Lines Matching refs:auto
120 + const auto end = fbb_.EndTable(start_);
121 + auto o = flatbuffers::Offset<TuneParam>(end);
146 + auto local__ = local ? _fbb.CreateVector<int32_t>(*local) : 0;
147 + auto block__ = block ? _fbb.CreateVector<int32_t>(*block) : 0;
148 + auto shape__ = shape ? _fbb.CreateVector<int32_t>(*shape) : 0;
149 + auto opPara__ = opPara ? _fbb.CreateVector<int32_t>(*opPara) : 0;
213 + const auto end = fbb_.EndTable(start_);
214 + auto o = flatbuffers::Offset<ProgramBinary>(end);
239 + auto program_name__ = program_name ? _fbb.CreateString(program_name) : 0;
240 + auto build_option__ = build_option ? _fbb.CreateString(build_option) : 0;
241 + auto data__ = data ? _fbb.CreateVector<uint8_t>(*data) : 0;
297 + const auto end = fbb_.EndTable(start_);
298 + auto o = flatbuffers::Offset<GpuCache>(end);
320 + auto name__ = name ? _fbb.CreateString(name) : 0;
321 + auto version__ = version ? _fbb.CreateString(version) : 0;
322 + auto allBins__ = allBins ? _fbb.CreateVector<flatbuffers::Offset<mindspore::schema::ProgramBinar…
481 + const auto end = fbb_.EndTable(start_);
482 + auto o = flatbuffers::Offset<TuneParam>(end);
507 + auto local__ = local ? _fbb.CreateVector<int32_t>(*local) : 0;
508 + auto block__ = block ? _fbb.CreateVector<int32_t>(*block) : 0;
509 + auto shape__ = shape ? _fbb.CreateVector<int32_t>(*shape) : 0;
510 + auto opPara__ = opPara ? _fbb.CreateVector<int32_t>(*opPara) : 0;
603 + const auto end = fbb_.EndTable(start_);
604 + auto o = flatbuffers::Offset<ProgramBinary>(end);
629 + auto program_name__ = program_name ? _fbb.CreateString(program_name) : 0;
630 + auto build_option__ = build_option ? _fbb.CreateString(build_option) : 0;
631 + auto data__ = data ? _fbb.CreateVector<uint8_t>(*data) : 0;
712 + const auto end = fbb_.EndTable(start_);
713 + auto o = flatbuffers::Offset<GpuCache>(end);
735 + auto name__ = name ? _fbb.CreateString(name) : 0;
736 + auto version__ = version ? _fbb.CreateString(version) : 0;
737 + auto allBins__ = allBins ? _fbb.CreateVector<flatbuffers::Offset<mindspore::schema::ProgramBinar…
748 + auto _o = std::unique_ptr<TuneParamT>(new TuneParamT());
756 + { auto _e = local(); if (_e) { _o->local.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0;…
757 + { auto _e = block(); if (_e) { _o->block.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0;…
758 + { auto _e = shape(); if (_e) { _o->shape.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0;…
759 + { auto _e = opPara(); if (_e) { _o->opPara.resize(_e->size()); for (flatbuffers::uoffset_t _i = …
770 + auto _local = _o->local.size() ? _fbb.CreateVector(_o->local) : 0;
771 + auto _block = _o->block.size() ? _fbb.CreateVector(_o->block) : 0;
772 + auto _shape = _o->shape.size() ? _fbb.CreateVector(_o->shape) : 0;
773 + auto _opPara = _o->opPara.size() ? _fbb.CreateVector(_o->opPara) : 0;
783 + auto _o = std::unique_ptr<ProgramBinaryT>(new ProgramBinaryT());
791 + { auto _e = program_name(); if (_e) _o->program_name = _e->str(); }
792 + { auto _e = build_option(); if (_e) _o->build_option = _e->str(); }
793 + { auto _e = tune(); if (_e) _o->tune = std::unique_ptr<mindspore::schema::TuneParamT>(_e->UnPack…
794 + { auto _e = data(); if (_e) { _o->data.resize(_e->size()); std::copy(_e->begin(), _e->end(), _o-…
805 + auto _program_name = _o->program_name.empty() ? 0 : _fbb.CreateString(_o->program_name);
806 + auto _build_option = _o->build_option.empty() ? 0 : _fbb.CreateString(_o->build_option);
807 + auto _tune = _o->tune ? CreateTuneParam(_fbb, _o->tune.get(), _rehasher) : 0;
808 + auto _data = _o->data.size() ? _fbb.CreateVector(_o->data) : 0;
818 + auto _o = std::unique_ptr<GpuCacheT>(new GpuCacheT());
826 + { auto _e = name(); if (_e) _o->name = _e->str(); }
