@@ -1 +0,0 @@ | |||
../../proto/ge_api.proto |
@@ -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<string, AttrDef> 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<string, AttrDef> 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:index | |||
map<string, AttrDef> 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<string, AttrDef> 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,graph[0] represents the main diagram in modeldef | |||
map<string, AttrDef> attr = 11; // Extended field | |||
} | |||
@@ -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 | |||
} |
@@ -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<string, AttrDef> 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<string, AttrDef> 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<string, AttrDef> attr = 2; | |||
} | |||
@@ -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<string, string> 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; | |||
} |
@@ -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<string, AttrDef> 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<string, AttrDef> 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:index | |||
map<string, AttrDef> 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<string, AttrDef> 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,graph[0] represents the main diagram in modeldef | |||
map<string, AttrDef> attr = 11; // Extended field | |||
} | |||
@@ -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 | |||
} |
@@ -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<string, AttrDef> 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<string, AttrDef> 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<string, AttrDef> attr = 2; | |||
} | |||
@@ -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; | |||
} |
@@ -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<string, string> 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; | |||
} |
@@ -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<string, AttrValue> attr = 2; | |||
} |
@@ -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<string, AttrValue> 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<string, string> 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. | |||
} |
@@ -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<string, FunctionDefLib> 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; | |||
}; |
@@ -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; | |||
}; |
@@ -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<string, AttrValue> attr = 5; | |||
}; |
@@ -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; | |||
}; |
@@ -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; | |||
}; |
@@ -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; | |||
} |
@@ -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; | |||
}; |
@@ -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) |
@@ -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; | |||
}; |
@@ -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; | |||
} |
@@ -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<string, AttrDef> 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<string, AttrDef> 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:index | |||
map<string, AttrDef> 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<string, AttrDef> 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,graph[0] represents the main diagram in modeldef | |||
map<string, AttrDef> attr = 11; // Extended field | |||
} | |||
@@ -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 | |||
} |
@@ -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<string, AttrDef> 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<string, AttrDef> 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<string, AttrDef> attr = 2; | |||
} | |||
@@ -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; | |||
} |
@@ -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<string, string> 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; | |||
} |
@@ -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<string, string> 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; | |||
} |
@@ -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<string, AttrDef> 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<string, AttrDef> 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:index | |||
map<string, AttrDef> 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<string, AttrDef> 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,graph[0] represents the main diagram in modeldef | |||
map<string, AttrDef> attr = 11; // Extended field | |||
} | |||
@@ -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 | |||
} |
@@ -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<string, AttrDef> 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<string, AttrDef> 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<string, AttrDef> attr = 2; | |||
} | |||
@@ -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<string, string> 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; | |||
} |
@@ -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; | |||
} |
@@ -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; | |||
} |
@@ -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; | |||
} | |||
@@ -1,88 +0,0 @@ | |||
syntax = "proto3"; | |||
package ge.api_pb; | |||
import "ge_ir.proto"; | |||
// GE initialize | |||
message GEInitialize { | |||
map<string, string> 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<string, string> 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; | |||
}; |
@@ -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<string, AttrDef> 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<string, AttrDef> 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:index | |||
map<string, AttrDef> 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<string, AttrDef> 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,graph[0] represents the main diagram in modeldef | |||
map<string, AttrDef> attr = 11; // Extended field | |||
} | |||
@@ -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 | |||
} |
@@ -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<string, AttrDef> 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<string, AttrDef> 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<string, AttrDef> attr = 2; | |||
} | |||
@@ -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; | |||
} |
@@ -1,7 +0,0 @@ | |||
syntax = "proto3"; | |||
package ge.optimizers; | |||
// Default: GE>FE>AICPU | |||
message Priority{ | |||
repeated string optimizer = 1; | |||
} |
@@ -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<string, string> 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; | |||
} |
@@ -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<string, AttrValue> attr = 2; | |||
} |
@@ -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<string, AttrValue> 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<string, string> 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. | |||
} |
@@ -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<string, FunctionDefLib> 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; | |||
}; |
@@ -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; | |||
}; |
@@ -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<string, AttrValue> attr = 5; | |||
}; |
@@ -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; | |||
}; |
@@ -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; | |||
}; |
@@ -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; | |||
} |
@@ -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; | |||
}; |
@@ -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) |
@@ -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; | |||
}; |