diff --git a/csharp/test/Microsoft.ML.OnnxRuntime.Tests/Microsoft.ML.OnnxRuntime.Tests.csproj b/csharp/test/Microsoft.ML.OnnxRuntime.Tests/Microsoft.ML.OnnxRuntime.Tests.csproj index b4fb8de55d..2673fb3920 100644 --- a/csharp/test/Microsoft.ML.OnnxRuntime.Tests/Microsoft.ML.OnnxRuntime.Tests.csproj +++ b/csharp/test/Microsoft.ML.OnnxRuntime.Tests/Microsoft.ML.OnnxRuntime.Tests.csproj @@ -8,7 +8,7 @@ bin\$(Configuration)\ $(OnnxRuntimeCsharpRoot)\..\build\Windows $(OnnxRuntimeBuildDirectory)\$(Configuration)\external\protobuf\cmake\$(Configuration) - $(OnnxRuntimeCsharpRoot)\..\cmake\external\onnx\onnx + $(OnnxRuntimeCsharpRoot)\..\onnxruntime\core\protobuf $(OnnxRuntimeBuildDirectory)\$(Configuration)\$(Configuration) diff --git a/onnxruntime/core/protobuf/onnx-ml.proto b/onnxruntime/core/protobuf/onnx-ml.proto index 6cd542c61a..d56f19f4db 100644 --- a/onnxruntime/core/protobuf/onnx-ml.proto +++ b/onnxruntime/core/protobuf/onnx-ml.proto @@ -2,6 +2,7 @@ // WARNING: This file is automatically generated! Please edit onnx.in.proto. // + // Copyright (c) Facebook Inc. and Microsoft Corporation. // Licensed under the MIT license. @@ -19,11 +20,11 @@ package onnx; // // This document describes the syntax of models and their computation graphs, // as well as the standard data types. Together, they are referred to as the ONNX -// Intermediate Representation, or 'IR' for short. +// Intermediate Representation, or 'IR' for short. // // The normative semantic specification of the ONNX IR is found in docs/IR.md. // Definitions of the built-in neural network operators may be found in docs/Operators.md. -// Definitions of the built-in classical machine learning operators may be found in +// Definitions of the built-in classical machine learning operators may be found in // docs/Operators-ml.md. // Notes @@ -36,8 +37,8 @@ package onnx; // by sharing our working version of ONNX. // // Protobuf compatibility -// -// To simplify framework compatibility, ONNX is defined using the subset of protobuf +// +// To simplify framework compatibility, ONNX is defined using the subset of protobuf // that is compatible with both protobuf v2 and v3. This means that we do not use any // protobuf features that are only available in one of the two versions. // @@ -48,6 +49,7 @@ package onnx; // of key-value pairs, where order does not matter and duplicates // are not allowed. + // Versioning // // ONNX versioning is specified in docs/IR.md and elaborated on in docs/Versioning.md @@ -60,8 +62,8 @@ enum Version { _START_VERSION = 0; // The version field is always serialized and we will use it to store the // version that the graph is generated from. This helps us set up version - // control. - // For the IR, we are using simple numbers starting with with 0x00000001, + // control. + // For the IR, we are using simple numbers starting with with 0x00000001, // which was the version we published on Oct 10, 2017. IR_VERSION_2017_10_10 = 0x0000000000000001; @@ -74,7 +76,12 @@ enum Version { // - Added new message OperatorSetIdProto // - Added opset_import in ModelProto // - For vendor extensions, added domain in NodeProto - IR_VERSION = 0x0000000000000003; + IR_VERSION_2017_11_3 = 0x0000000000000003; + + // IR VERSION 4 published on Jan 22, 2019 + // - Relax constraint that initializers should be a subset of graph inputs + // - Add type BFLOAT16 + IR_VERSION = 0x0000000000000004; } // Attributes @@ -84,6 +91,7 @@ enum Version { // An AttributeProto MUST contain the name field, and *only one* of the // following content fields, effectively enforcing a C/C++ union equivalent. message AttributeProto { + // Note: this enum is structurally identical to the OpSchema::AttrType // enum defined in schema.h. If you rev one, you likely need to rev the other. enum AttributeType { @@ -102,8 +110,8 @@ message AttributeProto { } // The name field MUST be present for this version of the IR. - optional string name = 1; // namespace Attribute - + optional string name = 1; // namespace Attribute + // if ref_attr_name is not empty, ref_attr_name is the attribute name in parent function. // In this case, this AttributeProto does not contain data, and it's a reference of attribute // in parent scope. @@ -119,14 +127,14 @@ message AttributeProto { // which value field was in use. For IR_VERSION 0.0.2 or later, this // field MUST be set and match the f|i|s|t|... field in use. This // change was made to accomodate proto3 implementations. - optional AttributeType type = 20; // discriminator that indicates which field below is in use + optional AttributeType type = 20; // discriminator that indicates which field below is in use // Exactly ONE of the following fields must be present for this version of the IR - optional float f = 2; // float - optional int64 i = 3; // int - optional bytes s = 4; // UTF-8 string - optional TensorProto t = 5; // tensor value - optional GraphProto g = 6; // graph + optional float f = 2; // float + optional int64 i = 3; // int + optional bytes s = 4; // UTF-8 string + optional TensorProto t = 5; // tensor value + optional GraphProto g = 6; // graph // Do not use field below, it's deprecated. // optional ValueProto v = 12; // value - subsumes everything but graph @@ -141,7 +149,7 @@ message AttributeProto { // the shape of the value. message ValueInfoProto { // This field MUST be present in this version of the IR. - optional string name = 1; // namespace Value + optional string name = 1; // namespace Value // This field MUST be present in this version of the IR. optional TypeProto type = 2; // A human-readable documentation for this value. Markdown is allowed. @@ -153,20 +161,20 @@ message ValueInfoProto { // Computation graphs are made up of a DAG of nodes, which represent what is // commonly called a "layer" or "pipeline stage" in machine learning frameworks. // -// For example, it can be a node of type "Conv" that takes in an image, a filter +// For example, it can be a node of type "Conv" that takes in an image, a filter // tensor and a bias tensor, and produces the convolved output. message NodeProto { - repeated string input = 1; // namespace Value - repeated string output = 2; // namespace Value + repeated string input = 1; // namespace Value + repeated string output = 2; // namespace Value // An optional identifier for this node in a graph. // This field MAY be absent in ths version of the IR. - optional string name = 3; // namespace Node + optional string name = 3; // namespace Node // The symbolic identifier of the Operator to execute. optional string op_type = 4; // namespace Operator // The domain of the OperatorSet that specifies the operator named by op_type. - optional string domain = 7; // namespace Domain + optional string domain = 7; // namespace Domain // Additional named attributes. repeated AttributeProto attribute = 5; @@ -233,7 +241,7 @@ message ModelProto { // See https://developers.google.com/protocol-buffers/docs/proto3#maps message StringStringEntryProto { optional string key = 1; - optional string value = 2; + optional string value= 2; }; message QuantInfo { @@ -246,7 +254,7 @@ message QuantInfo { // Graphs // -// A graph defines the computational logic of a model and is comprised of a parameterized +// A graph defines the computational logic of a model and is comprised of a parameterized // list of nodes that form a directed acyclic graph based on their inputs and outputs. // This is the equivalent of the "network" or "graph" in many deep learning // frameworks. @@ -255,11 +263,11 @@ message GraphProto { repeated NodeProto node = 1; // The name of the graph. - optional string name = 2; // namespace Graph + optional string name = 2; // namespace Graph // A list of named tensor values, used to specify constant inputs of the graph. // Each TensorProto entry must have a distinct name (within the list) that - // also appears in the input list. + // MAY also appear in the input list. repeated TensorProto initializer = 5; // A human-readable documentation for this graph. Markdown is allowed. @@ -312,8 +320,8 @@ message TensorProto { DOUBLE = 11; UINT32 = 12; UINT64 = 13; - COMPLEX64 = 14; // complex with float32 real and imaginary components - COMPLEX128 = 15; // complex with float64 real and imaginary components + COMPLEX64 = 14; // complex with float32 real and imaginary components + COMPLEX128 = 15; // complex with float64 real and imaginary components // Non-IEEE floating-point format based on IEEE754 single-precision // floating-point number truncated to 16 bits. @@ -327,6 +335,7 @@ message TensorProto { repeated int64 dims = 1; // The data type of the tensor. + // This field MUST have a valid TensorProto.DataType value optional int32 data_type = 2; // For very large tensors, we may want to store them in chunks, in which @@ -371,7 +380,7 @@ message TensorProto { repeated int64 int64_data = 7 [packed = true]; // Optionally, a name for the tensor. - optional string name = 8; // namespace Value + optional string name = 8; // namespace Value // A human-readable documentation for this tensor. Markdown is allowed. optional string doc_string = 12; @@ -396,13 +405,12 @@ message TensorProto { // Data can be stored inside the protobuf file using type-specific fields or raw_data. // Alternatively, raw bytes data can be stored in an external file, using the external_data field. // external_data stores key-value pairs describing data location. Recognized keys are: - // - "location" (required) - file path relative to the filesystem directory where the ONNX + // - "location" (required) - POSIX filesystem path relative to the directory where the ONNX // protobuf model was stored // - "offset" (optional) - position of byte at which stored data begins. Integer stored as string. // Offset values SHOULD be multiples 4096 (page size) to enable mmap support. // - "length" (optional) - number of bytes containing data. Integer stored as string. // - "checksum" (optional) - SHA1 digest of file specified in under 'location' key. - repeated StringStringEntryProto external_data = 13; // Location of the data for this tensor. MUST be one of: @@ -438,7 +446,7 @@ message TensorShapeProto { message Dimension { oneof value { int64 dim_value = 1; - string dim_param = 2; // namespace Shape + string dim_param = 2; // namespace Shape }; // Standard denotation can optionally be used to denote tensor // dimensions with standard semantic descriptions to ensure @@ -454,13 +462,16 @@ message TensorShapeProto { // // The standard ONNX data types. message TypeProto { + message Tensor { // This field MUST NOT have the value of UNDEFINED + // This field MUST have a valid TensorProto.DataType value // This field MUST be present for this version of the IR. optional int32 elem_type = 1; optional TensorShapeProto shape = 2; } + // repeated T message Sequence { // The type and optional shape of each element of the sequence. @@ -470,6 +481,7 @@ message TypeProto { // map message Map { + // This field MUST have a valid TensorProto.DataType value // This field MUST be present for this version of the IR. // This field MUST refer to an integral type ([U]INT{8|16|32|64}) or STRING optional int32 key_type = 1; @@ -487,17 +499,20 @@ message TypeProto { // repeated TypeProto parameters = 3; } - message SparseTensor { - // This field MUST NOT have the value of UNDEFINED - // This field MUST be present for this version of the IR. + message SparseTensor { + // This field MUST NOT have the value of UNDEFINED + // This field MUST have a valid TensorProto.DataType value + // This field MUST be present for this version of the IR. optional int32 elem_type = 1; optional TensorShapeProto shape = 2; } + oneof value { // The type of a tensor. Tensor tensor_type = 1; + // NOTE: DNN-only implementations of ONNX MAY elect to not support non-tensor values // as input and output to graphs and nodes. These types are needed to naturally // support classical ML operators. DNN operators SHOULD restrict their input @@ -512,10 +527,11 @@ message TypeProto { Opaque opaque_type = 7; SparseTensor sparse_tensor_type = 8; + } - // An optional denotation can be used to denote the whole - // type with a standard semantic description as to what is + // An optional denotation can be used to denote the whole + // type with a standard semantic description as to what is // stored inside. Refer to https://github.com/onnx/onnx/blob/master/docs/TypeDenotation.md#type-denotation-definition // for pre-defined type denotations. optional string denotation = 6; @@ -536,22 +552,20 @@ message OperatorSetIdProto { optional int64 version = 2; } -// Following messages are copied from onnx-operators-ml.proto in ONNX. -// // Operator/function status. enum OperatorStatus { - EXPERIMENTAL = 0; - STABLE = 1; + EXPERIMENTAL = 0; + STABLE = 1; } message FunctionProto { // The name of the function, similar usage of op_type in OperatorProto. optional string name = 1; - + // The first version of a function set which contains this function. // When there's any breaking change for this function, the function set // contains the function needs to bump its version, and since_version of - // the updated function will be changed to the updated function set version. + // the updated function will be changed to the updated function set version. optional int64 since_version = 2; // This field indicates whether the syntax, semantics, or presence @@ -569,10 +583,10 @@ message FunctionProto { repeated string output = 5; // The attributes of the function. - repeated string attribute = 6; - + repeated string attribute= 6; + // The nodes in the function. repeated NodeProto node = 7; // A human-readable documentation for this function. Markdown is allowed. optional string doc_string = 8; -} +} \ No newline at end of file diff --git a/onnxruntime/core/protobuf/onnx-ml.proto3 b/onnxruntime/core/protobuf/onnx-ml.proto3 new file mode 100644 index 0000000000..d9e3726911 --- /dev/null +++ b/onnxruntime/core/protobuf/onnx-ml.proto3 @@ -0,0 +1,592 @@ +// +// WARNING: This file is automatically generated! Please edit onnx.in.proto. +// + + +// Copyright (c) Facebook Inc. and Microsoft Corporation. +// Licensed under the MIT license. + +syntax = "proto3"; + +package onnx; + +// Overview +// +// ONNX is an open specification that is comprised of the following components: +// +// 1) A definition of an extensible computation graph model. +// 2) Definitions of standard data types. +// 3) Definitions of built-in operators. +// +// This document describes the syntax of models and their computation graphs, +// as well as the standard data types. Together, they are referred to as the ONNX +// Intermediate Representation, or 'IR' for short. +// +// The normative semantic specification of the ONNX IR is found in docs/IR.md. +// Definitions of the built-in neural network operators may be found in docs/Operators.md. +// Definitions of the built-in classical machine learning operators may be found in +// docs/Operators-ml.md. + +// Notes +// +// Release +// +// We are still in the very early stage of defining ONNX. The current +// version of ONNX is a starting point. While we are actively working +// towards a complete spec, we would like to get the community involved +// by sharing our working version of ONNX. +// +// Protobuf compatibility +// +// To simplify framework compatibility, ONNX is defined using the subset of protobuf +// that is compatible with both protobuf v2 and v3. This means that we do not use any +// protobuf features that are only available in one of the two versions. +// +// Here are the most notable contortions we have to carry out to work around +// these limitations: +// +// - No 'map' (added protobuf 3.0). We instead represent mappings as lists +// of key-value pairs, where order does not matter and duplicates +// are not allowed. + + +// Versioning +// +// ONNX versioning is specified in docs/IR.md and elaborated on in docs/Versioning.md +// +// To be compatible with both proto2 and proto3, we will use a version number +// that is not defined by the default value but an explicit enum number. +enum Version { + // proto3 requires the first enum value to be zero. + // We add this just to appease the compiler. + _START_VERSION = 0; + // The version field is always serialized and we will use it to store the + // version that the graph is generated from. This helps us set up version + // control. + // For the IR, we are using simple numbers starting with with 0x00000001, + // which was the version we published on Oct 10, 2017. + IR_VERSION_2017_10_10 = 0x0000000000000001; + + // IR_VERSION 2 published on Oct 30, 2017 + // - Added type discriminator to AttributeProto to support proto3 users + IR_VERSION_2017_10_30 = 0x0000000000000002; + + // IR VERSION 3 published on Nov 3, 2017 + // - For operator versioning: + // - Added new message OperatorSetIdProto + // - Added opset_import in ModelProto + // - For vendor extensions, added domain in NodeProto + IR_VERSION_2017_11_3 = 0x0000000000000003; + + // IR VERSION 4 published on Jan 22, 2019 + // - Relax constraint that initializers should be a subset of graph inputs + // - Add type BFLOAT16 + IR_VERSION = 0x0000000000000004; +} + +// Attributes +// +// A named attribute containing either singular float, integer, string, graph, +// and tensor values, or repeated float, integer, string, graph, and tensor values. +// An AttributeProto MUST contain the name field, and *only one* of the +// following content fields, effectively enforcing a C/C++ union equivalent. +message AttributeProto { + + // Note: this enum is structurally identical to the OpSchema::AttrType + // enum defined in schema.h. If you rev one, you likely need to rev the other. + enum AttributeType { + UNDEFINED = 0; + FLOAT = 1; + INT = 2; + STRING = 3; + TENSOR = 4; + GRAPH = 5; + + FLOATS = 6; + INTS = 7; + STRINGS = 8; + TENSORS = 9; + GRAPHS = 10; + } + + // The name field MUST be present for this version of the IR. + string name = 1; // namespace Attribute + + // if ref_attr_name is not empty, ref_attr_name is the attribute name in parent function. + // In this case, this AttributeProto does not contain data, and it's a reference of attribute + // in parent scope. + // NOTE: This should ONLY be used in function (sub-graph). It's invalid to be used in main graph. + string ref_attr_name = 21; + + // A human-readable documentation for this attribute. Markdown is allowed. + string doc_string = 13; + + // The type field MUST be present for this version of the IR. + // For 0.0.1 versions of the IR, this field was not defined, and + // implementations needed to use has_field hueristics to determine + // which value field was in use. For IR_VERSION 0.0.2 or later, this + // field MUST be set and match the f|i|s|t|... field in use. This + // change was made to accomodate proto3 implementations. + AttributeType type = 20; // discriminator that indicates which field below is in use + + // Exactly ONE of the following fields must be present for this version of the IR + float f = 2; // float + int64 i = 3; // int + bytes s = 4; // UTF-8 string + TensorProto t = 5; // tensor value + GraphProto g = 6; // graph + // Do not use field below, it's deprecated. + // optional ValueProto v = 12; // value - subsumes everything but graph + + repeated float floats = 7; // list of floats + repeated int64 ints = 8; // list of ints + repeated bytes strings = 9; // list of UTF-8 strings + repeated TensorProto tensors = 10; // list of tensors + repeated GraphProto graphs = 11; // list of graph +} + +// Defines information on value, including the name, the type, and +// the shape of the value. +message ValueInfoProto { + // This field MUST be present in this version of the IR. + string name = 1; // namespace Value + // This field MUST be present in this version of the IR. + TypeProto type = 2; + // A human-readable documentation for this value. Markdown is allowed. + string doc_string = 3; +} + +// Nodes +// +// Computation graphs are made up of a DAG of nodes, which represent what is +// commonly called a "layer" or "pipeline stage" in machine learning frameworks. +// +// For example, it can be a node of type "Conv" that takes in an image, a filter +// tensor and a bias tensor, and produces the convolved output. +message NodeProto { + repeated string input = 1; // namespace Value + repeated string output = 2; // namespace Value + + // An optional identifier for this node in a graph. + // This field MAY be absent in ths version of the IR. + string name = 3; // namespace Node + + // The symbolic identifier of the Operator to execute. + string op_type = 4; // namespace Operator + // The domain of the OperatorSet that specifies the operator named by op_type. + string domain = 7; // namespace Domain + + // Additional named attributes. + repeated AttributeProto attribute = 5; + + // A human-readable documentation for this node. Markdown is allowed. + string doc_string = 6; +} + +// Models +// +// ModelProto is a top-level file/container format for bundling a ML model and +// associating its computation graph with metadata. +// +// The semantics of the model are described by the associated GraphProto. +message ModelProto { + // The version of the IR this model targets. See Version enum above. + // This field MUST be present. + int64 ir_version = 1; + + // The OperatorSets this model relies on. + // All ModelProtos MUST have at least one entry that + // specifies which version of the ONNX OperatorSet is + // being imported. + // + // All nodes in the ModelProto's graph will bind against the operator + // with the same-domain/same-op_type operator with the HIGHEST version + // in the referenced operator sets. + repeated OperatorSetIdProto opset_import = 8; + + // The name of the framework or tool used to generate this model. + // This field SHOULD be present to indicate which implementation/tool/framework + // emitted the model. + string producer_name = 2; + + // The version of the framework or tool used to generate this model. + // This field SHOULD be present to indicate which implementation/tool/framework + // emitted the model. + string producer_version = 3; + + // Domain name of the model. + // We use reverse domain names as name space indicators. For example: + // `com.facebook.fair` or `com.microsoft.cognitiveservices` + // + // Together with `model_version` and GraphProto.name, this forms the unique identity of + // the graph. + string domain = 4; + + // The version of the graph encoded. See Version enum below. + int64 model_version = 5; + + // A human-readable documentation for this model. Markdown is allowed. + string doc_string = 6; + + // The parameterized graph that is evaluated to execute the model. + GraphProto graph = 7; + // kezhan: This field is not in ONNX, and will be pushed into ONNX with good use cases in microsoft. + repeated FunctionProto functions = 100; + + // Named metadata values; keys should be distinct. + repeated StringStringEntryProto metadata_props = 14; +}; + +// StringStringEntryProto follows the pattern for cross-proto-version maps. +// See https://developers.google.com/protocol-buffers/docs/proto3#maps +message StringStringEntryProto { + string key = 1; + string value= 2; +}; + +message QuantInfo { + string tensor_name = 1; + // The keys used in the mapping below will be pre-defined in ONNX spec. + // For example, for linear case, “SCALE”, “ZERO_POINT” will be pre-defined as + // quantization parameter keys. + repeated StringStringEntryProto quant_parameter_tensor_names = 2; +}; + +// Graphs +// +// A graph defines the computational logic of a model and is comprised of a parameterized +// list of nodes that form a directed acyclic graph based on their inputs and outputs. +// This is the equivalent of the "network" or "graph" in many deep learning +// frameworks. +message GraphProto { + // The nodes in the graph, sorted topologically. + repeated NodeProto node = 1; + + // The name of the graph. + string name = 2; // namespace Graph + + // A list of named tensor values, used to specify constant inputs of the graph. + // Each TensorProto entry must have a distinct name (within the list) that + // MAY also appear in the input list. + repeated TensorProto initializer = 5; + + // A human-readable documentation for this graph. Markdown is allowed. + string doc_string = 10; + + // The inputs and outputs of the graph. + repeated ValueInfoProto input = 11; + repeated ValueInfoProto output = 12; + + // Information for the values in the graph. The ValueInfoProto.name's + // must be distinct. It is optional for a value to appear in value_info list. + repeated ValueInfoProto value_info = 13; + + // This field carries information to indicate the mapping among a tensor and its + // quantization parameter tensors. For example: + // A tensor “a” and its quantization parameter tensor are “scale_a” and + // “zero_point_a” (in linear case). + repeated QuantInfo quantization_annotation = 100; + + // DO NOT USE the following fields, they were deprecated from earlier versions. + // repeated string input = 3; + // repeated string output = 4; + // optional int64 ir_version = 6; + // optional int64 producer_version = 7; + // optional string producer_tag = 8; + // optional string domain = 9; +} + +// Tensors +// +// A serialized tensor value. +message TensorProto { + enum DataType { + UNDEFINED = 0; + // Basic types. + FLOAT = 1; // float + UINT8 = 2; // uint8_t + INT8 = 3; // int8_t + UINT16 = 4; // uint16_t + INT16 = 5; // int16_t + INT32 = 6; // int32_t + INT64 = 7; // int64_t + STRING = 8; // string + BOOL = 9; // bool + + // IEEE754 half-precision floating-point format (16 bits wide). + // This format has 1 sign bit, 5 exponent bits, and 10 mantissa bits. + FLOAT16 = 10; + + DOUBLE = 11; + UINT32 = 12; + UINT64 = 13; + COMPLEX64 = 14; // complex with float32 real and imaginary components + COMPLEX128 = 15; // complex with float64 real and imaginary components + + // Non-IEEE floating-point format based on IEEE754 single-precision + // floating-point number truncated to 16 bits. + // This format has 1 sign bit, 8 exponent bits, and 7 mantissa bits. + BFLOAT16 = 16; + + // Future extensions go here. + } + + // The shape of the tensor. + repeated int64 dims = 1; + + // The data type of the tensor. + // This field MUST have a valid TensorProto.DataType value + int32 data_type = 2; + + // For very large tensors, we may want to store them in chunks, in which + // case the following fields will specify the segment that is stored in + // the current TensorProto. + message Segment { + int64 begin = 1; + int64 end = 2; + } + Segment segment = 3; + + // Tensor content must be organized in row-major order. + // + // Depending on the data_type field, exactly one of the fields below with + // name ending in _data is used to store