios will be ignored. - // If none is provided, we use default ratio 1. - repeated float aspect_ratio = 3; - // If true, will flip each aspect ratio. - // For example, if there is aspect ratio "r", - // we will generate aspect ratio "1.0/r" as well. - optional bool flip = 4 [default = true]; - // If true, will clip the prior so that it is within [0, 1] - optional bool clip = 5 [default = false]; - // Variance for adjusting the prior bboxes. - repeated float variance = 6; - // By default, we calculate img_height, img_width, step_x, step_y based on - // bottom[0] (feat) and bottom[1] (img). Unless these values are explicitely - // provided. - // Explicitly provide the img_size. - optional uint32 img_size = 7; - // Either img_size or img_h/img_w should be specified; not both. - optional uint32 img_h = 8; - optional uint32 img_w = 9; - - // Explicitly provide the step size. - optional float step = 10; - // Either step or step_h/step_w should be specified; not both. - optional float step_h = 11; - optional float step_w = 12; - - // Offset to the top left corner of each cell. - optional float offset = 13 [default = 0.5]; -} - -// Message that stores parameters used by PermutetLayer -message PermuteParameter { - // The new orders of the axes of data. Notice it should be with - // in the same range as the input data, and it starts from 0. - // Do not provide repeated order. - repeated uint32 order = 1; -} - -message NormalizeParameter { - optional bool across_spatial = 1 [default = true]; - // Initial value of scale. Default is 1.0 for all - optional FillerParameter scale_filler = 2; - // Whether or not scale parameters are shared across channels. - optional bool channel_shared = 3 [default = true]; - // Epsilon for not dividing by zero while normalizing variance - optional float eps = 4 [default = 1e-10]; -} - -// needed by ssd -message SaveOutputParameter { - // Output directory. If not empty, we will save the results. - optional string output_directory = 1; - // Output name prefix. - optional string output_name_prefix = 2; - // Output format. - // VOC - PASCAL VOC output format. - // COCO - MS COCO output format. - optional string output_format = 3; - // If you want to output results, must also provide the following two files. - // Otherwise, we will ignore saving results. - // label map file. - optional string label_map_file = 4; - // A file which contains a list of names and sizes with same order - // of the input DB. The file is in the following format: - // name height width - // ... - optional string name_size_file = 5; - // Number of test images. It can be less than the lines specified in - // name_size_file. For example, when we only want to evaluate on part - // of the test images. - optional uint32 num_test_image = 6; - // The resize parameter used in saving the data. - // optional ResizeParameter resize_param = 7; -} - -message NonMaximumSuppressionParameter { - // Threshold to be used in nms. - optional float nms_threshold = 1 [default = 0.3]; - // Maximum number of results to be kept. - optional int32 top_k = 2; - // Parameter for adaptive nms. - optional float eta = 3 [default = 1.0]; -} - -message GeneralNmsParameter { - optional int32 post_top_k = 1 ; - optional float nms_threshold = 2 [default = 0]; - optional float iou_threshold_decay = 3 [default = 1.0]; - optional float coor_scale_factor = 4 [default = 1.0]; -} - -// Message that store parameters used by DetectionOutputLayer, ssd/fasterRcnn -message DetectionOutputParameter { - optional int32 num_classes = 1; - optional bool share_location = 2 [default = true]; - optional int32 background_label_id = 3 [default = 0]; - optional NonMaximumSuppressionParameter nms_param = 4; - optional SaveOutputParameter save_output_param = 5; - optional PriorBoxParameter.CodeType code_type = 6 [default = CENTER_SIZE]; - optional bool variance_encoded_in_target = 8 [default = true]; - optional int32 keep_top_k = 7; - optional float confidence_threshold = 9; - optional float nms_threshold = 13; - optional int32 top_k = 14; - optional int32 boxes = 15 [default = 1]; - optional bool relative = 17 [default = true]; - optional float objectness_threshold = 18 [default = 0.5]; - optional float class_threshold = 19 [default = 0.5]; - repeated float biases = 20; - optional GeneralNmsParameter general_nms_param = 21; - optional float objectness_score = 22; -} -message PSROIPoolingParameter { - required float spatial_scale = 1; - required int32 output_dim = 2; // output channel number - required int32 group_size = 3; // number of groups to encode position-sensitive score maps -} -// Message that stores parameters used by FreespaceExtractLayer -message FreespaceExtractParameter { - optional float org_height = 1; -} - -// Message that stores parameters used by DetectpostprocessLayer -message PostprocessParameter { - optional float nms_thresh = 1 [default = 0.3]; - optional float conf_thresh = 2 [default = 0.5]; - optional uint32 post_nms_topn = 3 [default = 100]; - optional uint32 cls_num = 4 [default = 12]; - repeated float bbox_reg_weights = 5; -} - -// Message that stores parameters used by SpatialTransformLayer -message SpatialTransformParameter { - optional uint32 output_h = 1 [default = 0]; - optional uint32 output_w = 2 [default = 0]; - optional float border_value = 3 [default = 0]; - repeated float affine_transform = 4; - enum Engine { - DEFAULT = 0; - CAFFE = 1; - CUDNN = 2; - } - optional Engine engine = 15 [default = DEFAULT]; -} -message ROIAlignParameter { - // Pad, kernel size, and stride are all given as a single value for equal - // dimensions in height and width or as Y, X pairs. - optional uint32 pooled_h = 1 [default = 0]; // The pooled output height - optional uint32 pooled_w = 2 [default = 0]; // The pooled output width - // Multiplicative spatial scale factor to translate ROI coords from their - // input scale to the scale used when pooling - optional float spatial_scale = 3 [default = 1]; - optional int32 sampling_ratio = 4 [default = -1]; - optional int32 roi_end_mode = 5 [default = 0]; -} - -message RegionParameter { - optional uint32 classes = 1 [default = 20]; // Category of classification - optional uint32 coords = 2 [default = 4]; // Coordinates of box - optional uint32 boxes = 3 [default = 1]; // Number of boxes predicted per grid - optional uint32 softmax = 4 [default = 0]; - optional string softmax_tree = 5 [default = ""]; - optional uint32 background = 6 [default = 0]; -} -message ReorgParameter{ - optional uint32 stride = 2 [default = 2]; - optional bool reverse = 1 [default = false]; -} -message ReverseParameter{ - repeated int32 axis = 1; -} -message InterpParameter{ - optional int32 height = 1 [default = 0];//Height of output - optional int32 width = 2 [default = 0];//Width of output - optional int32 zoom_factor = 3 [default = 1];//zoom factor - optional int32 shrink_factor = 4 [default = 1];//shrink factor - optional int32 pad_beg = 5 [default = 0];//padding at begin of input - optional int32 pad_end = 6 [default = 0];//padding at end of input -} -message ShuffleChannelParameter{ - optional uint32 group = 1[default = 1]; // The number of group -} -message UpsampleParameter{ - optional float scale = 1[default = 1]; - optional int32 stride = 2[default = 2]; - optional int32 stride_h = 3[default = 2]; - optional int32 stride_w = 4[default=2]; -} -message ROIPoolingParameter { - required int32 pooled_h = 1; - required int32 pooled_w = 2; - optional float spatial_scale = 3 [default=0.0625]; - optional float spatial_scale_h = 4; - optional float spatial_scale_w = 5; -} - -message YoloParameter { - optional int32 boxes = 1 [default = 3]; - optional int32 coords = 2 [default = 4]; - optional int32 classes = 3 [default = 80]; - optional string yolo_version = 4 [default = "V3"]; - optional bool softmax = 5 [default = false]; - optional bool background = 6 [default = false]; - optional bool softmaxtree = 7 [default = false]; -} - -message YoloV3DetectionOutputParameter { - optional int32 boxes = 1 [default = 3]; - optional int32 classes = 2 [default = 80]; - optional bool relative = 3 [default = true]; - optional float obj_threshold = 4 [default = 0.5]; - optional float score_threshold = 5 [default = 0.5]; - optional float iou_threshold = 6 [default = 0.45]; - optional int32 pre_nms_topn = 7 [default = 512]; - optional int32 post_nms_topn = 8 [default = 1024]; - repeated float biases_high = 9; - repeated float biases_mid = 10; - repeated float biases_low = 11; - optional int32 coords = 12 [default = 4]; - repeated float biases = 13; - optional bool resize_origin_img_to_net = 14 [default = false]; -} - -message YoloV3DetectionOutputV2Parameter { - optional int32 boxes = 1 [default = 3]; - optional int32 classes = 2 [default = 80]; - optional bool relative = 3 [default = true]; - optional float obj_threshold = 4 [default = 0.5]; - optional float score_threshold = 5 [default = 0.5]; - optional float iou_threshold = 6 [default = 0.45]; - optional int32 pre_nms_topn = 7 [default = 512]; - optional int32 post_nms_topn = 8 [default = 