827 + { auto _e = version(); if (_e) _o->version = _e->str(); }
828 + { auto _e = allBins(); if (_e) { _o->allBins.resize(_e->size()); for (flatbuffers::uoffset_t _i …
839 + auto _name = _o->name.empty() ? 0 : _fbb.CreateString(_o->name);
840 + auto _version = _o->version.empty() ? 0 : _fbb.CreateString(_o->version);
841 + auto _allBins = _o->allBins.size() ? _fbb.CreateVector<flatbuffers::Offset<mindspore::schema::Pr…
1260 + const auto end = fbb_.EndTable(start_);
1261 + auto o = flatbuffers::Offset<QuantParam>(end);
1378 + const auto end = fbb_.EndTable(start_);
1379 + auto o = flatbuffers::Offset<ExternalData>(end);
1404 + auto checkSum__ = checkSum ? _fbb.CreateString(checkSum) : 0;
1405 + auto location__ = location ? _fbb.CreateString(location) : 0;
1610 + const auto end = fbb_.EndTable(start_);
1611 + auto o = flatbuffers::Offset<Tensor>(end);
1663 + auto dims__ = dims ? _fbb.CreateVector<int32_t>(*dims) : 0;
1664 + auto data__ = data ? _fbb.CreateVector<uint8_t>(*data) : 0;
1665 + auto quantParams__ = quantParams ? _fbb.CreateVector<flatbuffers::Offset<mindspore::schema::Quan…
1666 + auto quantClusters__ = quantClusters ? _fbb.CreateVector<float>(*quantClusters) : 0;
1667 + auto name__ = name ? _fbb.CreateString(name) : 0;
1668 + auto externalData__ = externalData ? _fbb.CreateVector<flatbuffers::Offset<mindspore::schema::Ex…
3217 + const auto end = fbb_.EndTable(start_);
3218 + auto o = flatbuffers::Offset<Primitive>(end);
3341 + const auto end = fbb_.EndTable(start_);
3342 + auto o = flatbuffers::Offset<CNode>(end);
3373 + auto name__ = name ? _fbb.CreateString(name) : 0;
3374 + auto inputIndex__ = inputIndex ? _fbb.CreateVector<uint32_t>(*inputIndex) : 0;
3375 + auto outputIndex__ = outputIndex ? _fbb.CreateVector<uint32_t>(*outputIndex) : 0;
3483 + const auto end = fbb_.EndTable(start_);
3484 + auto o = flatbuffers::Offset<SubGraph>(end);
3512 + auto name__ = name ? _fbb.CreateString(name) : 0;
3513 + auto inputIndices__ = inputIndices ? _fbb.CreateVector<uint32_t>(*inputIndices) : 0;
3514 + auto outputIndices__ = outputIndices ? _fbb.CreateVector<uint32_t>(*outputIndices) : 0;
3515 + auto nodeIndices__ = nodeIndices ? _fbb.CreateVector<uint32_t>(*nodeIndices) : 0;
3516 + auto tensorIndices__ = tensorIndices ? _fbb.CreateVector<uint32_t>(*tensorIndices) : 0;
3701 + const auto end = fbb_.EndTable(start_);
3702 + auto o = flatbuffers::Offset<MetaGraph>(end);
3748 + auto name__ = name ? _fbb.CreateString(name) : 0;
3749 + auto version__ = version ? _fbb.CreateString(version) : 0;
3750 + auto inputIndex__ = inputIndex ? _fbb.CreateVector<uint32_t>(*inputIndex) : 0;
3751 + auto outputIndex__ = outputIndex ? _fbb.CreateVector<uint32_t>(*outputIndex) : 0;
3752 + auto nodes__ = nodes ? _fbb.CreateVector<flatbuffers::Offset<mindspore::schema::CNode>>(*nodes) …
3753 + auto allTensors__ = allTensors ? _fbb.CreateVector<flatbuffers::Offset<mindspore::schema::Tensor…
3754 + auto subGraph__ = subGraph ? _fbb.CreateVector<flatbuffers::Offset<mindspore::schema::SubGraph>>…
3755 + auto obfMetaData__ = obfMetaData ? _fbb.CreateVector<uint8_t>(*obfMetaData) : 0;
3774 + auto _o = std::unique_ptr<QuantParamT>(new QuantParamT());
3782 + { auto _e = scale(); _o->scale = _e; }
3783 + { auto _e = zeroPoint(); _o->zeroPoint = _e; }
3784 + { auto _e = min(); _o->min = _e; }
3785 + { auto _e = max(); _o->max = _e; }
3786 + { auto _e = narrowRange(); _o->narrowRange = _e; }
3787 + { auto _e = numBits(); _o->numBits = _e; }
3788 + { auto _e = inited(); _o->inited = _e; }
3789 + { auto _e = varCorr(); _o->varCorr = _e; }
3790 + { auto _e = meanCorr(); _o->meanCorr = _e; }
3791 + { auto _e = dstDtype(); _o->dstDtype = _e; }
3792 + { auto _e = roundType(); _o->roundType = _e; }