the elements of the tensor. + + // For float and complex64 values + // Complex64 tensors are encoded as a single array of floats, + // with the real components appearing in odd numbered positions, + // and the corresponding imaginary component apparing in the + // subsequent even numbered position. (e.g., [1.0 + 2.0i, 3.0 + 4.0i] + // is encoded as [1.0, 2.0 ,3.0 ,4.0] + // When this field is present, the data_type field MUST be FLOAT or COMPLEX64. + repeated float float_data = 4 [packed = true]; + + // For int32, uint8, int8, uint16, int16, bool, and float16 values + // float16 values must be bit-wise converted to an uint16_t prior + // to writing to the buffer. + // When this field is present, the data_type field MUST be + // INT32, INT16, INT8, UINT16, UINT8, BOOL, or FLOAT16 + repeated int32 int32_data = 5 [packed = true]; + + // For strings. + // Each element of string_data is a UTF-8 encoded Unicode + // string. No trailing null, no leading BOM. The protobuf "string" + // scalar type is not used to match ML community conventions. + // When this field is present, the data_type field MUST be STRING + repeated bytes string_data = 6; + + // For int64. + // When this field is present, the data_type field MUST be INT64 + repeated int64 int64_data = 7 [packed = true]; + + // Optionally, a name for the tensor. + string name = 8; // namespace Value + + // A human-readable documentation for this tensor. Markdown is allowed. + string doc_string = 12; + + // Serializations can either use one of the fields above, or use this + // raw bytes field. The only exception is the string case, where one is + // required to store the content in the repeated bytes string_data field. + // + // When this raw_data field is used to store tensor value, elements MUST + // be stored in as fixed-width, little-endian order. + // Floating-point data types MUST be stored in IEEE 754 format. + // Complex64 elements must be written as two consecutive FLOAT values, real component first. + // Complex128 elements must be written as two consecutive DOUBLE values, real component first. + // Boolean type MUST be written one byte per tensor element (00000001 for true, 00000000 for false). + // + // Note: the advantage of specific field rather than the raw_data field is + // that in some cases (e.g. int data), protobuf does a better packing via + // variable length storage, and may lead to smaller binary footprint. + // When this field is present, the data_type field MUST NOT be STRING or UNDEFINED + bytes raw_data = 9; + + // Data can be stored inside the protobuf file using type-specific fields or raw_data. + // Alternatively, raw bytes data can be stored in an external file, using the external_data field. + // external_data stores key-value pairs describing data location. Recognized keys are: + // - "location" (required) - POSIX filesystem path relative to the directory where the ONNX + // protobuf model was stored + // - "offset" (optional) - position of byte at which stored data begins. Integer stored as string. + // Offset values SHOULD be multiples 4096 (page size) to enable mmap support. + // - "length" (optional) - number of bytes containing data. Integer stored as string. + // - "checksum" (optional) - SHA1 digest of file specified in under 'location' key. + repeated StringStringEntryProto external_data = 13; + + // Location of the data for this tensor. MUST be one of: + // - DEFAULT - data stored inside the protobuf message. Data is stored in raw_data (if set) otherwise in type-specified field. + // - EXTERNAL - data stored in an external location as described by external_data field. + enum DataLocation { + DEFAULT = 0; + EXTERNAL = 1; + } + + // If value not set, data is stored in raw_data (if set) otherwise in type-specified field. + DataLocation data_location = 14; + + // For double + // Complex128 tensors are encoded as a single array of doubles, + // with the real components appearing in odd numbered positions, + // and the corresponding imaginary component apparing in the + // subsequent even numbered position. (e.g., [1.0 + 2.0i, 3.0 + 4.0i] + // is encoded as [1.0, 2.0 ,3.0 ,4.0] + // When this field is present, the data_type field MUST be DOUBLE or COMPLEX128 + repeated double double_data = 10 [packed = true]; + + // For uint64 and uint32 values + // When this field is present, the data_type field MUST be + // UINT32 or UINT64 + repeated uint64 uint64_data = 11 [packed = true]; +} + +// Defines a tensor shape. A dimension can be either an integer value +// or a symbolic variable. A symbolic variable represents an unknown +// dimension. +message TensorShapeProto { + message Dimension { + oneof value { + int64 dim_value = 1; + string dim_param = 2; // namespace Shape + }; + // Standard denotation can optionally be used to denote tensor + // dimensions with standard semantic descriptions to ensure + // that operations are applied to the correct axis of a tensor. + // Refer to https://github.com/onnx/onnx/blob/master/docs/DimensionDenotation.md#denotation-definition + // for pre-defined dimension denotations. + string denotation = 3; + }; + repeated Dimension dim = 1; +} + +// Types +// +// The standard ONNX data types. +message TypeProto { + + message Tensor { + // This field MUST NOT have the value of UNDEFINED + // This field MUST have a valid TensorProto.DataType value + // This field MUST be present for this version of the IR. + int32 elem_type = 1; + TensorShapeProto shape = 2; + } + + + // repeated T + message Sequence { + // The type and optional shape of each element of the sequence. + // This field MUST be present for this version of the IR. + TypeProto elem_type = 1; + }; + + // map + message Map { + // This field MUST have a valid TensorProto.DataType value + // This field MUST be present for this version of the IR. + // This field MUST refer to an integral type ([U]INT{8|16|32|64}) or STRING + int32 key_type = 1; + // This field MUST be present for this version of the IR. + TypeProto value_type = 2; + }; + + message Opaque { + // When missing, the domain is the same as the model's. + string domain = 1; + // The name is optional but significant when provided. + string name = 2; + // parameters that help defining the type + // DEPRECATED do not use. + // repeated TypeProto parameters = 3; + } + + message SparseTensor { + // This field MUST NOT have the value of UNDEFINED + // This field MUST have a valid TensorProto.DataType value + // This field MUST be present for this version of the IR. + int32 elem_type = 1; + TensorShapeProto shape = 2; + } + + + oneof value { + // The type of a tensor. + Tensor tensor_type = 1; + + + // NOTE: DNN-only implementations of ONNX MAY elect to not support non-tensor values + // as input and output to graphs and nodes. These types are needed to naturally + // support classical ML operators. DNN operators SHOULD restrict their input + // and output types to tensors. + + // The type of a sequence. + Sequence sequence_type = 4; + + // The type of a map. + Map map_type = 5; + + Opaque opaque_type = 7; + + SparseTensor sparse_tensor_type = 8; + + } + + // An optional denotation can be used to denote the whole + // type with a standard semantic description as to what is + // stored inside. Refer to https://github.com/onnx/onnx/blob/master/docs/TypeDenotation.md#type-denotation-definition + // for pre-defined type denotations. + string denotation = 6; +} + +// Operator Sets +// +// OperatorSets are uniquely identified by a (domain, opset_version) pair. +message OperatorSetIdProto { + // The domain of the operator set being identified. + // The empty string ("") or absence of this field implies the operator + // set that is defined as part of the ONNX specification. + // This field MUST be present in this version of the IR when referring to any other operator set. + string domain = 1; + + // The version of the operator set being identified. + // This field MUST be present in this version of the IR. + int64 version = 2; +} + +// Operator/function status. +enum OperatorStatus { + EXPERIMENTAL = 0; + STABLE = 1; +} + +message FunctionProto { + // The name of the function, similar usage of op_type in OperatorProto. + string name = 1; + + // The first version of a function set which contains this function. + // When there's any breaking change for this function, the function set + // contains the function needs to bump its version, and since_version of + // the updated function will be changed to the updated function set version. + int64 since_version = 2; + + // This field indicates whether the syntax, semantics, or presence + // of this function is in an experimental or stable stage. Once an + // function is published as STABLE, its syntax and semantics MUST NOT + // change in subsequent versions of the operator set. + // When a function is published as EXPERIMENTAL, the syntax and semantics + // of the function MAY change across operator set