1024]; - repeated float biases_high = 9; - repeated float biases_mid = 10; - repeated float biases_low = 11; - optional int32 coords = 12 [default = 4]; - repeated float biases = 13; - optional bool resize_origin_img_to_net = 14 [default = false]; - optional int32 out_box_dim = 15 [default = 3]; -} - -message ProposalParameter { - optional float feat_stride = 1 [default = 16]; - optional float base_size = 2 [default = 16]; - optional float min_size = 3 [default = 16]; - repeated float ratio = 4; - repeated float scale = 5; - optional int32 pre_nms_topn = 6 [default = 3000]; - optional int32 post_nms_topn = 7 [default = 304]; - optional float iou_threshold = 8 [default = 0.7]; - optional bool output_actual_rois_num = 9 [default = false]; -} - -message FSRDetectionOutputParameter { - required int32 num_classes = 1; - required float score_threshold = 2; - required float iou_threshold = 3; - optional int32 batch_rois = 4 [default = 1]; -} - -message SSDDetectionOutputParameter { - required int32 num_classes= 1 [default = 2]; - optional bool share_location = 2 [default = true]; - optional int32 background_label_id = 3 [default = 0]; - optional float iou_threshold = 4 [default = 0.3]; - optional int32 top_k = 5 [default = 200]; - optional float eta = 6 [default = 1.0]; - optional bool variance_encoded_in_target = 7 [default = false]; - optional int32 code_type = 8 [default = 1]; - optional int32 keep_top_k = 9 [default = -1]; - optional float confidence_threshold = 10 [default = 0.0]; -} -message YoloV2DetectionOutputParameter { - optional int32 boxes = 1 [default = 5]; - optional int32 classes = 2 [default = 80]; - optional bool relative = 3 [default = true]; - optional float obj_threshold = 4 [default = 0.5]; - optional float score_threshold = 5 [default = 0.5]; - optional float iou_threshold = 6 [default = 0.45]; - optional int32 pre_nms_topn = 7 [default = 512]; - optional int32 post_nms_topn = 8 [default = 1024]; - repeated float biases = 9; - optional int32 coords = 10 [default = 4]; - optional bool resize_origin_img_to_net = 11 [default = false]; -} - -message QuantParameter { - optional float scale = 2; - optional bytes offset = 3; -} - -message BatchMatMulParameter{ - optional bool adj_x1 = 1 [default = false]; - optional bool adj_x2 = 2 [default = false]; -} - -message CondTakeParameter { - required string mode = 1; - required float val = 2; - optional float eps = 3 [default = 1e-06]; -} - -message MatrixInverseParameter { - optional bool adjoint = 1 [default = false]; -} - -message WarpPerspectiveParameter { - required int32 out_height = 1; - required int32 out_width = 2; - optional float constant = 3; - optional string border_type = 4 [default = 'BORDER_CONSTANT']; -} - -message SpatialTransformerParameter { - // How to use the parameter passed by localisation network - optional string transform_type = 1 [default = "affine"]; - // What is the sampling technique - optional string sampler_type = 2 [default = "bilinear"]; - - // If not set,stay same with the input dimension H and W - optional int32 output_H = 3; - optional int32 output_W = 4; - // If false, only compute dTheta, DO NOT compute dU - optional bool to_compute_dU = 5 [default = true]; - - // The default value for some parameters - optional double theta_1_1 = 6; - optional double theta_1_2 = 7; - optional double theta_1_3 = 8; - optional double theta_2_1 = 9; - optional double theta_2_2 = 10; - optional double theta_2_3 = 11; -} diff --git a/ge/proto/dump_task.proto b/ge/proto/dump_task.proto deleted file mode 100644 index a2411ddb..00000000 --- a/ge/proto/dump_task.proto +++ /dev/null @@ -1,113 +0,0 @@ -syntax = "proto3"; -package toolkit.dump; - -enum OutputDataType { - DT_UNDEFINED = 0; - DT_FLOAT = 1; - DT_FLOAT16 = 2; - DT_INT8 = 3; - DT_UINT8 = 4; - DT_INT16 = 5; - DT_UINT16 = 6; - DT_INT32 = 7; - DT_INT64 = 8; - DT_UINT32 = 9; - DT_UINT64 = 10; - DT_BOOL = 11; - DT_DOUBLE = 12; - DT_STRING = 13; - DT_DUAL_SUB_INT8 = 14; - DT_DUAL_SUB_UINT8 = 15; - DT_COMPLEX64 = 16; - DT_COMPLEX128 = 17; - DT_QINT8 = 18; - DT_QINT16 = 19; - DT_QINT32 = 20; - DT_QUINT8 = 21; - DT_QUINT16 = 22; - DT_RESOURCE = 23; - DT_STRING_REF = 24; - DT_DUAL = 25; - DT_VARIANT = 26; -} - -enum OutputFormat { - FORMAT_NCHW = 0; - FORMAT_NHWC = 1; - FORMAT_ND = 2; - FORMAT_NC1HWC0 = 3; - FORMAT_FRACTAL_Z = 4; - FORMAT_NC1C0HWPAD = 5; - FORMAT_NHWC1C0 = 6; - FORMAT_FSR_NCHW = 7; - FORMAT_FRACTAL_DECONV = 8; - FORMAT_C1HWNC0 = 9; - FORMAT_FRACTAL_DECONV_TRANSPOSE = 10; - FORMAT_FRACTAL_DECONV_SP_STRIDE_TRANS = 11; - FORMAT_NC1HWC0_C04 = 12; - FORMAT_FRACTAL_Z_C04 = 13; - FORMAT_CHWN = 14; - FORMAT_FRACTAL_DECONV_SP_STRIDE8_TRANS = 15; - FORMAT_HWCN = 16; - FORMAT_NC1KHKWHWC0 = 17; - FORMAT_BN_WEIGHT = 18; - FORMAT_FILTER_HWCK = 19; - FORMAT_HASHTABLE_LOOKUP_LOOKUPS=20; - FORMAT_HASHTABLE_LOOKUP_KEYS = 21; - FORMAT_HASHTABLE_LOOKUP_VALUE = 22; - FORMAT_HASHTABLE_LOOKUP_OUTPUT = 23; - FORMAT_HASHTABLE_LOOKUP_HITS=24; - FORMAT_C1HWNCoC0 = 25; - FORMAT_MD = 26; - FORMAT_NDHWC = 27; - FORMAT_FRACTAL_ZZ = 28; - FORMAT_FRACTAL_NZ = 29; - FORMAT_RESERVED = 30; -} - -message OriginalOp { - string name = 1; - uint32 output_index = 2; - OutputDataType data_type = 3; - OutputFormat format = 4; -} - -message Shape { - repeated uint64 dim = 1; -} - -message OpOutput { - OutputDataType data_type = 1; - OutputFormat format = 2; - Shape shape = 3; - OriginalOp original_op = 4; // the original op corresponding to the output - bytes data = 5; - uint64 size = 6; -} - -message OpInput { - OutputDataType data_type = 1; - OutputFormat format = 2; - Shape shape = 3; - bytes data = 4; - uint64 size = 5; -} - -enum BufferType { - L1 = 0; -} - -message OpBuffer { - BufferType buffer_type = 1; - bytes data = 2; - uint64 size = 3; -} - -message DumpData{ - string version = 1; - uint64 dump_time = 2; - repeated OpOutput output = 3; - repeated OpInput input = 4; - repeated OpBuffer buffer = 5; - string op_name = 6; -} diff --git a/ge/proto/fusion_model.proto b/ge/proto/fusion_model.proto deleted file mode 100755 index c92c5581..00000000 --- a/ge/proto/fusion_model.proto +++ /dev/null @@ -1,21 +0,0 @@ -/* Copyright (C) 2018. Huawei Technologies Co., Ltd. All rights reserved. - * - * This program is free software; you can redistribute it and/or modify - * it under the terms of the Apache License Version 2.0.You may not use this file except in compliance with the License. - * - * This program is distributed in the hope that it will be useful, - * but WITHOUT ANY WARRANTY; without even the implied warranty of - * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - * Apache License for more details at - * http://www.apache.org/licenses/LICENSE-2.0 - */ -syntax = "proto3"; - -import "om.proto"; - -package domi; - -message FusionModelDef { - string version = 1; - repeated OpDef fusion_op = 2; -} \ No newline at end of file diff --git a/ge/proto/fwk_adapter.proto b/ge/proto/fwk_adapter.proto deleted file mode 100644 index 9335c926..00000000 --- a/ge/proto/fwk_adapter.proto +++ /dev/null @@ -1,37 +0,0 @@ -/* Copyright (C) 2018. Huawei Technologies Co., Ltd. All rights reserved. - * - * This program is free software; you can redistribute it and/or modify - * it under the terms of the Apache License Version 2.0.You may not use this file except in compliance with the License. - * - * This program is distributed in the hope that it will be useful, - * but WITHOUT ANY WARRANTY; without even the implied warranty of - * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - * Apache License for more details at - * http://www.apache.org/licenses/LICENSE-2.0 - */ -syntax = "proto3"; - -package aicpu.FWKAdapter; -option cc_enable_arenas = true; - - -// Defines an struct for input and output. -message TensorDataInfo { - - // value DataType - uint32 dtype = 1; - - // shape dim - repeated int64 dim = 2; - - // data point addr - int64 data_addr = 3; -} - -message KernelRunParam { - // input - repeated TensorDataInfo input = 1; - // output - repeated TensorDataInfo output = 2; -} - diff --git a/ge/proto/ge_api.proto b/ge/proto/ge_api.proto deleted file mode 100755 index 331c5aea..00000000 --- a/ge/proto/ge_api.proto +++ /dev/null @@ -1,88 +0,0 @@ -syntax = "proto3"; -package ge.api_pb; - -import "ge_ir.proto"; - -// GE initialize -message GEInitialize { - map options = 1; -}; - -// initialize response -message GEInitializeResponse { - uint32 status = 1; - uint32 clientId = 2; -}; - -// GE finalize -message GEFinalize { - bool final = 1; - uint32 clientId = 2; -}; - -message GEFinalizeResponse { - uint32 status = 1; -}; - -// GE Session -message CreateSession{ - map options = 1; -}; - -message CreateSessionResponse { - uint32 status = 1; - uint64 sessionId = 2; -}; - -//GE AddGraph -//model serialize :: serializegraph -message SessionAddGraph{ - uint32 graphId = 1; - uint64 sessionId = 2; - ge.proto.GraphDef graph = 3; -}; - -message SessionAddGraphResponse { - uint32 status = 1; -}; - -//GE SessionRemoveGraph -message SessionRemoveGraph{ - uint32 graphId = 1; - uint64 sessionId = 2; -}; - -message