@@ -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; | |||||
}; |