versions. + // Functions "become" stable by deprecating the experimental version and + // introducing a new stable function with the same name. + OperatorStatus status = 3; + + // The inputs and outputs of the function. + repeated string input = 4; + repeated string output = 5; + + // The attributes of the function. + repeated string attribute= 6; + + // The nodes in the function. + repeated NodeProto node = 7; + // A human-readable documentation for this function. Markdown is allowed. + string doc_string = 8; +} \ No newline at end of file diff --git a/onnxruntime/core/protobuf/onnx-operators-ml.proto b/onnxruntime/core/protobuf/onnx-operators-ml.proto index 4c4fb2b49b..aadf0cf47f 100644 --- a/onnxruntime/core/protobuf/onnx-operators-ml.proto +++ b/onnxruntime/core/protobuf/onnx-operators-ml.proto @@ -2,6 +2,7 @@ // WARNING: This file is automatically generated! Please edit onnx.in.proto. // + // Copyright (c) Facebook Inc. and Microsoft Corporation. // Licensed under the MIT license. @@ -44,7 +45,8 @@ import "onnx-ml.proto"; // *since_version* is the version of the operator set that // this operator was initially declared in. // -message OperatorProto { +message OperatorProto { + // The name of the operator within a domain. // This field MUST be present in this version of the IR. optional string op_type = 1; @@ -123,7 +125,7 @@ message OperatorSetProto { // The operators specified by this operator set. // The (name, version) MUST be unique across all OperatorProtos in operator repeated OperatorProto operator = 8; - + // The functions specified by this operator set. // The (name, version) MUST be unique across all OperatorProtos/FunctionProtos in operator/functions repeated FunctionProto functions = 9; diff --git a/onnxruntime/core/protobuf/onnx-operators-ml.proto3 b/onnxruntime/core/protobuf/onnx-operators-ml.proto3 new file mode 100644 index 0000000000..16ed77be35 --- /dev/null +++ b/onnxruntime/core/protobuf/onnx-operators-ml.proto3 @@ -0,0 +1,132 @@ +// +// WARNING: This file is automatically generated! Please edit onnx.in.proto. +// + + +// Copyright (c) Facebook Inc. and Microsoft Corporation. +// Licensed under the MIT license. + +syntax = "proto3"; + +package onnx; +import "onnx-ml.proto3"; + +// +// This file contains the proto definitions for OperatorSetProto and +// OperatorProto. OperatorSetProtos are used to describe a versioned +// set of operators that can be used by a ModelProto. +// +// Like ModelProto, OperatorSetProto is defined as a top-level file/wire +// format, however their usage is different. +// +// ModelProto files are used to describe executable graphs that can be +// executed directly by a framework, runtime, or engine. +// +// OperatorSetProto files are used to describe a set of operators that are +// available in a given environment. The file TBD.TBD is the OperatorSetProto +// that describes the ONNX standard operators. +// + +// An OperatorProto represents the immutable specification of the signature +// and semantics of an operator. +// +// Operators are declared as part of an OperatorSet, which also defines the +// domain name for the set. +// +// Operators are uniquely identified by a three part identifier +// (domain, op_type, since_version) +// where +// *domain* is the domain of an operator set that +// contains this operator specification. +// +// *op_type* is the name of the operator as referenced by a +// NodeProto.op_type +// +// *since_version* is the version of the operator set that +// this operator was initially declared in. +// +message OperatorProto { + + // The name of the operator within a domain. + // This field MUST be present in this version of the IR. + string op_type = 1; + + // The version of the operator set that first introduced this + // operator. This value MUST be the same value as the + // opset_version of the operator set that first published this operator. + // Subsequent versions of the operator set MUST NOT alter the signature + // or semantics of the operator once published as STABLE. + // This field MUST be present in this version of the IR. + int64 since_version = 2; + + // This field indicates whether the syntax, semantics, or presence + // of this operator is in an experimental or stable stage. Once an + // operator is published as STABLE, it's syntax and semantics MUST NOT + // change in subsequent versions of the operator set. + // When an operator is published as EXPERIMENTAL, the syntax and semantics + // of the operator MAY change across operator set versions. + // Operators "become" stable by deprecating the experimental version and + // introducing a new stable operator with the same op_type. + OperatorStatus status = 3; + + // Eventually we will declare the signature of the operator here + + // A human-readable documentation for this operator. Markdown is allowed. + string doc_string = 10; +} + +// An OperatorSetProto represents an immutable set of immutable operator +// specifications. +// +// The domain of the set (OperatorSetProto.domain) is a reverse-DNS name +// that disambiguates operator sets defined by independent entities. +// +// The version of the set (opset_version) is a monotonically increasing +// integer that indicates changes to the membership of the operator set. +// +// +// Operator sets are uniquely identified by a two part identifier (domain, opset_version) +// +// Like ModelProto, OperatorSetProto is intended as a top-level file/wire format, +// and thus has the standard format headers in addition to the operator set information. +// +message OperatorSetProto { + // All OperatorSetProtos start with a distingushed byte sequence to disambiguate + // protobuf files containing OperatorSets from other content. + // This field MUST be "ONNXOPSET" + // This field MUST be present in this version of the IR + string magic = 1; + + // All OperatorSetProtos indicate the version of the IR syntax and semantics + // they adhere to. It is always IR_VERSION. + // This field MUST be present in this version of the IR + int32 ir_version = 2; + + // The prerelease component of the SemVer of the IR. + // This field MAY be absent in this version of the IR + string ir_version_prerelease = 3; + + // The build metadata component of the SemVer of the IR. + // This field MAY be absent in this version of the IR + string ir_build_metadata = 7; + + // Domain name of the operator set, in reverse DNS form (e.g., com.acme.dnnops). + string domain = 4; + + // The version of the set of operators. This is a simple int value + // that is monotonically increasing as new versions of operator set + // are published. All operators in this set MUST have version + // numbers no greater than opset_version. + int64 opset_version = 5; + + // A human-readable documentation for this set of operators. Markdown is allowed. + string doc_string = 6; + + // The operators specified by this operator set. + // The (name, version) MUST be unique across all OperatorProtos in operator + repeated OperatorProto operator = 8; + + // The functions specified by this operator set. + // The (name, version) MUST be unique across all OperatorProtos/FunctionProtos in operator/functions + repeated FunctionProto functions = 9; +} diff --git a/onnxruntime/core/protobuf/onnx-operators.in.proto b/onnxruntime/core/protobuf/onnx-operators.in.proto new file mode 100644 index 0000000000..3b1df88f81 --- /dev/null +++ b/onnxruntime/core/protobuf/onnx-operators.in.proto @@ -0,0 +1,131 @@ +// Copyright (c) Facebook Inc. and Microsoft Corporation. +// Licensed under the MIT license. + +syntax = "proto2"; + +package {PACKAGE_NAME}; +// #if ONNX-ML +import "onnx/onnx-ml.proto"; +// #else +import "onnx/onnx.proto"; +// #endif + +// +// This file contains the proto definitions for OperatorSetProto and +// OperatorProto. OperatorSetProtos are used to describe a versioned +// set of operators that can be used by a ModelProto. +// +// Like ModelProto, OperatorSetProto is defined as a top-level file/wire +// format, however their usage is different. +// +// ModelProto files are used to describe executable graphs that can be +// executed directly by a framework, runtime, or engine. +// +// OperatorSetProto files are used to describe a set of operators that are +// available in a given environment. The file TBD.TBD is the OperatorSetProto +// that describes the ONNX standard operators. +// + +// An OperatorProto represents the immutable specification of the signature +// and semantics of an operator. +// +// Operators are declared as part of an OperatorSet, which also defines the +// domain name for the set. +// +// Operators are uniquely identified by a three part identifier +// (domain, op_type, since_version) +// where +// *domain* is the domain of an operator set that +// contains this operator specification. +// +// *op_type* is the name of the operator as referenced by a +// NodeProto.op_type +// +// *since_version* is the version of the