SessionRemoveGraphResponse { - uint32 status = 1; -}; - -message SessionRunGraph{ - uint32 graphId = 1; - uint64 sessionId = 2; - repeated ge.proto.TensorDef tensor = 3; -}; - -message SessionBuildGraph{ - uint32 graphId = 1; - uint64 sessionId = 2; - repeated ge.proto.TensorDef tensor = 3; - string savePath = 4; -}; - -message SessionRunGraphResponse { - uint32 status = 1; - repeated ge.proto.TensorDef tensor = 2; -}; - -message SessionBuildGraphResponse { - uint32 status = 1; -}; - -message DestroySession{ - bool final = 1; - uint64 sessionId = 2; -}; - -message DestroySessionResponse { - uint32 status = 1; -}; diff --git a/ge/proto/ge_ir.proto b/ge/proto/ge_ir.proto deleted file mode 100644 index c0ef3071..00000000 --- a/ge/proto/ge_ir.proto +++ /dev/null @@ -1,193 +0,0 @@ -syntax = "proto3"; - -package ge.proto; - -enum DataType -{ - DT_UNDEFINED = 0; // Used to indicate a DataType field has not been set. - DT_FLOAT = 1; // float type - DT_FLOAT16 = 2; // fp16 type - DT_INT8 = 3; // int8 type - DT_UINT8 = 4; // uint8 type - DT_INT16 = 5; // int16 type - DT_UINT16 = 6; // uint16 type - DT_INT32 = 7; // - DT_INT64 = 8; // int64 type - DT_UINT32 = 9; // unsigned int32 - DT_UINT64 = 10; // unsigned int64 - DT_BOOL = 11; // bool type - DT_DOUBLE = 12; // double type - DT_STRING = 13; // string type - DT_DUAL_SUB_INT8 = 14; /**< dual output int8 type */ - DT_DUAL_SUB_UINT8 = 15; /**< dual output uint8 type */ - DT_COMPLEX64 = 16; // complex64 type - DT_COMPLEX128 = 17; // complex128 type - DT_QINT8 = 18; // qint8 type - DT_QINT16 = 19; // qint16 type - DT_QINT32 = 20; // qint32 type - DT_QUINT8 = 21; // quint8 type - DT_QUINT16 = 22; // quint16 type - DT_RESOURCE = 23; // resource type - DT_STRING_REF = 24; // string_ref type - DT_DUAL = 25; /**< dual output type */ - DT_VARIANT = 26; // variant type - DT_BF16 = 27; // bf16 type - DT_INT4 = 28; // int4 type -} - -message AttrDef -{ - message ListValue - { - enum ListValueType{ - VT_LIST_NONE = 0; - VT_LIST_STRING = 1; - VT_LIST_INT = 2; - VT_LIST_FLOAT = 3; - VT_LIST_BOOL = 4; - VT_LIST_BYTES = 5; - VT_LIST_TENSOR_DESC = 6; - VT_LIST_TENSOR = 7; - VT_LIST_GRAPH = 8; - VT_LIST_NAMED_ATTRS = 9; - VT_LIST_DATA_TYPE = 10; - } - repeated bytes s = 2; // "list(string)" - repeated int64 i = 3; // "list(int)" - repeated float f = 4; // "list(float)" - repeated bool b = 5; // "list(bool)" - repeated bytes bt = 7; - repeated TensorDescriptor td = 8; - repeated TensorDef t = 9; - repeated GraphDef g = 10; - repeated NamedAttrs na = 11; - repeated int64 dt = 12; // list ge::DataType - - ListValueType val_type = 20; - } - - message ListListInt{ - message ListInt{ - repeated int64 list_i = 1; // list int - } - repeated ListInt list_list_i = 1; // list list int - } - - oneof value - { - bytes s = 2; // "string" - int64 i = 3; // "int" - float f = 4; // "float" - bool b = 5; // "bool" - bytes bt = 7; - ListValue list = 1; // any "list(...)" - NamedAttrs func = 10; // Used to support attr nesting - TensorDescriptor td = 11; // GeTensorDesc type - TensorDef t = 12; // GeTensor type - GraphDef g = 13; // Graph type - ListListInt list_list_int = 14; // List List Int type - int64 dt = 15; // ge::DataType - } -} - -// A list of attr names and their values. The whole list is attached -// with a string name. E.g., MatMul[T=float]. -message NamedAttrs -{ - string name = 1; - map attr = 2; -} - -// Shape / dimension description, using row-major order -message ShapeDef -{ - repeated int64 dim = 1; // Size of each dimension -} - -// Multidimensional data description -message TensorDescriptor -{ - string name = 1; // Optional parameter, tensor name - - DataType dtype = 2; // tensor datatype - ShapeDef shape = 3; // Shape / dimension - string layout = 4; // Tensor format, eg: "NCHW", "NHWC", "CHW", "ND" - - bool has_out_attr = 9; - int64 size = 10; - int64 weight_size = 11; - bool reuse_input = 12; - bool output_tensor = 13; - string device_type = 14; - bool input_tensor =15; - int64 real_dim_cnt = 16; - int64 reuse_input_index = 17; - int64 data_offset = 18; - int64 cmps_size = 19; - string cmps_tab = 20; - int64 cmps_tab_offset = 21; - - map attr = 5; // Set of extra parameter fields -} - -// GeTensor definition -message TensorDef -{ - TensorDescriptor desc = 1; // Tensor description - bytes data = 2; // Tensor data -} - - -// Operator description -message OpDef -{ - string name = 1; // name - string type = 2; // type - - repeated string input = 5; // input original op name + outgoing index. op_name锛歩ndex - - map attr = 10; // Set of operator parameter fields - - bool has_out_attr = 20; - int64 id = 21; - int64 stream_id =22; - repeated string input_name = 23; - repeated string src_name = 24; - repeated int64 src_index = 25; - repeated string dst_name = 26; - repeated int64 dst_index = 27; - repeated int64 input_i = 28; - repeated int64 output_i = 29; - repeated int64 workspace = 30; - repeated int64 workspace_bytes = 31; - repeated bool is_input_const = 32; - repeated TensorDescriptor input_desc = 33; - repeated TensorDescriptor output_desc = 34; - repeated string subgraph_name = 35; -} - -// Graph definition -message GraphDef -{ - string name = 1; // name - - repeated string input = 4; // Graph input - repeated string output = 5; // Graph output - - repeated OpDef op = 6; // List of operators - - map attr = 11; // Extended field -} - -// model definition -message ModelDef -{ - string name = 1; // name - uint32 version = 2; // IR Proto verion - string custom_version = 3; // User model version number, passed in by user - - repeated GraphDef graph = 7; // Graph definition锛実raph[0] represents the main diagram in modeldef - - map attr = 11; // Extended field -} - diff --git a/ge/proto/insert_op.proto b/ge/proto/insert_op.proto deleted file mode 100644 index 7d708865..00000000 --- a/ge/proto/insert_op.proto +++ /dev/null @@ -1,140 +0,0 @@ -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; - - // related_input_name is optional and the top name of data node which inserts aipp - string related_input_name = 6; - - // 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; - float padding_value = 72; - - 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 -} diff --git a/ge/proto/om.proto b/ge/proto/om.proto deleted file mode 100644 index e15e5f80..00000000 --- a/ge/proto/om.proto +++ /dev/null @@ -1,396 +0,0 @@ -/* Copyright (C) 2018. Huawei Technologies Co., Ltd. All rights reserved. - * - * This program is free software; you can redistribute it and/or modify - * it under the terms of the Apache License Version 2.0.You may not use this file except in compliance with the License. - * - * This program is distributed in the hope that it will be useful, - * but WITHOUT ANY WARRANTY; without even the implied warranty of - * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - * Apache License for more details at - * http://www.apache.org/licenses/LICENSE-2.0 - */ -syntax = "proto3"; - -package domi; - -enum TargetType -{ - MINI = 0; - TINY = 1; - LITE = 2; -} - -// offline model -message ModelDef { - string name = 1; - uint32 version = 2; - - uint64 memory_size = 10; - uint32 stream_num = 11; - uint32 event_num = 12; - uint64 weight_size = 13; - uint32 label_num = 15; - repeated OpDef op = 20; - TargetType target_type = 23; - - map attr = 30; -}; - -// operator define -message OpDef { - string name = 1; - string type = 2; - - uint32 id = 3; - uint32 stream_id = 4; - - repeated string input_name = 5; - - repeated string src_name = 8; - repeated int32 src_index = 9; - repeated int64 input = 10; - repeated int64 output = 11; - repeated TensorDescriptor input_desc = 12; - repeated TensorDescriptor output_desc = 13; - repeated WeightDef weights = 14; - repeated string dst_name = 15; - repeated int32 dst_index = 16; - - repeated int64 workspace = 20; - repeated uint32 workspace_bytes = 21; - - repeated string weight_name = 22; - repeated bool is_input_const = 23; - - map attr = 30; - - QuantizeFactorParams quantize_factor = 31; - - oneof op_params { - // start at 100 here - SendOpParams sender_param = 100; - RecvOpParams receiver_param = 200; - ConvolutionOpParams convolution_param = 300; - PoolingOpParams pooling_param = 400; - EltwiseOpParams eltwise_param = 500; - BatchNormOpParams batchnorm_param = 600; - ScaleOpParams scale_param = 700; - FullConnectionOpParams full_connection_param = 800; - SoftmaxOpParams softmax_param = 900; - ActivationOpParams activation_param = 1000; - ReshapeOpParams reshape_param = 1100; - } -}; - -message SendOpParams { - uint32 event_id = 1; -}; - -message RecvOpParams { - uint32 event_id = 1; -}; - -enum QuantizeScaleType -{ - VECTOR_SCALE = 0; - SCALAR_SCALE = 1; -} - -enum QuantizeScaleMode -{ - NORMAL_MODE = 0; - SQRT_MODE = 1; -} - -enum QuantizeAlgorithm -{ - NON_OFFSET_ALGO = 0; - HALF_OFFSET_ALGO = 1; - ALL_OFFSET_ALGO = 2; -} -message QuantizeFactor -{ - QuantizeScaleMode scale_mode = 1; - bytes scale_value = 2; - int64 scale_offset = 3; - bytes offset_data_value = 4; - int64 offset_data_offset = 5; - bytes offset_weight_value = 6; - int64 