3793 + { auto _e = multiplier(); _o->multiplier = _e; }
3804 + auto _scale = _o->scale;
3805 + auto _zeroPoint = _o->zeroPoint;
3806 + auto _min = _o->min;
3807 + auto _max = _o->max;
3808 + auto _narrowRange = _o->narrowRange;
3809 + auto _numBits = _o->numBits;
3810 + auto _inited = _o->inited;
3811 + auto _varCorr = _o->varCorr;
3812 + auto _meanCorr = _o->meanCorr;
3813 + auto _dstDtype = _o->dstDtype;
3814 + auto _roundType = _o->roundType;
3815 + auto _multiplier = _o->multiplier;
3833 + auto _o = std::unique_ptr<ExternalDataT>(new ExternalDataT());
3841 + { auto _e = checkSum(); if (_e) _o->checkSum = _e->str(); }
3842 + { auto _e = location(); if (_e) _o->location = _e->str(); }
3843 + { auto _e = offset(); _o->offset = _e; }
3844 + { auto _e = length(); _o->length = _e; }
3855 + auto _checkSum = _o->checkSum.empty() ? 0 : _fbb.CreateString(_o->checkSum);
3856 + auto _location = _o->location.empty() ? 0 : _fbb.CreateString(_o->location);
3857 + auto _offset = _o->offset;
3858 + auto _length = _o->length;
3868 + auto _o = std::unique_ptr<TensorT>(new TensorT());
3876 + { auto _e = nodeType(); _o->nodeType = _e; }
3877 + { auto _e = dataType(); _o->dataType = _e; }
3878 + { auto _e = dims(); if (_e) { _o->dims.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _…
3879 + { auto _e = format(); _o->format = _e; }
3880 + { auto _e = refCount(); _o->refCount = _e; }
3881 + { auto _e = offset(); _o->offset = _e; }
3882 + { auto _e = data(); if (_e) { _o->data.resize(_e->size()); std::copy(_e->begin(), _e->end(), _o-…
3883 + { auto _e = quantParams(); if (_e) { _o->quantParams.resize(_e->size()); for (flatbuffers::uoffs…
3884 + { auto _e = quantClusters(); if (_e) { _o->quantClusters.resize(_e->size()); for (flatbuffers::u…
3885 + { auto _e = name(); if (_e) _o->name = _e->str(); }
3886 + { auto _e = enableHuffmanCode(); _o->enableHuffmanCode = _e; }
3887 + { auto _e = weightQunatCompressType(); _o->weightQunatCompressType = _e; }
3888 + { auto _e = externalData(); if (_e) { _o->externalData.resize(_e->size()); for (flatbuffers::uof…
3899 + auto _nodeType = _o->nodeType;
3900 + auto _dataType = _o->dataType;
3901 + auto _dims = _o->dims.size() ? _fbb.CreateVector(_o->dims) : 0;
3902 + auto _format = _o->format;
3903 + auto _refCount = _o->refCount;
3904 + auto _offset = _o->offset;
3905 + auto _data = _o->data.size() ? _fbb.CreateVector(_o->data) : 0;
3906 + auto _quantParams = _o->quantParams.size() ? _fbb.CreateVector<flatbuffers::Offset<mindspore::sc…
3907 + auto _quantClusters = _o->quantClusters.size() ? _fbb.CreateVector(_o->quantClusters) : 0;
3908 + auto _name = _o->name.empty() ? 0 : _fbb.CreateString(_o->name);
3909 + auto _enableHuffmanCode = _o->enableHuffmanCode;
3910 + auto _weightQunatCompressType = _o->weightQunatCompressType;
3911 + auto _externalData = _o->externalData.size() ? _fbb.CreateVector<flatbuffers::Offset<mindspore::…
3930 + auto _o = std::unique_ptr<PrimitiveT>(new PrimitiveT());
3938 + { auto _e = value_type(); _o->value.type = _e; }
3939 + { auto _e = value(); if (_e) _o->value.value = mindspore::schema::PrimitiveTypeUnion::UnPack(_e,…
3950 + auto _value_type = _o->value.type;
3951 + auto _value = _o->value.Pack(_fbb);
3959 + auto _o = std::unique_ptr<CNodeT>(new CNodeT());
3967 + { auto _e = name(); if (_e) _o->name = _e->str(); }
3968 + { auto _e = primitive(); if (_e) _o->primitive = std::unique_ptr<mindspore::schema::PrimitiveT>(…
3969 + { auto _e = inputIndex(); if (_e) { _o->inputIndex.resize(_e->size()); for (flatbuffers::uoffset…
3970 + { auto _e = outputIndex(); if (_e) { _o->outputIndex.resize(_e->size()); for (flatbuffers::uoffs…
3971 + { auto _e = quantType(); _o->quantType = _e; }