operator set that +// this operator was initially declared in. +// +message OperatorProto { + + // The name of the operator within a domain. + // This field MUST be present in this version of the IR. + optional string op_type = 1; + + // The version of the operator set that first introduced this + // operator. This value MUST be the same value as the + // opset_version of the operator set that first published this operator. + // Subsequent versions of the operator set MUST NOT alter the signature + // or semantics of the operator once published as STABLE. + // This field MUST be present in this version of the IR. + optional int64 since_version = 2; + + // This field indicates whether the syntax, semantics, or presence + // of this operator is in an experimental or stable stage. Once an + // operator is published as STABLE, it's syntax and semantics MUST NOT + // change in subsequent versions of the operator set. + // When an operator is published as EXPERIMENTAL, the syntax and semantics + // of the operator MAY change across operator set versions. + // Operators "become" stable by deprecating the experimental version and + // introducing a new stable operator with the same op_type. + optional OperatorStatus status = 3; + + // Eventually we will declare the signature of the operator here + + // A human-readable documentation for this operator. Markdown is allowed. + optional string doc_string = 10; +} + +// An OperatorSetProto represents an immutable set of immutable operator +// specifications. +// +// The domain of the set (OperatorSetProto.domain) is a reverse-DNS name +// that disambiguates operator sets defined by independent entities. +// +// The version of the set (opset_version) is a monotonically increasing +// integer that indicates changes to the membership of the operator set. +// +// +// Operator sets are uniquely identified by a two part identifier (domain, opset_version) +// +// Like ModelProto, OperatorSetProto is intended as a top-level file/wire format, +// and thus has the standard format headers in addition to the operator set information. +// +message OperatorSetProto { + // All OperatorSetProtos start with a distingushed byte sequence to disambiguate + // protobuf files containing OperatorSets from other content. + // This field MUST be "ONNXOPSET" + // This field MUST be present in this version of the IR + optional string magic = 1; + + // All OperatorSetProtos indicate the version of the IR syntax and semantics + // they adhere to. It is always IR_VERSION. + // This field MUST be present in this version of the IR + optional int32 ir_version = 2; + + // The prerelease component of the SemVer of the IR. + // This field MAY be absent in this version of the IR + optional string ir_version_prerelease = 3; + + // The build metadata component of the SemVer of the IR. + // This field MAY be absent in this version of the IR + optional string ir_build_metadata = 7; + + // Domain name of the operator set, in reverse DNS form (e.g., com.acme.dnnops). + optional string domain = 4; + + // The version of the set of operators. This is a simple int value + // that is monotonically increasing as new versions of operator set + // are published. All operators in this set MUST have version + // numbers no greater than opset_version. + optional int64 opset_version = 5; + + // A human-readable documentation for this set of operators. Markdown is allowed. + optional string doc_string = 6; + + // The operators specified by this operator set. + // The (name, version) MUST be unique across all OperatorProtos in operator + repeated OperatorProto operator = 8; + + // The functions specified by this operator set. + // The (name, version) MUST be unique across all OperatorProtos/FunctionProtos in operator/functions + repeated FunctionProto functions = 9; +} diff --git a/onnxruntime/core/protobuf/onnx.in.proto b/onnxruntime/core/protobuf/onnx.in.proto new file mode 100644 index 0000000000..4495646600 --- /dev/null +++ b/onnxruntime/core/protobuf/onnx.in.proto @@ -0,0 +1,593 @@ +// Copyright (c) Facebook Inc. and Microsoft Corporation. +// Licensed under the MIT license. + +syntax = "proto2"; + +package {PACKAGE_NAME}; + +// Overview +// +// ONNX is an open specification that is comprised of the following components: +// +// 1) A definition of an extensible computation graph model. +// 2) Definitions of standard data types. +// 3) Definitions of built-in operators. +// +// This document describes the syntax of models and their computation graphs, +// as well as the standard data types. Together, they are referred to as the ONNX +// Intermediate Representation, or 'IR' for short. +// +// The normative semantic specification of the ONNX IR is found in docs/IR.md. +// Definitions of the built-in neural network operators may be found in docs/Operators.md. +// #if ONNX-ML +// Definitions of the built-in classical machine learning operators may be found in +// docs/Operators-ml.md. +// #endif + +// Notes +// +// Release +// +// We are still in the very early stage of defining ONNX. The current +// version of ONNX is a starting point. While we are actively working +// towards a complete spec, we would like to get the community involved +// by sharing our working version of ONNX. +// +// Protobuf compatibility +// +// To simplify framework compatibility, ONNX is defined using the subset of protobuf +// that is compatible with both protobuf v2 and v3. This means that we do not use any +// protobuf features that are only available in one of the two versions. +// +// Here are the most notable contortions we have to carry out to work around +// these limitations: +// +// - No 'map' (added protobuf 3.0). We instead represent mappings as lists +// of key-value pairs, where order does not matter and duplicates +// are not allowed. + + +// Versioning +// +// ONNX versioning is specified in docs/IR.md and elaborated on in docs/Versioning.md +// +// To be compatible with both proto2 and proto3, we will use a version number +// that is not defined by the default value but an explicit enum number. +enum Version { + // proto3 requires the first enum value to be zero. + // We add this just to appease the compiler. + _START_VERSION = 0; + // The version field is always serialized and we will use it to store the + // version that the graph is generated from. This helps us set up version + // control. + // For the IR, we are using simple numbers starting with with 0x00000001, + // which was the version we published on Oct 10, 2017. + IR_VERSION_2017_10_10 = 0x0000000000000001; + + // IR_VERSION 2 published on Oct 30, 2017 + // - Added type discriminator to AttributeProto to support proto3 users + IR_VERSION_2017_10_30 = 0x0000000000000002; + + // IR VERSION 3 published on Nov 3, 2017 + // - For operator versioning: + // - Added new message OperatorSetIdProto + // - Added opset_import in ModelProto + // - For vendor extensions, added domain in NodeProto + IR_VERSION_2017_11_3 = 0x0000000000000003; + + // IR VERSION 4 published on Jan 22, 2019 + // - Relax constraint that initializers should be a subset of graph inputs + // - Add type BFLOAT16 + IR_VERSION = 0x0000000000000004; +} + +// Attributes +// +// A named attribute containing either singular float, integer, string, graph, +// and tensor values, or repeated float, integer, string, graph, and tensor values. +// An AttributeProto MUST contain the name field, and *only one* of the +// following content fields, effectively enforcing a C/C++ union equivalent. +message AttributeProto { + + // Note: this enum is structurally identical to the OpSchema::AttrType + // enum defined in schema.h. If you rev one, you likely need to rev the other. + enum AttributeType { + UNDEFINED = 0; + FLOAT = 1; + INT = 2; + STRING = 3; + TENSOR = 4; + GRAPH = 5; + + FLOATS = 6; + INTS = 7; + STRINGS = 8; + TENSORS = 9; + GRAPHS = 10; + } + + // The name field MUST be present for this version of the IR. + optional string name = 1; // namespace Attribute + + // if ref_attr_name is not empty, ref_attr_name is the attribute name in parent function. + // In this case, this AttributeProto does not contain data, and it's a reference of attribute + // in parent scope. + // NOTE: This should ONLY be used in function (sub-graph). It's invalid to be used in main graph. + optional string ref_attr_name = 21; + + // A human-readable documentation for this attribute. Markdown is allowed. + optional string doc_string = 13; + + // The type field MUST be present for this version of the IR. + // For 0.0.1 versions of the IR, this field was not defined, and + // implementations needed to use has_field hueristics to determine + // which value field was in use. For IR_VERSION 0.0.2 or later, this + // field MUST be set and match the f|i|s|t|... field in use. This + // change was made to accomodate proto3 implementations. + optional AttributeType type = 20; // discriminator that