offset_weight_offset = 7; - bytes offset_pad_value = 8; - int64 offset_pad_offset = 9; -}; - -message QuantizeCalcFactor -{ - bytes offsetw = 1; - int64 offsetw_offset = 2; - bytes offsetd = 3; - int64 offsetd_offset = 4; - bytes scalereq = 5; - int64 scaledreq_offset = 6; - bytes offsetdnext = 7; - int64 offsetdnext_offset = 8; -} - -message QuantizeFactorParams -{ - QuantizeAlgorithm quantize_algo = 1; - QuantizeScaleType scale_type = 2; - QuantizeFactor quantize_param = 3; - QuantizeFactor dequantize_param = 4; - QuantizeFactor requantize_param = 5; - QuantizeCalcFactor quantizecalc_param = 6; -}; - -message ConvolutionOpParams { - int32 mode = 1; - int32 algo = 2; - int32 pad_mode = 3; - uint32 group = 4; - uint32 num_output = 5; - - repeated uint32 pad = 10; - repeated uint32 stride = 11; - repeated uint32 dilation = 12; - repeated uint32 kernel = 13; - - float alpha = 20; - float beta = 21; - - WeightDef filter = 40; - WeightDef bias = 41; - - bool relu_flag = 62; - repeated uint32 adj = 70; - repeated uint32 target_shape = 71; - repeated uint32 before_pad = 72; -}; - -message PoolingOpParams { - int32 mode = 1; - int32 nan_opt = 2; - int32 pad_mode = 3; - bool global_pooling = 4; - - repeated uint32 window = 10; - repeated uint32 pad = 11; - repeated uint32 stride = 12; - bool ceil_mode = 13; - int32 data_mode = 14; - - float alpha = 20; - float beta = 21; - repeated uint32 before_pad = 22; -}; - -message EltwiseOpParams { - int32 mode = 1; - repeated float coeff = 2; - float alpha = 3; - float beta = 4; - repeated WeightDef weight = 5; - bool relu_flag = 6; -}; - -message ActivationOpParams { - int32 mode = 1; - float coef = 2; - float alpha = 3; - float beta = 4; -}; - -message BatchNormOpParams { - int32 mode = 1; - - float alpha = 2; - float beta = 3; - double epsilon = 4;//optinal,[default = 1e-5] - bool use_global_stats = 5; //optinal,by default true,testing mode - float moving_average_fraction = 6; //optinal,[default = .999]; - - WeightDef estimated_mean = 7; - WeightDef estimated_variance = 8; - - WeightDef scale = 9; - WeightDef bias = 10; -}; - -message ScaleOpParams { - WeightDef scale = 1; - WeightDef bias = 2; -}; - -message ReshapeOpParams { - float alpha = 1; - float beta = 2; - ShapeDef shape = 3; - int32 axis = 4; - int32 num_axes = 5; - int32 format = 6; -}; - -message SoftmaxOpParams { - int32 algo = 1; - int32 mode = 2; - float alpha = 3; - float beta = 4; -}; - -message FullConnectionOpParams { - WeightDef filter = 1; - WeightDef bias = 2; - uint32 num_output = 3; - bool relu_flag = 12; -}; - -message FlattenOpParams { - float alpha = 1; - float beta = 2; - int32 start_axis = 3; - int32 end_axis = 4; -} - -message AddLimitedOpParams { - float alpha = 1; - float beta = 2; - int32 axis = 3; - bool broadcast = 4; - - repeated WeightDef weight = 10; -}; - -message MulLimitedOpParams { - float alpha = 1; - float beta = 2; - int32 axis = 3; - bool broadcast = 4; - - repeated WeightDef weight = 10; -}; - -message AddOpParams { - float alpha = 1; - float beta = 2; - - repeated WeightDef weight = 10; -}; - -message MulOpParams { - float alpha = 1; - float beta = 2; - - repeated WeightDef weight = 10; -}; - -message SubOpParams { - float alpha = 1; - float beta = 2; - - repeated WeightDef weight = 10; -}; - -message BiasAddOpParams { - float alpha = 1; - float beta = 2; - - WeightDef bias = 10; -}; - -message MatMulOpParams { - float alpha = 1; - float beta = 2; - bool transposeX = 3; - bool transposeW = 4; - - WeightDef filter = 10; - WeightDef bias = 12; -}; - -message RsqrtOpParams { - float alpha = 1; - float beta = 2; -}; - - -message WeightDef { - int32 format = 1; - int32 data_type = 2; - ShapeDef shape = 3; - bytes data = 4; - int64 data_offset = 5; - uint32 cmps_size = 6; - bytes cmps_tab = 7; - int64 cmps_tab_offset = 10; - CompressInfo cmps_info = 8; - AllOffsetQuantizeInfo alloffset_quantize_info = 11; -} - -message ShapeDef { - repeated int64 dim = 1; -} - -enum DeviceType { - NPU = 0; // In default, we will use NPU. - CPU = 1; // CPU -} - -message AllOffsetQuantizeInfo { - float scale = 1; - int32 offset = 2; -} - -message TensorDescriptor { - int32 format = 1; - int32 data_type = 2; - repeated int64 dim = 3; - uint32 size = 4; - bool reuse_input = 5; - bool output_tensor = 7; - DeviceType device_type = 8; - bool input_tensor = 9; - uint32 real_dim_cnt = 10; - uint32 reuse_input_index = 11; - AllOffsetQuantizeInfo alloffset_quantize_info = 12; -} - -message CompressInfo { - int32 blockRow = 1; // block row - int32 blockCol = 2; // block col - int32 fractalK = 3; // fractal K - int32 fractalN = 4; // fractal N - int32 lastFractalK = 5; // K of last fractal - int32 lastFractalN = 6; // N of last fractal - int32 cubeSize = 7; // cube's length - int32 loadDir = 8; // data load directtiono 0:col load 1:row load -} - -message AttrDef { - message ListValue { - repeated string s = 2; // "list(string)" - repeated int64 i = 3 [packed = true]; // "list(int)" - repeated float f = 4 [packed = true]; // "list(float)" - repeated bool b = 5 [packed = true]; // "list(bool)" - repeated uint32 u = 6 [packed = true]; // "list(uint)" - repeated bytes bt = 7; - } - - oneof value { - string s = 2; // "string" - int64 i = 3; // "int" - float f = 4; // "float" - bool b = 5; // "bool" - uint32 u = 6; // "uint32" - bytes bt = 7; - ListValue list = 1; // any "list(...)" - NamedAttrs func = 10; - } -} - -// A list of attr names and their values. The whole list is attached -// with a string name. E.g., MatMul[T=float]. -message NamedAttrs { - string name = 1; - map attr = 2; -} - diff --git a/ge/proto/op_mapping.proto b/ge/proto/op_mapping.proto deleted file mode 100644 index d626eb49..00000000 --- a/ge/proto/op_mapping.proto +++ /dev/null @@ -1,75 +0,0 @@ -syntax = "proto3"; -package toolkit.aicpu.dump; - -message Shape { - repeated uint64 dim = 1; -} - -message Output { - int32 data_type = 1; - int32 format = 2; - Shape shape = 3; - uint64 address = 4; - string original_name = 5; - int32 original_output_index = 6; - int32 original_output_data_type = 7; - int32 original_output_format = 8; - uint64 size = 9; - Shape origin_shape = 10; -} - -message Input { - int32 data_type =1; - int32 format = 2; - Shape shape = 3; - uint64 address = 4; - uint64 size = 5; - Shape origin_shape = 6; -} - -enum BufferType { - L1 = 0; -} - -message OpBuffer { - BufferType buffer_type = 1; - uint64 address = 2; - uint64 size = 3; -} - -message Op { - string op_name = 1; - string op_type = 2; -} - -message Task { - uint32 task_id = 1; - uint32 stream_id = 2; - Op op = 3; - repeated Output output = 4; - bool end_graph = 5; - repeated Input input = 6; - repeated OpBuffer buffer = 7; -} - -message OpMappingInfo { - string dump_path = 1; - oneof model_name_param { - string model_name = 2; - } - oneof model_id_param { - uint32 model_id = 3; - } - oneof step_id { - uint64 step_id_addr = 4; - } - oneof iterations_per_loop { - uint64 iterations_per_loop_addr = 5; - } - oneof loop_cond { - uint64 loop_cond_addr = 6; - } - uint32 flag = 7; // 0x01 load, 0x00 unload - repeated Task task = 8; - string dump_step = 9; -} \ No newline at end of file diff --git a/ge/proto/optimizer_priority.proto b/ge/proto/optimizer_priority.proto deleted file mode 100644 index 769619cf..00000000 --- a/ge/proto/optimizer_priority.proto +++ /dev/null @@ -1,7 +0,0 @@ -syntax = "proto3"; -package ge.optimizers; - -// Default: GE>FE>AICPU -message Priority{ - repeated string optimizer = 1; -} \ No newline at end of file diff --git a/ge/proto/task.proto b/ge/proto/task.proto deleted file mode 100644 index 0da5631e..00000000 --- a/ge/proto/task.proto +++ /dev/null @@ -1,179 +0,0 @@ -/* Copyright (C) 2018. Huawei Technologies Co., Ltd. All rights reserved. - * - * This program is free software; you can redistribute it and/or modify - * it under the terms of the Apache License Version 2.0.You may not use this file except in compliance with the License. - * - * This program is distributed in the hope that it will be useful, - * but WITHOUT ANY WARRANTY; without even the implied warranty of - * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - * Apache License for more details at - * http://www.apache.org/licenses/LICENSE-2.0 - */ -syntax = "proto3"; - -package domi; - -message ModelTaskDef { - string version = 1; - - map attr = 9; // Extended field - repeated TaskDef task = 10; - - uint64 memory_size = 11; - uint32 stream_num = 12; - uint32 event_num = 13; - uint64 weight_size = 14; - - repeated bytes op = 15; // input/output opdef in bytes - - uint64 base_addr = 16; // base addr - uint64 weight_addr = 17; // weight addr - uint32 batch_num = 18; -} - - -message TaskDef { - uint32 id = 1; - uint32 type = 2; - - uint32 stream_id = 10; - uint32 event_id = 11; - - KernelDef kernel = 20; - KernelExDef kernel_ex = 21; - KernelHcclDef kernel_hccl = 25; - EventExDef event_ex = 26; - LogTimeStampDef log_timestamp = 28; - - uint32 label_id = 30; - - MemcpyAsyncDef memcpy_async = 31; - StreamSwitchDef stream_switch = 32; - StreamActiveDef stream_active = 