mindspore2022/mindspore/lite/schema/model.fbs

/**
 * Copyright 2019 Huawei Technologies Co., Ltd
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

include "ops.fbs";

namespace mindspore.schema;

// This corresponds to the version.
file_identifier "MSL1";
// File extension of any written files.
file_extension "ms";

enum NodeType: int {
    ValueNode,  // const
    Parameter,  // var
    CNode       // op
}

table QuantParam {
    scale: double;
    zeroPoint: int;
    min: double = 0;
    max: double = 0;
    narrowRange: bool = true;
    numBits: int = 8;
    inited: bool = false;
    varCorr: float = 1;
    meanCorr: float = 0;
    dstDtype: int = 32;
}

table Tensor {
    nodeType: NodeType;
    // data type
    dataType: int;
    // shape
    dims: [int];
    format: Format;
    refCount: int;
    offset: int;
    data: [ubyte];
    quantParams: [QuantParam];
    quantClusters: [float];
    name: string;
}

union PrimitiveType {
    Concat,
    SoftMax,
    Activation,
    Conv2D,
    FusedBatchNorm,
    BatchNorm,
    BiasAdd,
    Pooling,
    ROIPooling,
    DepthwiseConv2D,
    DeDepthwiseConv2D,
    Resize,
    DetectionPostProcess,
    FullConnection,
    Mean,  // DEPRECATED
    DeConv2D,
    Scale,
    Reshape,
    Eltwise,
    NetOutput,
    Add,
    Sub,
    MatMul,
    StridedSlice,
    Power,
    Slice,
    Stack,
    Mul,
    RealDiv,
    Pad,
    Maximum,
    Minimum,
    PReLU,
    LeakyReLU,
    ArgMax,
    ArgMin,
    Exp,
    Crop,
    Range,
    Rsqrt,
    ExpandDims,
    Tile,
    Cast,
    Shape,
    Nchw2Nhwc,
    Nhwc2Nchw,
    QuantDTypeCast,
    Split,
    Permute,
    FakeQuantWithMinMaxVars,
    Equal,
    Less,
    Greater,
    NotEqual,
    LessEqual,
    GreaterEqual,
    Min,
    Floor,
    Abs,
    Neg,
    Cos,
    Sin,
    Sqrt,
    Square,
    Constant,
    Log,
    Tan,
    Atan,
    Asin,
    Clip,
    Transpose,
    Squeeze,
    Unsqueeze,
    Upsample,
    Dropout,
    Broadcast,
    BroadcastTo,
    Lrn,
    ZerosLike,
    TopK,
    SpaceToDepth,
    SpaceToBatch,
    SparseToDense,
    ReverseSequence,
    Rank,
    Gather,
    GatherNd,
    Fill,
    Elu,
    DepthToSpace,
    BatchToSpace,
    AddN,
    Ceil,
    EmbeddingLookup,
    EmbeddingLookupSparse,
    FloorDiv,
    FloorMod,
    L2Norm,
    LocalResponseNormalization,
    MatrixDiag,
    Reduce,
    Reverse,
    Round,
    Select,
    Scatter,
    ScatterND,
    ConstantOfShape,
    Unique,
    Unstack,
    LogicalAnd,
    LogicalOr,
    LogicalXor,
    LogicalNot,
    OnnxInt8Quantize,
    OnnxInt8Dequantize,
    FakeQuantWithMinMax,
    FakeQuantWithMinMaxPerChannel,
    BatchNormFold,
    MulFold,
    AddFold,
    SquaredDifference,
    Flatten,
    FlattenGrad,
    TupleGetItem,
    Div,
    Where,
    OneHot,
    Lstm,
    Conv2DGradFilter,
    Conv2DGradInput,
    PoolingGrad,
    BNGrad,
    Assign,
    ApplyMomentum,
    BiasGrad,
    SoftmaxCrossEntropy,
    AddGrad,
    SubGrad,
    MulGrad,
    DivGrad,
    PowerGrad,
    ActivationGrad,
    PriorBox,
    SpaceToBatchND,
    Depend,
    Return,
    MakeTuple,
    ToFormat,
    Proposal,
    Custom,
    BlackBox,
    NegGrad,
    LogGrad,
    BatchToSpaceND,
    LshProjection,
    HashtableLookup,
    SkipGram,
    DeConv2DGradFilter,
    CustomPredict,
    CustomNormalize,
    CustomExtractFeatures,
    AudioSpectrogram,
    Mfcc,
    Rfft,
    FftReal,
    FftImag,
    Sgd,
    Adam,
    GroupConv2DGradInput,
    Loop,
    NonMaxSuppression,
    InstanceNorm,
    Identity,
    LayerNorm,
    While,
    ControlDepend,
    UnsortedSegmentSum,
    AssignAdd,
    OnesLike,
    BinaryCrossEntropyGrad,
    BinaryCrossEntropy,
    LpNormalization,
    DropoutGrad,
    MaximumGrad,
    MinimumGrad,
    Switch,
    Partial,
    TensorListFromTensor,
    TensorListStack,
    TensorListGetItem,
    TensorListSetItem,
    TensorListReserve,
    All,
    Assert,
    Adder,
    SparseSoftmaxCrossEntropy,
    SmoothL1Loss,
    SmoothL1LossGrad,
    SigmoidCrossEntropyWithLogits,
    SigmoidCrossEntropyWithLogitsGrad,
    Reciprocal,
    Merge,
}

enum QuantType: int {
    QUANT_NONE,
    AwareTraining,
    WeightQuant,
    PostTraining
}

table Primitive {
    value: PrimitiveType;
}

table CNode {
    name: string;
    nodeType: NodeType = CNode;
    primitive: Primitive;
    inputIndex: [uint];
    outputIndex: [uint];
    quantType: QuantType = QUANT_NONE;
}

table SubGraph {
    name:string;
    inputIndices: [uint];
    outputIndices: [uint];
    nodeIndices: [uint];
    tensorIndices: [uint];
}

table MetaGraph {
    name: string;
    version: string;
    fmkType: int; // 0:tf,1:caffe
    inputIndex: [uint];
    outputIndex: [uint];
    mempoolSize: uint;
    nodes: [CNode];
    allTensors: [Tensor]; // weight + input + output
    subGraph : [SubGraph];
}

root_type MetaGraph;