indicates which field below is in use + + // Exactly ONE of the following fields must be present for this version of the IR + optional float f = 2; // float + optional int64 i = 3; // int + optional bytes s = 4; // UTF-8 string + optional TensorProto t = 5; // tensor value + optional GraphProto g = 6; // graph + // Do not use field below, it's deprecated. + // optional ValueProto v = 12; // value - subsumes everything but graph + + repeated float floats = 7; // list of floats + repeated int64 ints = 8; // list of ints + repeated bytes strings = 9; // list of UTF-8 strings + repeated TensorProto tensors = 10; // list of tensors + repeated GraphProto graphs = 11; // list of graph +} + +// Defines information on value, including the name, the type, and +// the shape of the value. +message ValueInfoProto { + // This field MUST be present in this version of the IR. + optional string name = 1; // namespace Value + // This field MUST be present in this version of the IR. + optional TypeProto type = 2; + // A human-readable documentation for this value. Markdown is allowed. + optional string doc_string = 3; +} + +// Nodes +// +// Computation graphs are made up of a DAG of nodes, which represent what is +// commonly called a "layer" or "pipeline stage" in machine learning frameworks. +// +// For example, it can be a node of type "Conv" that takes in an image, a filter +// tensor and a bias tensor, and produces the convolved output. +message NodeProto { + repeated string input = 1; // namespace Value + repeated string output = 2; // namespace Value + + // An optional identifier for this node in a graph. + // This field MAY be absent in ths version of the IR. + optional string name = 3; // namespace Node + + // The symbolic identifier of the Operator to execute. + optional string op_type = 4; // namespace Operator + // The domain of the OperatorSet that specifies the operator named by op_type. + optional string domain = 7; // namespace Domain + + // Additional named attributes. + repeated AttributeProto attribute = 5; + + // A human-readable documentation for this node. Markdown is allowed. + optional string doc_string = 6; +} + +// Models +// +// ModelProto is a top-level file/container format for bundling a ML model and +// associating its computation graph with metadata. +// +// The semantics of the model are described by the associated GraphProto. +message ModelProto { + // The version of the IR this model targets. See Version enum above. + // This field MUST be present. + optional int64 ir_version = 1; + + // The OperatorSets this model relies on. + // All ModelProtos MUST have at least one entry that + // specifies which version of the ONNX OperatorSet is + // being imported. + // + // All nodes in the ModelProto's graph will bind against the operator + // with the same-domain/same-op_type operator with the HIGHEST version + // in the referenced operator sets. + repeated OperatorSetIdProto opset_import = 8; + + // The name of the framework or tool used to generate this model. + // This field SHOULD be present to indicate which implementation/tool/framework + // emitted the model. + optional string producer_name = 2; + + // The version of the framework or tool used to generate this model. + // This field SHOULD be present to indicate which implementation/tool/framework + // emitted the model. + optional string producer_version = 3; + + // Domain name of the model. + // We use reverse domain names as name space indicators. For example: + // `com.facebook.fair` or `com.microsoft.cognitiveservices` + // + // Together with `model_version` and GraphProto.name, this forms the unique identity of + // the graph. + optional string domain = 4; + + // The version of the graph encoded. See Version enum below. + optional int64 model_version = 5; + + // A human-readable documentation for this model. Markdown is allowed. + optional string doc_string = 6; + + // The parameterized graph that is evaluated to execute the model. + optional GraphProto graph = 7; + // kezhan: This field is not in ONNX, and will be pushed into ONNX with good use cases in microsoft. + repeated FunctionProto functions = 100; + + // Named metadata values; keys should be distinct. + repeated StringStringEntryProto metadata_props = 14; +}; + +// StringStringEntryProto follows the pattern for cross-proto-version maps. +// See https://developers.google.com/protocol-buffers/docs/proto3#maps +message StringStringEntryProto { + optional string key = 1; + optional string value= 2; +}; + +message QuantInfo { + optional string tensor_name = 1; + // The keys used in the mapping below will be pre-defined in ONNX spec. + // For example, for linear case, “SCALE”, “ZERO_POINT” will be pre-defined as + // quantization parameter keys. + repeated StringStringEntryProto quant_parameter_tensor_names = 2; +}; + +// Graphs +// +// A graph defines the computational logic of a model and is comprised of a parameterized +// list of nodes that form a directed acyclic graph based on their inputs and outputs. +// This is the equivalent of the "network" or "graph" in many deep learning +// frameworks. +message GraphProto { + // The nodes in the graph, sorted topologically. + repeated NodeProto node = 1; + + // The name of the graph. + optional string name = 2; // namespace Graph + + // A list of named tensor values, used to specify constant inputs of the graph. + // Each TensorProto entry must have a distinct name (within the list) that + // MAY also appear in the input list. + repeated TensorProto initializer = 5; + + // A human-readable documentation for this graph. Markdown is allowed. + optional string doc_string = 10; + + // The inputs and outputs of the graph. + repeated ValueInfoProto input = 11; + repeated ValueInfoProto output = 12; + + // Information for the values in the graph. The ValueInfoProto.name's + // must be distinct. It is optional for a value to appear in value_info list. + repeated ValueInfoProto value_info = 13; + + // This field carries information to indicate the mapping among a tensor and its + // quantization parameter tensors. For example: + // A tensor “a” and its quantization parameter tensor are “scale_a” and + // “zero_point_a” (in linear case). + repeated QuantInfo quantization_annotation = 100; + + // DO NOT USE the following fields, they were deprecated from earlier versions. + // repeated string input = 3; + // repeated string output = 4; + // optional int64 ir_version = 6; + // optional int64 producer_version = 7; + // optional string producer_tag = 8; + // optional string domain = 9; +} + +// Tensors +// +// A serialized tensor value. +message TensorProto { + enum DataType { + UNDEFINED = 0; + // Basic types. + FLOAT = 1; // float + UINT8 = 2; // uint8_t + INT8 = 3; // int8_t + UINT16 = 4; // uint16_t + INT16 = 5; // int16_t + INT32 = 6; // int32_t + INT64 = 7; // int64_t + STRING = 8; // string + BOOL = 9; // bool + + // IEEE754 half-precision floating-point format (16 bits wide). + // This format has 1 sign bit, 5 exponent bits, and 10 mantissa bits. + FLOAT16 = 10; + + DOUBLE = 11; + UINT32 = 12; + UINT64 = 13; + COMPLEX64 = 14; // complex with float32 real and imaginary components + COMPLEX128 = 15; // complex with float64 real and imaginary components + + // Non-IEEE floating-point format based on IEEE754 single-precision + // floating-point number truncated to 16 bits. + // This format has 1 sign bit, 8 exponent bits, and 7 mantissa bits. + BFLOAT16 = 16; + + // Future extensions go here. + } + + // The shape of the tensor. + repeated int64 dims = 1; + + // The data type of the tensor. + // This field MUST have a valid TensorProto.DataType value + optional int32 data_type = 2; + + // For very large tensors, we may want to store them in chunks, in which + // case the following fields will specify the segment that is stored in + // the current TensorProto. + message Segment { + optional int64 begin = 1; + optional int64 end = 2; + } + optional Segment segment = 3; + + // Tensor content must be organized in row-major order. + // + // Depending on the data_type field, exactly one of the fields below with + // name ending in _data is used to store the elements of the tensor. + + // For float and complex64 values + // Complex64 tensors are encoded as a single array of floats, + // with the real components appearing in odd numbered positions, + // and the corresponding imaginary component apparing in the + // subsequent even numbered position. (e.g., [1.0 + 2.0i, 3.0 + 4.0i] + // is encoded as [1.0, 2.0 ,3.0 ,4.0] + // When this field is present, the data_type field MUST be FLOAT or COMPLEX64. + repeated float float_data = 4 [packed = true]; + + // For int32, uint8, int8, uint16, int16, bool, and float16 values + // float16 values must be bit-wise converted to an uint16_t prior + // to writing to the buffer. + // When this field is present, the data_type field MUST be + // INT32, INT16, INT8, UINT16, UINT8, BOOL, or