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diff --git a/config-model/src/main/protobuf/onnx.proto b/config-model/src/main/protobuf/onnx.proto deleted file mode 100644 index dc6542867e0..00000000000 --- a/config-model/src/main/protobuf/onnx.proto +++ /dev/null @@ -1,464 +0,0 @@ -// -// WARNING: This file is automatically generated! Please edit onnx.in.proto. -// - - -// Copyright (c) Facebook Inc. and Microsoft Corporation. -// Licensed under the MIT license. - -syntax = "proto2"; - -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. - -// 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. We should use version as - // xx(major) - xx(minor) - xxxx(bugfix) - // and we are starting with 0x00000001 (0.0.1), which was the - // version we published on Oct 10, 2017. - IR_VERSION_2017_10_10 = 0x00000001; - - // IR_VERSION 0.0.2 published on Oct 30, 2017 - // - Added type discriminator to AttributeProto to support proto3 users - IR_VERSION_2017_10_30 = 0x00000002; - - // IR VERSION 0.0.3 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 = 0x00000003; -} - -// 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; - - // 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; -}; - -// 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 - // also appears 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; - - // 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 - - // Advanced types - 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 - // Future extensions go here. - } - - // The shape of the tensor. - repeated int64 dims = 1; - - // The data type of the tensor. - optional DataType 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, INT8, BOOL, or FLOAT32 - 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; - - // For double - // Complex64 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. - optional string denotation = 3; - }; - repeated Dimension dim = 1; -} - -// A set of pre-defined constants to be used as values for -// the standard denotation field in TensorShapeProto.Dimension -// for semantic description of the tensor dimension. -message DenotationConstProto { - // Describe a batch number dimension. - optional string DATA_BATCH = 1 [default = "DATA_BATCH"]; - // Describe a channel dimension. - optional string DATA_CHANNEL = 2 [default = "DATA_CHANNEL"]; - // Describe a time dimension. - optional string DATA_TIME = 3 [default = "DATA_TIME"]; - // Describe a feature dimension. This is typically a feature - // dimension in RNN and/or spatial dimension in CNN. - optional string DATA_FEATURE = 4 [default = "DATA_FEATURE"]; - // Describe a filter in-channel dimension. This is the dimension - // that is identical (in size) to the channel dimension of the input - // image feature maps. - optional string FILTER_IN_CHANNEL = 5 [default = "FILTER_IN_CHANNEL"]; - // Describe a filter out channel dimension. This is the dimension - // that is identical (int size) to the channel dimension of the output - // image feature maps. - optional string FILTER_OUT_CHANNEL = 6 [default = "FILTER_OUT_CHANNEL"]; - // Describe a filter spatial dimension. - optional string FILTER_SPATIAL = 7 [default = "FILTER_SPATIAL"]; -} - -// Types -// -// The standard ONNX data types. -message TypeProto { - - message Tensor { - // This field MUST NOT have the value of UNDEFINED - // This field MUST be present for this version of the IR. - optional TensorProto.DataType elem_type = 1; - optional TensorShapeProto shape = 2; - } - - - oneof value { - // The type of a tensor. - Tensor tensor_type = 1; - - } -} - -// 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; -}
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