3972 + { auto _e = deviceType(); _o->deviceType = _e; }
3983 + auto _name = _o->name.empty() ? 0 : _fbb.CreateString(_o->name);
3984 + auto _primitive = _o->primitive ? CreatePrimitive(_fbb, _o->primitive.get(), _rehasher) : 0;
3985 + auto _inputIndex = _o->inputIndex.size() ? _fbb.CreateVector(_o->inputIndex) : 0;
3986 + auto _outputIndex = _o->outputIndex.size() ? _fbb.CreateVector(_o->outputIndex) : 0;
3987 + auto _quantType = _o->quantType;
3988 + auto _deviceType = _o->deviceType;
4000 + auto _o = std::unique_ptr<SubGraphT>(new SubGraphT());
4008 + { auto _e = name(); if (_e) _o->name = _e->str(); }
4009 + { auto _e = inputIndices(); if (_e) { _o->inputIndices.resize(_e->size()); for (flatbuffers::uof…
4010 + { auto _e = outputIndices(); if (_e) { _o->outputIndices.resize(_e->size()); for (flatbuffers::u…
4011 + { auto _e = nodeIndices(); if (_e) { _o->nodeIndices.resize(_e->size()); for (flatbuffers::uoffs…
4012 + { auto _e = tensorIndices(); if (_e) { _o->tensorIndices.resize(_e->size()); for (flatbuffers::u…
4023 + auto _name = _o->name.empty() ? 0 : _fbb.CreateString(_o->name);
4024 + auto _inputIndices = _o->inputIndices.size() ? _fbb.CreateVector(_o->inputIndices) : 0;
4025 + auto _outputIndices = _o->outputIndices.size() ? _fbb.CreateVector(_o->outputIndices) : 0;
4026 + auto _nodeIndices = _o->nodeIndices.size() ? _fbb.CreateVector(_o->nodeIndices) : 0;
4027 + auto _tensorIndices = _o->tensorIndices.size() ? _fbb.CreateVector(_o->tensorIndices) : 0;
4038 + auto _o = std::unique_ptr<MetaGraphT>(new MetaGraphT());
4046 + { auto _e = name(); if (_e) _o->name = _e->str(); }
4047 + { auto _e = version(); if (_e) _o->version = _e->str(); }
4048 + { auto _e = fmkType(); _o->fmkType = _e; }
4049 + { auto _e = inputIndex(); if (_e) { _o->inputIndex.resize(_e->size()); for (flatbuffers::uoffset…
4050 + { auto _e = outputIndex(); if (_e) { _o->outputIndex.resize(_e->size()); for (flatbuffers::uoffs…
4051 + { auto _e = mempoolSize(); _o->mempoolSize = _e; }
4052 + { auto _e = nodes(); if (_e) { _o->nodes.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0;…
4053 + { auto _e = allTensors(); if (_e) { _o->allTensors.resize(_e->size()); for (flatbuffers::uoffset…
4054 + { auto _e = subGraph(); if (_e) { _o->subGraph.resize(_e->size()); for (flatbuffers::uoffset_t _…
4055 + { auto _e = obfuscate(); _o->obfuscate = _e; }
4056 + { auto _e = obfMetaData(); if (_e) { _o->obfMetaData.resize(_e->size()); std::copy(_e->begin(), …
4067 + auto _name = _o->name.empty() ? 0 : _fbb.CreateString(_o->name);
4068 + auto _version = _o->version.empty() ? 0 : _fbb.CreateString(_o->version);
4069 + auto _fmkType = _o->fmkType;
4070 + auto _inputIndex = _o->inputIndex.size() ? _fbb.CreateVector(_o->inputIndex) : 0;
4071 + auto _outputIndex = _o->outputIndex.size() ? _fbb.CreateVector(_o->outputIndex) : 0;
4072 + auto _mempoolSize = _o->mempoolSize;
4073 + auto _nodes = _o->nodes.size() ? _fbb.CreateVector<flatbuffers::Offset<mindspore::schema::CNode>…
4074 + auto _allTensors = _o->allTensors.size() ? _fbb.CreateVector<flatbuffers::Offset<mindspore::sche…
4075 + auto _subGraph = _o->subGraph.size() ? _fbb.CreateVector<flatbuffers::Offset<mindspore::schema::…
4076 + auto _obfuscate = _o->obfuscate;
4077 + auto _obfMetaData = _o->obfMetaData.size() ? _fbb.CreateVector(_o->obfMetaData) : 0;
8872 + const auto end = fbb_.EndTable(start_);
8873 + auto o = flatbuffers::Offset<Abs>(end);
8976 + const auto end = fbb_.EndTable(start_);
8977 + auto o = flatbuffers::Offset<Activation>(end);
9054 + const auto end = fbb_.EndTable(start_);
9055 + auto o = flatbuffers::Offset<ActivationGrad>(end);
9126 + const auto end = fbb_.EndTable(start_);
9127 + auto o = flatbuffers::Offset<Adam>(end);
