wehub-resource-sync
162 lines
2.7 KiB
Plaintext
162 lines
2.7 KiB
Plaintext
//
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// MNN.fbs
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// MNN
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//
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// Created by MNN on 2019/1/4.
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// Copyright © 2018, Alibaba Group Holding Limited
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//
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include "CaffeOp.fbs";
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include "Tensor.fbs";
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include "Type.fbs";
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namespace MNN;
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enum FusedActivation : byte {
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kTfLiteActNone = 0,
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kTfLiteActRelu,
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kTfLiteActRelu1,
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kTfLiteActRelu6,
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kTfLiteActTanh,
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kTfLiteActSignBit,
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kTfLiteActSigmoid,
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}
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table QuantizedParam {
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zeroPoint: int;
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scale: float;
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}
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table QuantizedAdd {
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activationType: FusedActivation;
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input1QuantizedParam: QuantizedParam;
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input2QuantizedParam: QuantizedParam;
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outputQuantizedParam: QuantizedParam;
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}
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enum ModeFormat : byte {
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TENSORFLOW = 0,
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TFLITE
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}
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enum QuantizeMode : byte {
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MIN_COMBINED = 0,
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MIN_FIRST,
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SCALED
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}
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table Dequantize {
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inputQuantizedParam: QuantizedParam;
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mode: QuantizeMode;
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modelFormat: ModeFormat = TENSORFLOW;
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type: DataType;
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}
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table QuantizedAvgPool {
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kernelX: int;
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kernelY: int;
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modelFormat: ModeFormat = TENSORFLOW;
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outputActivationMax: int;
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outputActivationMin: int;
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padType: PoolPadType;
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padX: int;
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padY: int;
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strideX: int;
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strideY: int;
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type: DataType;
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}
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table QuantizedBiasAdd {
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bias: [int32];
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inputType: DataType;
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max: int32;
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min: int32;
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outputType: DataType;
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}
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table QuantizedConcat {
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activationType: FusedActivation;
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axis: int;
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inputScale: [float];
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inputZeroPoint: [int];
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outputQuantizedParam: QuantizedParam;
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}
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table QuantizedLogistic {
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inputQuantizedParam: QuantizedParam;
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outputQuantizedParam: QuantizedParam;
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}
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table QuantizedMatMul {
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transposeA: bool;
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transposeB: bool;
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}
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table QuantizedMaxPool {
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kernelX: int;
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kernelY: int;
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modelFormat: ModeFormat = TENSORFLOW;
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outputActivationMax: int;
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outputActivationMin: int;
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padType: PoolPadType;
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padX: int;
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padY: int;
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strideX: int;
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strideY: int;
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type: DataType;
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}
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table QuantizedRelu {
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type: DataType;
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}
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table QuantizedRelu6 {
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type: DataType;
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}
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table QuantizedReshape {
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dims: [int];
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modelFormat: ModeFormat = TENSORFLOW;
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}
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table QuantizedSoftmax {
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beta: float;
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inputScale: float;
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}
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enum QuantizeRoundMode : byte {
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HALF_AWAY_FROM_ZERO = 0,
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HALF_TO_EVEN
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}
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table QuantizeV2 {
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type: DataType;
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mode: QuantizeMode;
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roundMode: QuantizeRoundMode;
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}
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table RequantizationRange { }
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table Requantize { }
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table TfQuantizedConv2D {
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bias: [int32];
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biasflag: bool;
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common: Convolution2DCommon;
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weight: [ubyte];
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// tflite
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activationType: FusedActivation;
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multiplier: int32;
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outMax: int32;
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outMin: int32;
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shift: int32;
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// for depthwise_conv2D
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biasQuantizedParam: QuantizedParam;
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depthMultiplier: int;
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filterQuantizedParam: QuantizedParam;
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inputQuantizedParam: QuantizedParam;
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modelFormat: ModeFormat = TENSORFLOW;
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outputQuantizedParam: QuantizedParam;
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}
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