33; - bytes private_def = 34; - uint64 ops_kernel_store_ptr = 35; // adjustments to other fields in the future - StreamSwitchNDef stream_switch_n = 36; - - LabelSetDef label_set = 37; - LabelGotoExDef label_goto_ex = 38; - LabelSwitchByIndexDef label_switch_by_index = 39; - KernelDefWithHandle kernel_with_handle = 40; -} - -message KernelDef { - KernelContext context = 1; - - string stub_func = 10; - uint32 block_dim = 11; - uint32 args_size = 12; - bytes args = 13; - bytes sm_desc = 14; - bytes flowtable = 15; - string so_name = 16; - string kernel_name = 17; - bytes kernel_ext_info = 18; - uint32 kernel_ext_info_size = 19; -} - -message KernelDefWithHandle { - KernelContext context = 1; - - uint64 handle = 10; - string dev_func = 11; - uint32 block_dim = 12; - uint32 args_size = 13; - bytes args = 14; - bytes sm_desc = 15; - string original_kernel_key = 16; - string node_info = 17; -} - -message KernelContext { - uint32 kernel_type = 1; - uint32 op_id = 2; // OP type in CCE - uint32 kernel_func_id = 3; - uint32 op_index = 4; // TE/Custom operator - bool is_flowtable = 5; // Identify whether args is a flowtable structure - bytes args_offset = 6; // args offset information - uint32 args_count = 7; // args count - repeated uint32 origin_op_index = 8; -} - - -message KernelExDef { - uint32 flags = 1; - - uint32 op_index = 4; - uint32 args_size = 12; - bytes args = 13; - bytes task_info = 14; // serialized nodeDef, funcDef, inputoutput - uint32 task_info_size = 15; - bytes kernel_ext_info = 16; - uint32 kernel_ext_info_size = 17; -} - - -message KernelHcclDef { - uint32 op_index = 8; - string hccl_type = 9; -} - - -message EventExDef { - uint32 op_index = 1; - uint32 event_type = 2; -} - -message LogTimeStampDef { - uint64 logid = 1; - bool notify = 2; - uint32 flat = 3; -} - -message MemcpyAsyncDef { - uint64 dst = 1; - uint64 dst_max = 2; - uint64 src = 3; - uint64 count = 4; - uint32 kind = 5; - uint32 op_index = 6; -} - -message StreamSwitchDef { - uint32 op_index = 1; - uint32 true_stream_id = 2; - int64 value = 3; - uint64 value_ptr = 4; - uint32 data_type = 5; -} - -message StreamActiveDef { - uint32 op_index = 1; - uint32 active_stream_id = 2; -} - -message StreamSwitchNDef { - uint32 op_index = 1; - uint32 size = 2; - repeated int64 target_value = 3; - repeated uint32 true_stream_id = 4; - uint32 element_size = 5; - uint32 data_type = 6; -} - -message LabelSetDef { - uint32 op_index = 1; - uint32 label_id = 2; - uint32 model_id = 3; -} - -message LabelGotoExDef { - uint32 op_index = 1; - uint32 label_id = 2; - uint32 model_id = 3; -} - -message LabelSwitchByIndexDef { - uint32 op_index = 1; - uint32 label_max = 2; -} diff --git a/ge/proto/tensorflow/attr_value.proto b/ge/proto/tensorflow/attr_value.proto deleted file mode 100644 index 438d7163..00000000 --- a/ge/proto/tensorflow/attr_value.proto +++ /dev/null @@ -1,70 +0,0 @@ -/** - * This file is part of Open Source Software TensorFlow, version 1.15.0 https://github.com/tensorflow/tensorflow - * - * This file is included by GraphEngine so as to support model format conversion from tensorflow model to GraphEngine model. - * This file in this distribution may have been modified by Huawei Technologies Co., Ltd ("Huawei Modifications"). - * All Huawei Modifications are Copyright 2019-2020 Huawei Technologies Co., Ltd. - */ - -syntax = "proto3"; - -package domi.tensorflow; -option cc_enable_arenas = true; -option java_outer_classname = "AttrValueProtos"; -option java_multiple_files = true; -option java_package = "org.tensorflow.framework"; - -import "tensor.proto"; -import "tensor_shape.proto"; -import "types.proto"; - -// Protocol buffer representing the value for an attr used to configure an Op. -// Comment indicates the corresponding attr type. Only the field matching the -// attr type may be filled. -message AttrValue { - // LINT.IfChange - message ListValue { - repeated bytes s = 2; // "list(string)" - repeated int64 i = 3 [packed = true]; // "list(int)" - repeated float f = 4 [packed = true]; // "list(float)" - repeated bool b = 5 [packed = true]; // "list(bool)" - repeated DataType type = 6 [packed = true]; // "list(type)" - repeated TensorShapeProto shape = 7; // "list(shape)" - repeated TensorProto tensor = 8; // "list(tensor)" - repeated NameAttrList func = 9; // "list(attr)" - } - // LINT.ThenChange(https://www.tensorflow.org/code/tensorflow/c/c_api.cc) - - oneof value { - bytes s = 2; // "string" - int64 i = 3; // "int" - float f = 4; // "float" - bool b = 5; // "bool" - DataType type = 6; // "type" - TensorShapeProto shape = 7; // "shape" - TensorProto tensor = 8; // "tensor" - ListValue list = 1; // any "list(...)" - - // "func" represents a function. func.name is a function's name or - // a primitive op's name. func.attr.first is the name of an attr - // defined for that function. func.attr.second is the value for - // that attr in the instantiation. - NameAttrList func = 10; - - // This is a placeholder only used in nodes defined inside a - // function. It indicates the attr value will be supplied when - // the function is instantiated. For example, let us suppose a - // node "N" in function "FN". "N" has an attr "A" with value - // placeholder = "foo". When FN is instantiated with attr "foo" - // set to "bar", the instantiated node N's attr A will have been - // given the value "bar". - string placeholder = 9; - } -} - -// A list of attr names and their values. The whole list is attached -// with a string name. E.g., MatMul[T=float]. -message NameAttrList { - string name = 1; - map attr = 2; -} diff --git a/ge/proto/tensorflow/function.proto b/ge/proto/tensorflow/function.proto deleted file mode 100644 index 44681e32..00000000 --- a/ge/proto/tensorflow/function.proto +++ /dev/null @@ -1,108 +0,0 @@ -/** - * This file is part of Open Source Software TensorFlow, version 1.15.0 https://github.com/tensorflow/tensorflow - * - * This file is included by GraphEngine so as to support model format conversion from tensorflow model to GraphEngine model. - * This file in this distribution may have been modified by Huawei Technologies Co., Ltd ("Huawei Modifications"). - * All Huawei Modifications are Copyright 2019-2020 Huawei Technologies Co., Ltd. - */ - -syntax = "proto3"; - -package domi.tensorflow; -option cc_enable_arenas = true; -option java_outer_classname = "FunctionProtos"; -option java_multiple_files = true; -option java_package = "org.tensorflow.framework"; - -import "attr_value.proto"; -import "node_def.proto"; -import "op_def.proto"; - -// A library is a set of named functions. -message FunctionDefLibrary { - repeated FunctionDef function = 1; - repeated GradientDef gradient = 2; -} - -// A function can be instantiated when the runtime can bind every attr -// with a value. When a GraphDef has a call to a function, it must -// have binding for every attr defined in the signature. -// * device spec, etc. -message FunctionDef { - // The definition of the function's name, arguments, return values, - // attrs etc. - OpDef signature = 1; - - // Attributes specific to this function definition. - map attr = 5; - - // NOTE: field id 2 deleted on Jan 11, 2017, GraphDef version 21. - reserved 2; - - // In both of the following fields, there is the need to specify an - // output that is used as either the input to another node (in - // `node_def`) or as a return value of the function (in `ret`). - // Unlike the NodeDefs in GraphDef, we need to be able to specify a - // list in some cases (instead of just single outputs). Also, we - // need to be able to deal with lists of unknown length (so the - // output index may not be known at function definition time). So - // we use the following format instead: - // * "fun_in" where "fun_in" is the name of a function input arg in - // the `signature` field above. This represents that input, whether - // it is a single tensor or a list. - // * "fun_in:0" gives the first element of a function input arg (a - // non-list input is considered a list of length 1 for these - // purposes). - // * "node:out" where "node" is the name of a node in `node_def` and - // "out" is the name one of its op's output arguments (the name - // comes from the OpDef of the node's op). This represents that - // node's output, whether it is a single tensor or a list. - // Note: We enforce that an op's output arguments are never - // renamed in the backwards-compatibility test. - // * "node:out:0" gives the first element of a node output arg (a - // non-list output is considered a list of length 1 for these - // purposes). - // - // NOT CURRENTLY SUPPORTED (but may be in the future): - // * "node:out:-1" gives last element in a node output list - // * "node:out:1:" gives a list with all but the first element in a - // node output list - // * "node:out::-1" gives a list with all but the last element in a - // node output list - - // The body of the function. Unlike the NodeDefs in a GraphDef, attrs - // may have values of type `placeholder` and the `input` field uses - // the "output" format above. - - // By convention, "op" in