9186 + const auto end = fbb_.EndTable(start_);
9187 + auto o = flatbuffers::Offset<AddFusion>(end);
9356 + const auto end = fbb_.EndTable(start_);
9357 + auto o = flatbuffers::Offset<AdderFusion>(end);
9400 + auto kernel_size__ = kernel_size ? _fbb.CreateVector<int64_t>(*kernel_size) : 0;
9401 + auto stride__ = stride ? _fbb.CreateVector<int64_t>(*stride) : 0;
9402 + auto dilation__ = dilation ? _fbb.CreateVector<int64_t>(*dilation) : 0;
9403 + auto pad_list__ = pad_list ? _fbb.CreateVector<int64_t>(*pad_list) : 0;
9448 + const auto end = fbb_.EndTable(start_);
9449 + auto o = flatbuffers::Offset<AddGrad>(end);
9490 + const auto end = fbb_.EndTable(start_);
9491 + auto o = flatbuffers::Offset<AddN>(end);
9546 + const auto end = fbb_.EndTable(start_);
9547 + auto o = flatbuffers::Offset<All>(end);
9628 + const auto end = fbb_.EndTable(start_);
9629 + auto o = flatbuffers::Offset<ApplyMomentum>(end);
9726 + const auto end = fbb_.EndTable(start_);
9727 + auto o = flatbuffers::Offset<ArgMaxFusion>(end);
9826 + const auto end = fbb_.EndTable(start_);
9827 + auto o = flatbuffers::Offset<ArgMinFusion>(end);
9890 + const auto end = fbb_.EndTable(start_);
9891 + auto o = flatbuffers::Offset<Assert>(end);
9934 + const auto end = fbb_.EndTable(start_);
9935 + auto o = flatbuffers::Offset<Assign>(end);
9976 + const auto end = fbb_.EndTable(start_);
9977 + auto o = flatbuffers::Offset<AssignAdd>(end);
10056 + const auto end = fbb_.EndTable(start_);
10057 + auto o = flatbuffers::Offset<AudioSpectrogram>(end);
10205 + const auto end = fbb_.EndTable(start_);
10206 + auto o = flatbuffers::Offset<AvgPoolFusion>(end);
10243 + auto kernel_size__ = kernel_size ? _fbb.CreateVector<int64_t>(*kernel_size) : 0;
10244 + auto strides__ = strides ? _fbb.CreateVector<int64_t>(*strides) : 0;
10245 + auto pad__ = pad ? _fbb.CreateVector<int64_t>(*pad) : 0;
10340 + const auto end = fbb_.EndTable(start_);
10341 + auto o = flatbuffers::Offset<AvgPoolGrad>(end);
10366 + auto kernel_size__ = kernel_size ? _fbb.CreateVector<int64_t>(*kernel_size) : 0;
10367 + auto strides__ = strides ? _fbb.CreateVector<int64_t>(*strides) : 0;
10444 + const auto end = fbb_.EndTable(start_);
10445 + auto o = flatbuffers::Offset<BatchNorm>(end);
10518 + const auto end = fbb_.EndTable(start_);
10519 + auto o = flatbuffers::Offset<BatchNormGrad>(end);
10592 + const auto end = fbb_.EndTable(start_);
10593 + auto o = flatbuffers::Offset<BatchToSpace>(end);
10612 + auto block_size__ = block_size ? _fbb.CreateVector<int64_t>(*block_size) : 0;
10677 + const auto end = fbb_.EndTable(start_);
10678 + auto o = flatbuffers::Offset<BatchToSpaceND>(end);
10697 + auto block_shape__ = block_shape ? _fbb.CreateVector<int64_t>(*block_shape) : 0;
10748 + const auto end = fbb_.EndTable(start_);
10749 + auto o = flatbuffers::Offset<BiasAdd>(end);
10806 + const auto end = fbb_.EndTable(start_);
10807 + auto o = flatbuffers::Offset<BinaryCrossEntropy>(end);
10864 + const auto end = fbb_.EndTable(start_);
10865 + auto o = flatbuffers::Offset<BinaryCrossEntropyGrad>(end);
10908 + const auto end = fbb_.EndTable(start_);
10909 + auto o = flatbuffers::Offset<BiasAddGrad>(end);
10965 + const auto end = fbb_.EndTable(start_);
10966 + auto o = flatbuffers::Offset<BroadcastTo>(end);
10982 + auto shape__ = shape ? _fbb.CreateVector<int64_t>(*shape) : 0;
11018 + const auto end = fbb_.EndTable(start_);
11019 + auto o = flatbuffers::Offset<Cast>(end);
11060 + const auto end = fbb_.EndTable(start_);
11061 + auto o = flatbuffers::Offset<Ceil>(end);
11128 + const auto end = fbb_.EndTable(start_);
11129 + auto o = flatbuffers::Offset<Clip>(end);
11188 + const auto end = fbb_.EndTable(start_);
11189 + auto o = flatbuffers::Offset<Concat>(end);
11232 + const auto end = fbb_.EndTable(start_);