FLOAT16 + repeated int32 int32_data = 5 [packed = true]; + + // For strings. + // Each element of string_data is a UTF-8 encoded Unicode + // string. No trailing null, no leading BOM. The protobuf "string" + // scalar type is not used to match ML community conventions. + // When this field is present, the data_type field MUST be STRING + repeated bytes string_data = 6; + + // For int64. + // When this field is present, the data_type field MUST be INT64 + repeated int64 int64_data = 7 [packed = true]; + + // Optionally, a name for the tensor. + optional string name = 8; // namespace Value + + // A human-readable documentation for this tensor. Markdown is allowed. + optional string doc_string = 12; + + // Serializations can either use one of the fields above, or use this + // raw bytes field. The only exception is the string case, where one is + // required to store the content in the repeated bytes string_data field. + // + // When this raw_data field is used to store tensor value, elements MUST + // be stored in as fixed-width, little-endian order. + // Floating-point data types MUST be stored in IEEE 754 format. + // Complex64 elements must be written as two consecutive FLOAT values, real component first. + // Complex128 elements must be written as two consecutive DOUBLE values, real component first. + // Boolean type MUST be written one byte per tensor element (00000001 for true, 00000000 for false). + // + // Note: the advantage of specific field rather than the raw_data field is + // that in some cases (e.g. int data), protobuf does a better packing via + // variable length storage, and may lead to smaller binary footprint. + // When this field is present, the data_type field MUST NOT be STRING or UNDEFINED + optional bytes raw_data = 9; + + // Data can be stored inside the protobuf file using type-specific fields or raw_data. + // Alternatively, raw bytes data can be stored in an external file, using the external_data field. + // external_data stores key-value pairs describing data location. Recognized keys are: + // - "location" (required) - POSIX filesystem path relative to the directory where the ONNX + // protobuf model was stored + // - "offset" (optional) - position of byte at which stored data begins. Integer stored as string. + // Offset values SHOULD be multiples 4096 (page size) to enable mmap support. + // - "length" (optional) - number of bytes containing data. Integer stored as string. + // - "checksum" (optional) - SHA1 digest of file specified in under 'location' key. + repeated StringStringEntryProto external_data = 13; + + // Location of the data for this tensor. MUST be one of: + // - DEFAULT - data stored inside the protobuf message. Data is stored in raw_data (if set) otherwise in type-specified field. + // - EXTERNAL - data stored in an external location as described by external_data field. + enum DataLocation { + DEFAULT = 0; + EXTERNAL = 1; + } + + // If value not set, data is stored in raw_data (if set) otherwise in type-specified field. + optional DataLocation data_location = 14; + + // For double + // Complex128 tensors are encoded as a single array of doubles, + // with the real components appearing in odd numbered positions, + // and the corresponding imaginary component apparing in the + // subsequent even numbered position. (e.g., [1.0 + 2.0i, 3.0 + 4.0i] + // is encoded as [1.0, 2.0 ,3.0 ,4.0] + // When this field is present, the data_type field MUST be DOUBLE or COMPLEX128 + repeated double double_data = 10 [packed = true]; + + // For uint64 and uint32 values + // When this field is present, the data_type field MUST be + // UINT32 or UINT64 + repeated uint64 uint64_data = 11 [packed = true]; +} + +// Defines a tensor shape. A dimension can be either an integer value +// or a symbolic variable. A symbolic variable represents an unknown +// dimension. +message TensorShapeProto { + message Dimension { + oneof value { + int64 dim_value = 1; + string dim_param = 2; // namespace Shape + }; + // Standard denotation can optionally be used to denote tensor + // dimensions with standard semantic descriptions to ensure + // that operations are applied to the correct axis of a tensor. + // Refer to https://github.com/onnx/onnx/blob/master/docs/DimensionDenotation.md#denotation-definition + // for pre-defined dimension denotations. + optional string denotation = 3; + }; + repeated Dimension dim = 1; +} + +// Types +// +// The standard ONNX data types. +message TypeProto { + + message Tensor { + // This field MUST NOT have the value of UNDEFINED + // This field MUST have a valid TensorProto.DataType value + // This field MUST be present for this version of the IR. + optional int32 elem_type = 1; + optional TensorShapeProto shape = 2; + } + +// #if ONNX-ML + + // repeated T + message Sequence { + // The type and optional shape of each element of the sequence. + // This field MUST be present for this version of the IR. + optional TypeProto elem_type = 1; + }; + + // map + message Map { + // This field MUST have a valid TensorProto.DataType value + // This field MUST be present for this version of the IR. + // This field MUST refer to an integral type ([U]INT{8|16|32|64}) or STRING + optional int32 key_type = 1; + // This field MUST be present for this version of the IR. + optional TypeProto value_type = 2; + }; + + message Opaque { + // When missing, the domain is the same as the model's. + optional string domain = 1; + // The name is optional but significant when provided. + optional string name = 2; + // parameters that help defining the type + // DEPRECATED do not use. + // repeated TypeProto parameters = 3; + } + + message SparseTensor { + // This field MUST NOT have the value of UNDEFINED + // This field MUST have a valid TensorProto.DataType value + // This field MUST be present for this version of the IR. + optional int32 elem_type = 1; + optional TensorShapeProto shape = 2; + } + +// #endif + + oneof value { + // The type of a tensor. + Tensor tensor_type = 1; + +// #if ONNX-ML + + // NOTE: DNN-only implementations of ONNX MAY elect to not support non-tensor values + // as input and output to graphs and nodes. These types are needed to naturally + // support classical ML operators. DNN operators SHOULD restrict their input + // and output types to tensors. + + // The type of a sequence. + Sequence sequence_type = 4; + + // The type of a map. + Map map_type = 5; + + Opaque opaque_type = 7; + + SparseTensor sparse_tensor_type = 8; + +// #endif + } + + // An optional denotation can be used to denote the whole + // type with a standard semantic description as to what is + // stored inside. Refer to https://github.com/onnx/onnx/blob/master/docs/TypeDenotation.md#type-denotation-definition + // for pre-defined type denotations. + optional string denotation = 6; +} + +// Operator Sets +// +// OperatorSets are uniquely identified by a (domain, opset_version) pair. +message OperatorSetIdProto { + // The domain of the operator set being identified. + // The empty string ("") or absence of this field implies the operator + // set that is defined as part of the ONNX specification. + // This field MUST be present in this version of the IR when referring to any other operator set. + optional string domain = 1; + + // The version of the operator set being identified. + // This field MUST be present in this version of the IR. + optional int64 version = 2; +} + +// Operator/function status. +enum OperatorStatus { + EXPERIMENTAL = 0; + STABLE = 1; +} + +message FunctionProto { + // The name of the function, similar usage of op_type in OperatorProto. + optional string name = 1; + + // The first version of a function set which contains this function. + // When there's any breaking change for this function, the function set + // contains the function needs to bump its version, and since_version of + // the updated function will be changed to the updated function set version. + optional int64 since_version = 2; + + // This field indicates whether the syntax, semantics, or presence + // of this function is in an experimental or stable stage. Once an + // function is published as STABLE, its syntax and semantics MUST NOT + // change in subsequent versions of the operator set. + // When a function is published as EXPERIMENTAL, the syntax and semantics + // of the function MAY change across operator set versions. + // Functions "become" stable by deprecating the experimental version and + // introducing a new stable function with the same name. + optional OperatorStatus status = 3; + + // The inputs and outputs of the function. + repeated string input = 4; + repeated string output = 5; + + // The attributes of the function. + repeated string attribute= 6; + + // The nodes in the function. + repeated NodeProto node = 7; + // A human-readable documentation for this function. Markdown is allowed. + optional string doc_string = 8; +}