node_def is resolved by consulting with a - // user-defined library first. If not resolved, "func" is assumed to - // be a builtin op. - repeated NodeDef node_def = 3; - - // A mapping from the output arg names from `signature` to the - // outputs from `node_def` that should be returned by the function. - map ret = 4; -} - -// GradientDef defines the gradient function of a function defined in -// a function library. -// -// A gradient function g (specified by gradient_func) for a function f -// (specified by function_name) must follow the following: -// -// The function 'f' must be a numerical function which takes N inputs -// and produces M outputs. Its gradient function 'g', which is a -// function taking N + M inputs and produces N outputs. -// -// I.e. if we have -// (y1, y2, ..., y_M) = f(x1, x2, ..., x_N), -// then, g is -// (dL/dx1, dL/dx2, ..., dL/dx_N) = g(x1, x2, ..., x_N, -// dL/dy1, dL/dy2, ..., dL/dy_M), -// where L is a scalar-value function of (x1, x2, ..., xN) (e.g., the -// loss function). dL/dx_i is the partial derivative of L with respect -// to x_i. -message GradientDef { - string function_name = 1; // The function name. - string gradient_func = 2; // The gradient function's name. -} diff --git a/ge/proto/tensorflow/graph.proto b/ge/proto/tensorflow/graph.proto deleted file mode 100644 index 73bfc6ee..00000000 --- a/ge/proto/tensorflow/graph.proto +++ /dev/null @@ -1,64 +0,0 @@ -/** - * This file is part of Open Source Software TensorFlow, version 1.15.0 https://github.com/tensorflow/tensorflow - * - * This file is included by GraphEngine so as to support model format conversion from tensorflow model to GraphEngine model. - * This file in this distribution may have been modified by Huawei Technologies Co., Ltd ("Huawei Modifications"). - * All Huawei Modifications are Copyright 2019-2020 Huawei Technologies Co., Ltd. - */ - -syntax = "proto3"; - -package domi.tensorflow; -option cc_enable_arenas = true; -option java_outer_classname = "GraphProtos"; -option java_multiple_files = true; -option java_package = "org.tensorflow.framework"; - -import "node_def.proto"; -import "function.proto"; -import "versions.proto"; - -// Represents the graph of operations -message GraphDef { - repeated NodeDef node = 1; - - // Compatibility versions of the graph. See core/public/version.h for version - // history. The GraphDef version is distinct from the TensorFlow version, and - // each release of TensorFlow will support a range of GraphDef versions. - VersionDef versions = 4; - - // Deprecated single version field; use versions above instead. Since all - // GraphDef changes before "versions" was introduced were forward - // compatible, this field is entirely ignored. - int32 version = 3 [deprecated = true]; - - // EXPERIMENTAL. DO NOT USE OR DEPEND ON THIS YET. - // - // "library" provides user-defined functions. - // - // Naming: - // * library.function.name are in a flat namespace. - // NOTE: We may need to change it to be hierarchical to support - // different orgs. E.g., - // { "/google/nn", { ... }}, - // { "/google/vision", { ... }} - // { "/org_foo/module_bar", { ... }} - // map named_lib; - // * If node[i].op is the name of one function in "library", - // node[i] is deemed as a function call. Otherwise, node[i].op - // must be a primitive operation supported by the runtime. - // - // - // Function call semantics: - // - // * The callee may start execution as soon as some of its inputs - // are ready. The caller may want to use Tuple() mechanism to - // ensure all inputs are ready in the same time. - // - // * The consumer of return values may start executing as soon as - // the return values the consumer depends on are ready. The - // consumer may want to use Tuple() mechanism to ensure the - // consumer does not start until all return values of the callee - // function are ready. - FunctionDefLibrary library = 2; -}; diff --git a/ge/proto/tensorflow/graph_library.proto b/ge/proto/tensorflow/graph_library.proto deleted file mode 100644 index 7bca0838..00000000 --- a/ge/proto/tensorflow/graph_library.proto +++ /dev/null @@ -1,22 +0,0 @@ -/** - * This file is part of Open Source Software TensorFlow, version 1.15.0 https://github.com/tensorflow/tensorflow - * - * This file is included by GraphEngine so as to support model format conversion from tensorflow model to GraphEngine model. - * This file in this distribution may have been modified by Huawei Technologies Co., Ltd ("Huawei Modifications"). - * All Huawei Modifications are Copyright 2019-2020 Huawei Technologies Co., Ltd. - */ - -syntax = "proto3"; - -package domi.tensorflow; - -import "graph.proto"; - -message GeGraphDef { - string name = 1; - GraphDef graph = 2; -} - -message GraphDefLibrary { - repeated GeGraphDef graph_def = 1; -}; \ No newline at end of file diff --git a/ge/proto/tensorflow/node_def.proto b/ge/proto/tensorflow/node_def.proto deleted file mode 100644 index 50cf5cac..00000000 --- a/ge/proto/tensorflow/node_def.proto +++ /dev/null @@ -1,71 +0,0 @@ -/** - * This file is part of Open Source Software TensorFlow, version 1.15.0 https://github.com/tensorflow/tensorflow - * - * This file is included by GraphEngine so as to support model format conversion from tensorflow model to GraphEngine model. - * This file in this distribution may have been modified by Huawei Technologies Co., Ltd ("Huawei Modifications"). - * All Huawei Modifications are Copyright 2019-2020 Huawei Technologies Co., Ltd. - */ - -syntax = "proto3"; - -package domi.tensorflow; -option cc_enable_arenas = true; -option java_outer_classname = "NodeProto"; -option java_multiple_files = true; -option java_package = "org.tensorflow.framework"; - -import "attr_value.proto"; - -message NodeDef { - // The name given to this operator. Used for naming inputs, - // logging, visualization, etc. Unique within a single GraphDef. - // Must match the regexp "[A-Za-z0-9.][A-Za-z0-9_./]*". - string name = 1; - - // The operation name. There may be custom parameters in attrs. - // Op names starting with an underscore are reserved for internal use. - string op = 2; - - // Each input is "node:src_output" with "node" being a string name and - // "src_output" indicating which output tensor to use from "node". If - // "src_output" is 0 the ":0" suffix can be omitted. Regular inputs - // may optionally be followed by control inputs that have the format - // "^node". - repeated string input = 3; - - // A (possibly partial) specification for the device on which this - // node should be placed. - // The expected syntax for this string is as follows: - // - // DEVICE_SPEC ::= PARTIAL_SPEC - // - // PARTIAL_SPEC ::= ("/" CONSTRAINT) * - // CONSTRAINT ::= ("job:" JOB_NAME) - // | ("replica:" [1-9][0-9]*) - // | ("task:" [1-9][0-9]*) - // | ("device:" [A-Za-z]* ":" ([1-9][0-9]* | "*") ) - // - // Valid values for this string include: - // * "/job:worker/replica:0/task:1/device:GPU:3" (full specification) - // * "/job:worker/device:GPU:3" (partial specification) - // * "" (no specification) - // - // If the constraints do not resolve to a single device (or if this - // field is empty or not present), the runtime will attempt to - // choose a device automatically. - string device = 4; - - // Operation-specific graph-construction-time configuration. - // Note that this should include all attrs defined in the - // corresponding OpDef, including those with a value matching - // the default -- this allows the default to change and makes - // NodeDefs easier to interpret on their own. However, if - // an attr with a default is not specified in this list, the - // default will be used. - // The "names" (keys) must match the regexp "[a-z][a-z0-9_]+" (and - // one of the names from the corresponding OpDef's attr field). - // The values must have a type matching the corresponding OpDef - // attr's type field. - // Add some examples here showing best practices. - map attr = 5; -}; diff --git a/ge/proto/tensorflow/op_def.proto b/ge/proto/tensorflow/op_def.proto deleted file mode 100644 index 7f0e8ce2..00000000 --- a/ge/proto/tensorflow/op_def.proto +++ /dev/null @@ -1,172 +0,0 @@ -/** - * This file is part of Open Source Software TensorFlow, version 1.15.0 https://github.com/tensorflow/tensorflow - * - * This file is included by GraphEngine so as to support model format conversion from tensorflow model to GraphEngine model. - * This file in this distribution may have been modified by Huawei Technologies Co., Ltd ("Huawei Modifications"). - * All Huawei Modifications are Copyright 2019-2020 Huawei Technologies Co., Ltd. - */ - -syntax = "proto3"; - -package domi.tensorflow; -option cc_enable_arenas = true; -option java_outer_classname = "OpDefProtos"; -option java_multiple_files = true; -option java_package = "org.tensorflow.framework"; - -import "attr_value.proto"; -import "types.proto"; - -// Defines an operation. A NodeDef in a GraphDef specifies an Op by -// using the "op" field which should match the name of a OpDef. -// LINT.IfChange -message OpDef { - // Op names starting