11233 + auto o = flatbuffers::Offset<Attention>(end);
11412 + const auto end = fbb_.EndTable(start_);
11413 + auto o = flatbuffers::Offset<Conv2DBackpropFilterFusion>(end);
11459 + auto kernel_size__ = kernel_size ? _fbb.CreateVector<int64_t>(*kernel_size) : 0;
11460 + auto stride__ = stride ? _fbb.CreateVector<int64_t>(*stride) : 0;
11461 + auto dilation__ = dilation ? _fbb.CreateVector<int64_t>(*dilation) : 0;
11462 + auto pad_list__ = pad_list ? _fbb.CreateVector<int64_t>(*pad_list) : 0;
11659 + const auto end = fbb_.EndTable(start_);
11660 + auto o = flatbuffers::Offset<Conv2DBackpropInputFusion>(end);
11709 + auto kernel_size__ = kernel_size ? _fbb.CreateVector<int64_t>(*kernel_size) : 0;
11710 + auto stride__ = stride ? _fbb.CreateVector<int64_t>(*stride) : 0;
11711 + auto dilation__ = dilation ? _fbb.CreateVector<int64_t>(*dilation) : 0;
11712 + auto pad__ = pad ? _fbb.CreateVector<int64_t>(*pad) : 0;
11713 + auto pad_list__ = pad_list ? _fbb.CreateVector<int64_t>(*pad_list) : 0;
11898 + const auto end = fbb_.EndTable(start_);
11899 + auto o = flatbuffers::Offset<Conv2DFusion>(end);
11945 + auto kernel_size__ = kernel_size ? _fbb.CreateVector<int64_t>(*kernel_size) : 0;
11946 + auto stride__ = stride ? _fbb.CreateVector<int64_t>(*stride) : 0;
11947 + auto dilation__ = dilation ? _fbb.CreateVector<int64_t>(*dilation) : 0;
11948 + auto pad_list__ = pad_list ? _fbb.CreateVector<int64_t>(*pad_list) : 0;
12158 + const auto end = fbb_.EndTable(start_);
12159 + auto o = flatbuffers::Offset<Conv2dTransposeFusion>(end);
12211 + auto kernel_size__ = kernel_size ? _fbb.CreateVector<int64_t>(*kernel_size) : 0;
12212 + auto stride__ = stride ? _fbb.CreateVector<int64_t>(*stride) : 0;
12213 + auto dilation__ = dilation ? _fbb.CreateVector<int64_t>(*dilation) : 0;
12214 + auto pad__ = pad ? _fbb.CreateVector<int64_t>(*pad) : 0;
12215 + auto pad_list__ = pad_list ? _fbb.CreateVector<int64_t>(*pad_list) : 0;
12216 + auto output_paddings__ = output_paddings ? _fbb.CreateVector<int64_t>(*output_paddings) : 0;
12264 + const auto end = fbb_.EndTable(start_);
12265 + auto o = flatbuffers::Offset<Cos>(end);
12333 + const auto end = fbb_.EndTable(start_);
12334 + auto o = flatbuffers::Offset<ConstantOfShape>(end);
12353 + auto value__ = value ? _fbb.CreateVector<float>(*value) : 0;
12417 + const auto end = fbb_.EndTable(start_);
12418 + auto o = flatbuffers::Offset<Crop>(end);
12437 + auto offsets__ = offsets ? _fbb.CreateVector<int64_t>(*offsets) : 0;
12474 + const auto end = fbb_.EndTable(start_);
12475 + auto o = flatbuffers::Offset<CustomExtractFeatures>(end);
12516 + const auto end = fbb_.EndTable(start_);
12517 + auto o = flatbuffers::Offset<CustomNormalize>(end);
12584 + const auto end = fbb_.EndTable(start_);
12585 + auto o = flatbuffers::Offset<CustomPredict>(end);
12756 + const auto end = fbb_.EndTable(start_);
12757 + auto o = flatbuffers::Offset<DeConv2DGradFilter>(end);
12800 + auto kernel_size__ = kernel_size ? _fbb.CreateVector<int64_t>(*kernel_size) : 0;
12801 + auto pad_list__ = pad_list ? _fbb.CreateVector<int64_t>(*pad_list) : 0;
12802 + auto stride__ = stride ? _fbb.CreateVector<int64_t>(*stride) : 0;
12803 + auto dilation__ = dilation ? _fbb.CreateVector<int64_t>(*dilation) : 0;
12848 + const auto end = fbb_.EndTable(start_);
12849 + auto o = flatbuffers::Offset<Depend>(end);
12916 + const auto end = fbb_.EndTable(start_);
12917 + auto o = flatbuffers::Offset<DepthToSpace>(end);
13097 + const auto end = fbb_.EndTable(start_);
13098 + auto o = flatbuffers::Offset<DetectionPostProcess>(end);
13144 + auto scale__ = scale ? _fbb.CreateVector<float>(*scale) : 0;
13204 + const auto end = fbb_.EndTable(start_);
13205 + auto o = flatbuffers::Offset<DivFusion>(end);
13248 + const auto end = fbb_.EndTable(start_);
13249 + auto o = flatbuffers::Offset<DivGrad>(end);
13304 + const auto end = fbb_.EndTable(start_);
13305 + auto o = flatbuffers::Offset<Dropout>(end);
13362 + const auto end = fbb_.EndTable(start_);
13363 + auto o = flatbuffers::Offset<DropoutGrad>(end);
13420 + const auto end = fbb_.EndTable(start_);
13421 + auto o = flatbuffers::Offset<Elu>(end);
13478 + const auto end = fbb_.EndTable(start_);
13479 + auto o = flatbuffers::Offset<Eltwise>(end);
13522 + const auto end = fbb_.EndTable(start_);
13523 + auto o = flatbuffers::Offset<Equal>(end);
13578 + const auto end = fbb_.EndTable(start_);
13579 + auto o = flatbuffers::Offset<EmbeddingLookupFusion>(end);
13660 + const auto end = fbb_.EndTable(start_);
13661 + auto o = flatbuffers::Offset<ExpFusion>(end);
13708 + const auto end = fbb_.EndTable(start_);
13709 + auto o = flatbuffers::Offset<ExpandDims>(end);
13776 + const auto end = fbb_.EndTable(start_);
13777 + auto o = flatbuffers::Offset<FakeQuantWithMinMaxVars>(end);
13848 + const auto end = fbb_.EndTable(start_);
13849 + auto o = flatbuffers::Offset<FakeQuantWithMinMaxVarsPerChannel>(end);
13894 + const auto end = fbb_.EndTable(start_);
13895 + auto o = flatbuffers::Offset<FftReal>(end);
13936 + const auto end = fbb_.EndTable(start_);
13937 + auto o = flatbuffers::Offset<FftImag>(end);
13992 + const auto end = fbb_.EndTable(start_);
13993 + auto o = flatbuffers::Offset<Flatten>(end);
14036 + const auto end = fbb_.EndTable(start_);
14037 + auto o = flatbuffers::Offset<FlattenGrad>(end);
14078 + const auto end = fbb_.EndTable(start_);
14079 + auto o = flatbuffers::Offset<Floor>(end);
14120 + const auto end = fbb_.EndTable(start_);
14121 + auto o = flatbuffers::Offset<FloorDiv>(end);
14162 + const auto end = fbb_.EndTable(start_);
14163 + auto o = flatbuffers::Offset<FloorMod>(end);
14204 + const auto end = fbb_.EndTable(start_);
14205 + auto o = flatbuffers::Offset<Fill>(end);
14296 + const auto end = fbb_.EndTable(start_);
14297 + auto o = flatbuffers::Offset<FullConnection>(end);
14384 + const auto end = fbb_.EndTable(start_);
14385 + auto o = flatbuffers::Offset<FusedBatchNorm>(end);
14432 + const auto end = fbb_.EndTable(start_);
14433 + auto o = flatbuffers::Offset<Gather>(end);
14474 + const auto end = fbb_.EndTable(start_);
14475 + auto o = flatbuffers::Offset<GatherNd>(end);
14516 + const auto end = fbb_.EndTable(start_);
14517 + auto o = flatbuffers::Offset<Greater>(end);
14558 + const auto end = fbb_.EndTable(start_);
14559 + auto o = flatbuffers::Offset<GreaterEqual>(end);
14600 + const auto end = fbb_.EndTable(start_);
14601 + auto o = flatbuffers::Offset<HashtableLookup>(end);
14656 + const auto end = fbb_.EndTable(start_);
14657 + auto o = flatbuffers::Offset<InstanceNorm>(end);
14750 + const auto end = fbb_.EndTable(start_);
14751 + auto o = flatbuffers::Offset<LayerNormFusion>(end);
14814 + const auto end = fbb_.EndTable(start_);
14815 + auto o = flatbuffers::Offset<LeakyRelu>(end);
14858 + const auto end = fbb_.EndTable(start_);
14859 + auto o = flatbuffers::Offset<Less>(end);
14900 + const auto end = fbb_.EndTable(start_);
14901 + auto o = flatbuffers::Offset<LessEqual>(end);
14942 + const auto end = fbb_.EndTable(start_);
14943 + auto o = flatbuffers::Offset<Log>(end);
14984 + const auto end = fbb_.EndTable(start_);
14985 + auto o = flatbuffers::Offset<LogGrad>(end);
15026 + const auto end = fbb_.EndTable(start_);
15027 + auto o = flatbuffers::Offset<LogicalAnd>(end);
15068 + const auto end = fbb_.EndTable(start_);
15069 + auto o = flatbuffers::Offset<LogicalNot>(end);
15110 + const auto end = fbb_.EndTable(start_);
15111 + auto o = flatbuffers::Offset<LogicalOr>(end);