with an underscore are reserved for internal use. - // Names should be CamelCase and match the regexp "[A-Z][a-zA-Z0-9_]*". - string name = 1; - - // For describing inputs and outputs. - message ArgDef { - // Name for the input/output. Should match the regexp "[a-z][a-z0-9_]*". - string name = 1; - - // Human readable description. - string description = 2; - - // Describes the type of one or more tensors that are accepted/produced - // by this input/output arg. The only legal combinations are: - // * For a single tensor: either the "type" field is set or the - // "type_attr" field is set to the name of an attr with type "type". - // * For a sequence of tensors with the same type: the "number_attr" - // field will be set to the name of an attr with type "int", and - // either the "type" or "type_attr" field will be set as for - // single tensors. - // * For a sequence of tensors, the "type_list_attr" field will be set - // to the name of an attr with type "list(type)". - DataType type = 3; - string type_attr = 4; // if specified, attr must have type "type" - string number_attr = 5; // if specified, attr must have type "int" - // If specified, attr must have type "list(type)", and none of - // type, type_attr, and number_attr may be specified. - string type_list_attr = 6; - - // For inputs: if true, the inputs are required to be refs. - // By default, inputs can be either refs or non-refs. - // For outputs: if true, outputs are refs, otherwise they are not. - bool is_ref = 16; - }; - - // Description of the input(s). - repeated ArgDef input_arg = 2; - - // Description of the output(s). - repeated ArgDef output_arg = 3; - - // Description of the graph-construction-time configuration of this - // Op. That is to say, this describes the attr fields that will - // be specified in the NodeDef. - message AttrDef { - // A descriptive name for the argument. May be used, e.g. by the - // Python client, as a keyword argument name, and so should match - // the regexp "[a-z][a-z0-9_]+". - string name = 1; - - // One of the type names from attr_value.proto ("string", "list(string)", - // "int", etc.). - string type = 2; - - // A reasonable default for this attribute if the user does not supply - // a value. If not specified, the user must supply a value. - AttrValue default_value = 3; - - // Human-readable description. - string description = 4; - - - // --- Constraints --- - // These constraints are only in effect if specified. Default is no - // constraints. - - // For type == "int", this is a minimum value. For "list(___)" - // types, this is the minimum length. - bool has_minimum = 5; - int64 minimum = 6; - - // The set of allowed values. Has type that is the "list" version - // of the "type" field above (uses the "list" field of AttrValue). - // If type == "type" or "list(type)" above, then the "type" field - // of "allowed_values.list" has the set of allowed DataTypes. - // If type == "string" or "list(string)", then the "s" field of - // "allowed_values.list" has the set of allowed strings. - AttrValue allowed_values = 7; - } - repeated AttrDef attr = 4; - - // Optional deprecation based on GraphDef versions. - OpDeprecation deprecation = 8; - - // One-line human-readable description of what the Op does. - string summary = 5; - - // Additional, longer human-readable description of what the Op does. - string description = 6; - - // ------------------------------------------------------------------------- - // Which optimizations this operation can participate in. - - // True if the operation is commutative ("op(a,b) == op(b,a)" for all inputs) - bool is_commutative = 18; - - // If is_aggregate is true, then this operation accepts N >= 2 - // inputs and produces 1 output all of the same type. Should be - // associative and commutative, and produce output with the same - // shape as the input. The optimizer may replace an aggregate op - // taking input from multiple devices with a tree of aggregate ops - // that aggregate locally within each device (and possibly within - // groups of nearby devices) before communicating. - bool is_aggregate = 16; // for things like add - - // Other optimizations go here, like - // can_alias_input, rewrite_when_output_unused, partitioning_strategy, etc. - - // ------------------------------------------------------------------------- - // Optimization constraints. - - // Ops are marked as stateful if their behavior depends on some state beyond - // their input tensors (e.g. variable reading op) or if they have - // a side-effect (e.g. printing or asserting ops). Equivalently, stateless ops - // must always produce the same output for the same input and have - // no side-effects. - // - // By default Ops may be moved between devices. Stateful ops should - // either not be moved, or should only be moved if that state can also - // be moved (e.g. via some sort of save / restore). - // Stateful ops are guaranteed to never be optimized away by Common - // Subexpression Elimination (CSE). - bool is_stateful = 17; // for things like variables, queue - - // ------------------------------------------------------------------------- - // Non-standard options. - - // By default, all inputs to an Op must be initialized Tensors. Ops - // that may initialize tensors for the first time should set this - // field to true, to allow the Op to take an uninitialized Tensor as - // input. - bool allows_uninitialized_input = 19; // for Assign, etc. -}; -// LINT.ThenChange( -// https://www.tensorflow.org/code/tensorflow/core/framework/op_def_util.cc) - -// Information about version-dependent deprecation of an op -message OpDeprecation { - // First GraphDef version at which the op is disallowed. - int32 version = 1; - - // Explanation of why it was deprecated and what to use instead. - string explanation = 2; -}; - -// A collection of OpDefs -message OpList { - repeated OpDef op = 1; -}; diff --git a/ge/proto/tensorflow/resource_handle.proto b/ge/proto/tensorflow/resource_handle.proto deleted file mode 100644 index 91c46c9a..00000000 --- a/ge/proto/tensorflow/resource_handle.proto +++ /dev/null @@ -1,37 +0,0 @@ -/** - * This file is part of Open Source Software TensorFlow, version 1.15.0 https://github.com/tensorflow/tensorflow - * - * This file is included by GraphEngine so as to support model format conversion from tensorflow model to GraphEngine model. - * This file in this distribution may have been modified by Huawei Technologies Co., Ltd ("Huawei Modifications"). - * All Huawei Modifications are Copyright 2019-2020 Huawei Technologies Co., Ltd. - */ - -syntax = "proto3"; - -package domi.tensorflow; -option cc_enable_arenas = true; -option java_outer_classname = "ResourceHandle"; -option java_multiple_files = true; -option java_package = "org.tensorflow.framework"; - -// Protocol buffer representing a handle to a tensorflow resource. Handles are -// not valid across executions, but can be serialized back and forth from within -// a single run. -message ResourceHandleProto { - // Unique name for the device containing the resource. - string device = 1; - - // Container in which this resource is placed. - string container = 2; - - // Unique name of this resource. - string name = 3; - - // Hash code for the type of the resource. Is only valid in the same device - // and in the same execution. - uint64 hash_code = 4; - - // For debug-only, the name of the type pointed to by this handle, if - // available. - string maybe_type_name = 5; -}; diff --git a/ge/proto/tensorflow/tensor.proto b/ge/proto/tensorflow/tensor.proto deleted file mode 100644 index 48eeb6c4..00000000 --- a/ge/proto/tensorflow/tensor.proto +++ /dev/null @@ -1,102 +0,0 @@ -/** - * This file is part of Open Source Software TensorFlow, version 1.15.0 https://github.com/tensorflow/tensorflow - * - * This file is included by GraphEngine so as to support model format conversion from tensorflow model to GraphEngine model. - * This file in this distribution may have been modified by Huawei Technologies Co., Ltd ("Huawei Modifications"). - * All Huawei Modifications are Copyright 2019-2020 Huawei Technologies Co., Ltd. - */ - -syntax = "proto3"; - -package domi.tensorflow; -option cc_enable_arenas = true; -option java_outer_classname = "TensorProtos"; -option java_multiple_files = true; -option java_package = "org.tensorflow.framework"; - -import "resource_handle.proto"; -import "tensor_shape.proto"; -import "types.proto"; - -// Protocol buffer representing a tensor. -message TensorProto { - DataType dtype = 1; - - // Shape of the tensor. - TensorShapeProto tensor_shape = 2; - - // Only one of the representations below is set, one of "tensor_contents" and - // the "xxx_val" attributes. We are not using oneof because as oneofs cannot - // contain repeated fields it would require another extra set of messages. - - // Version number. - // - // In version 0, if the "repeated xxx" representations contain only one - // element, that element is repeated to fill the shape. This makes it easy - // to represent a constant Tensor with a single value. - int32 version_number = 3; - - // Serialized raw tensor content from either Tensor::AsProtoTensorContent or - // memcpy in tensorflow::grpc::EncodeTensorToByteBuffer. This representation - // can be used for all tensor types. The purpose of this representation is to - // reduce serialization overhead during RPC call by avoiding serialization of - // many repeated small items. - bytes tensor_content = 4; - - // Type specific representations that make it easy to create tensor protos in - // all languages. Only the representation corresponding to "dtype" can - // be set. The values hold the flattened representation of the tensor in - // row major order. - - // DT_HALF, DT_BFLOAT16. Note that since protobuf has no int16 type, we'll - // have some pointless zero padding for each value here. - repeated int32 half_val = 13 [packed = true]; - - // DT_FLOAT. - repeated float float_val = 5 [packed = true]; - - // DT_DOUBLE. - repeated double double_val = 6 [packed = true]; - - // DT_INT32, DT_INT16, DT_INT8, DT_UINT8. - repeated int32 int_val = 7 [packed = true]; - - // DT_STRING - repeated bytes string_val = 8; - - // DT_COMPLEX64. scomplex_val(2*i) and scomplex_val(2*i+1) are real - // and imaginary parts of i-th single precision complex. - repeated float scomplex_val = 9 [packed = true]; - - // DT_INT64 - repeated int64 int64_val = 10 [packed = true]; - - // DT_BOOL - repeated bool bool_val = 11 [packed = true]; - - // DT_COMPLEX128. dcomplex_val(2*i) and dcomplex_val(2*i+1) are real - // and imaginary parts of i-th double precision complex. - repeated double dcomplex_val = 12 [packed = true]; - - // DT_RESOURCE - repeated ResourceHandleProto resource_handle_val = 14; - - // DT_VARIANT - repeated VariantTensorDataProto variant_val = 15; - - // DT_UINT32 - repeated uint32 uint32_val = 16 [packed = true]; - - // DT_UINT64 - repeated uint64 uint64_val = 17 [packed = true]; -}; - -// Protocol buffer representing the serialization format of DT_VARIANT tensors. -message VariantTensorDataProto { - // Name of the type of objects being serialized. - string type_name = 1; - // Portions of the object that are not Tensors. - bytes metadata = 2; - // Tensors contained within objects being serialized. - repeated TensorProto tensors = 3; -} diff --git a/ge/proto/tensorflow/tensor_shape.proto b/ge/proto/tensorflow/tensor_shape.proto deleted file mode 100644 index 3a6d8c5a..00000000 --- a/ge/proto/tensorflow/tensor_shape.proto +++ /dev/null @@ -1,53 +0,0 @@ -/** - * This file is part of Open Source Software TensorFlow, version 1.15.0 https://github.com/tensorflow/tensorflow - * - * This file is included by GraphEngine so as to support model format conversion from tensorflow model to GraphEngine model. - * This file in this distribution may have been modified by Huawei Technologies Co., Ltd ("Huawei Modifications"). - * All Huawei Modifications are Copyright 2019-2020 Huawei Technologies Co., Ltd. - */ - -// Protocol buffer representing the shape of tensors. - -syntax = "proto3"; -option cc_enable_arenas = true; -option java_outer_classname = "TensorShapeProtos"; -option java_multiple_files = true; -option java_package = "org.tensorflow.framework"; - -package domi.tensorflow; - -// Dimensions of a tensor. -message TensorShapeProto { - // One dimension of the tensor. - message Dim { - // Size of the tensor in that dimension. - // This value must be >= -1, but values of -1 are reserved for "unknown" - // shapes (values of -1 mean "unknown" dimension). Certain wrappers - // that work with TensorShapeProto may fail at runtime when deserializing - // a TensorShapeProto containing a dim value of -1. - int64 size = 1; - - // Optional name of the tensor dimension. - string name = 2; - }; - - // Dimensions of the tensor, such as {"input", 30}, {"output", 40} - // for a 30 x 40 2D tensor. If an entry has size -1, this - // corresponds to a dimension of unknown size. The names are - // optional. - // - // The order of entries in "dim" matters: It indicates the layout of the - // values in the tensor in-memory representation. - // - // The first entry in "dim" is the outermost dimension used to layout the - // values, the last entry is the innermost dimension. This matches the - // in-memory layout of RowMajor Eigen tensors. - // - // If "dim.size()" > 0, "unknown_rank" must be false. - repeated Dim dim = 2; - - // If true, the number of dimensions in the shape is unknown. - // - // If true, "dim.size()" must be 0. - bool unknown_rank = 3; -}; diff --git a/ge/proto/tensorflow/types.proto b/ge/proto/tensorflow/types.proto deleted file mode 100644 index f40e49cb..00000000 --- a/ge/proto/tensorflow/types.proto +++ /dev/null @@ -1,82 +0,0 @@ -/** - * This file is part of Open Source Software TensorFlow, version 1.15.0 https://github.com/tensorflow/tensorflow - * - * This file is included by GraphEngine so as to support model format conversion from tensorflow model to GraphEngine model. - * This file in this distribution may have been modified by Huawei Technologies Co., Ltd ("Huawei Modifications"). - * All Huawei Modifications are Copyright 2019-2020 Huawei Technologies Co., Ltd. - */ - -syntax = "proto3"; - -package domi.tensorflow; -option cc_enable_arenas = true; -option java_outer_classname = "TypesProtos"; -option java_multiple_files = true; -option java_package = "org.tensorflow.framework"; - -// LINT.IfChange -enum DataType { - // Not a legal value for DataType. Used to indicate a DataType field - // has not been set. - DT_INVALID = 0; - - // Data types that all computation devices are expected to be - // capable to support. - DT_FLOAT = 1; - DT_DOUBLE = 2; - DT_INT32 = 3; - DT_UINT8 = 4; - DT_INT16 = 5; - DT_INT8 = 6; - DT_STRING = 7; - DT_COMPLEX64 = 8; // Single-precision complex - DT_INT64 = 9; - DT_BOOL = 10; - DT_QINT8 = 11; // Quantized int8 - DT_QUINT8 = 12; // Quantized uint8 - DT_QINT32 = 13; // Quantized int32 - DT_BFLOAT16 = 14; // Float32 truncated to 16 bits. Only for cast ops. - DT_QINT16 = 15; // Quantized int16 - DT_QUINT16 = 16; // Quantized uint16 - DT_UINT16 = 17; - DT_COMPLEX128 = 18; // Double-precision complex - DT_HALF = 19; - DT_RESOURCE = 20; - DT_VARIANT = 21; // Arbitrary C++ data types - DT_UINT32 = 22; - DT_UINT64 = 23; - - // Do not use! These are only for parameters. Every enum above - // should have a corresponding value below (verified by types_test). - DT_FLOAT_REF = 101; - DT_DOUBLE_REF = 102; - DT_INT32_REF = 103; - DT_UINT8_REF = 104; - DT_INT16_REF = 105; - DT_INT8_REF = 106; - DT_STRING_REF = 107; - DT_COMPLEX64_REF = 108; - DT_INT64_REF = 109; - DT_BOOL_REF = 110; - DT_QINT8_REF = 111; - DT_QUINT8_REF = 112; - DT_QINT32_REF = 113; - DT_BFLOAT16_REF = 114; - DT_QINT16_REF = 115; - DT_QUINT16_REF = 116; - DT_UINT16_REF = 117; - DT_COMPLEX128_REF = 118; - DT_HALF_REF = 119; - DT_RESOURCE_REF = 120; - DT_VARIANT_REF = 121; - DT_UINT32_REF = 122; - DT_UINT64_REF = 123; -} -// LINT.ThenChange( -// https://www.tensorflow.org/code/tensorflow/c/c_api.h, -// https://www.tensorflow.org/code/tensorflow/go/tensor.go, -// https://www.tensorflow.org/code/tensorflow/core/framework/tensor.cc, -// https://www.tensorflow.org/code/tensorflow/core/framework/types.h, -// https://www.tensorflow.org/code/tensorflow/core/framework/types.cc, -// https://www.tensorflow.org/code/tensorflow/python/framework/dtypes.py, -// https://www.tensorflow.org/code/tensorflow/python/framework/function.py) diff --git a/ge/proto/tensorflow/versions.proto b/ge/proto/tensorflow/versions.proto deleted file mode 100644 index 4e81548f..00000000 --- a/ge/proto/tensorflow/versions.proto +++ /dev/null @@ -1,39 +0,0 @@ -/** - * This file is part of Open Source Software TensorFlow, version 1.15.0 https://github.com/tensorflow/tensorflow - * - * This file is included by GraphEngine so as to support model format conversion from tensorflow model to GraphEngine model. - * This file in this distribution may have been modified by Huawei Technologies Co., Ltd ("Huawei Modifications"). - * All Huawei Modifications are Copyright 2019-2020 Huawei Technologies Co., Ltd. - */ - -syntax = "proto3"; - -package domi.tensorflow; -option cc_enable_arenas = true; -option java_outer_classname = "VersionsProtos"; -option java_multiple_files = true; -option java_package = "org.tensorflow.framework"; - -// Version information for a piece of serialized data -// -// There are different types of versions for each type of data -// (GraphDef, etc.), but they all have the same common shape -// described here. -// -// Each consumer has "consumer" and "min_producer" versions (specified -// elsewhere). A consumer is allowed to consume this data if -// -// producer >= min_producer -// consumer >= min_consumer -// consumer not in bad_consumers -// -message VersionDef { - // The version of the code that produced this data. - int32 producer = 1; - - // Any consumer below this version is not allowed to consume this data. - int32 min_consumer = 2; - - // Specific consumer versions which are disallowed (e.g. due to bugs). - repeated int32 bad_consumers = 3; -};