15178 + const auto end = fbb_.EndTable(start_);
15179 + auto o = flatbuffers::Offset<LpNormalization>(end);
15287 + const auto end = fbb_.EndTable(start_);
15288 + auto o = flatbuffers::Offset<LRN>(end);
15316 + auto norm_region__ = norm_region ? _fbb.CreateString(norm_region) : 0;
15370 + const auto end = fbb_.EndTable(start_);
15371 + auto o = flatbuffers::Offset<LshProjection>(end);
15524 + const auto end = fbb_.EndTable(start_);
15525 + auto o = flatbuffers::Offset<LSTM>(end);
15694 + const auto end = fbb_.EndTable(start_);
15695 + auto o = flatbuffers::Offset<LSTMGrad>(end);
15793 + const auto end = fbb_.EndTable(start_);
15794 + auto o = flatbuffers::Offset<L2NormalizeFusion>(end);
15816 + auto axis__ = axis ? _fbb.CreateVector<int64_t>(*axis) : 0;
15892 + const auto end = fbb_.EndTable(start_);
15893 + auto o = flatbuffers::Offset<MatMulFusion>(end);
15940 + const auto end = fbb_.EndTable(start_);
15941 + auto o = flatbuffers::Offset<Maximum>(end);
16008 + const auto end = fbb_.EndTable(start_);
16009 + auto o = flatbuffers::Offset<MaximumGrad>(end);
16155 + const auto end = fbb_.EndTable(start_);
16156 + auto o = flatbuffers::Offset<MaxPoolFusion>(end);
16193 + auto kernel_size__ = kernel_size ? _fbb.CreateVector<int64_t>(*kernel_size) : 0;
16194 + auto strides__ = strides ? _fbb.CreateVector<int64_t>(*strides) : 0;
16195 + auto pad__ = pad ? _fbb.CreateVector<int64_t>(*pad) : 0;
16290 + const auto end = fbb_.EndTable(start_);
16291 + auto o = flatbuffers::Offset<MaxPoolGrad>(end);
16316 + auto kernel_size__ = kernel_size ? _fbb.CreateVector<int64_t>(*kernel_size) : 0;
16317 + auto strides__ = strides ? _fbb.CreateVector<int64_t>(*strides) : 0;
16356 + const auto end = fbb_.EndTable(start_);
16357 + auto o = flatbuffers::Offset<SwitchLayer>(end);
16448 + const auto end = fbb_.EndTable(start_);
16449 + auto o = flatbuffers::Offset<Mfcc>(end);
16498 + const auto end = fbb_.EndTable(start_);
16499 + auto o = flatbuffers::Offset<Minimum>(end);
16566 + const auto end = fbb_.EndTable(start_);
16567 + auto o = flatbuffers::Offset<MinimumGrad>(end);
16612 + const auto end = fbb_.EndTable(start_);
16613 + auto o = flatbuffers::Offset<Mod>(end);
16668 + const auto end = fbb_.EndTable(start_);
16669 + auto o = flatbuffers::Offset<MulFusion>(end);
16712 + const auto end = fbb_.EndTable(start_);
16713 + auto o = flatbuffers::Offset<MulGrad>(end);
16754 + const auto end = fbb_.EndTable(start_);
16755 + auto o = flatbuffers::Offset<Neg>(end);
16796 + const auto end = fbb_.EndTable(start_);
16797 + auto o = flatbuffers::Offset<NegGrad>(end);
16838 + const auto end = fbb_.EndTable(start_);
16839 + auto o = flatbuffers::Offset<NotEqual>(end);
16894 + const auto end = fbb_.EndTable(start_);
16895 + auto o = flatbuffers::Offset<NonMaxSuppression>(end);
16952 + const auto end = fbb_.EndTable(start_);
16953 + auto o = flatbuffers::Offset<OneHot>(end);
16996 + const auto end = fbb_.EndTable(start_);
16997 + auto o = flatbuffers::Offset<OnesLike>(end);
17077 + const auto end = fbb_.EndTable(start_);
17078 + auto o = flatbuffers::Offset<PadFusion>(end);
17139 + const auto end = fbb_.EndTable(start_);
17140 + auto o = flatbuffers::Offset<PartialFusion>(end);
17221 + const auto end = fbb_.EndTable(start_);
17222 + auto o = flatbuffers::Offset<PowerGrad>(end);
17295 + const auto end = fbb_.EndTable(start_);
17296 + auto o = flatbuffers::Offset<PowFusion>(end);
17479 + const auto end = fbb_.EndTable(start_);
17480 + auto o = flatbuffers::Offset<PriorBox>(end);
17526 + auto min_sizes__ = min_sizes ? _fbb.CreateVector<int64_t>(*min_sizes) : 0;
17527 + auto max_sizes__ = max_sizes ? _fbb.CreateVector<int64_t>(*max_sizes) : 0;
17528 + auto aspect_ratios__ = aspect_ratios ? _fbb.CreateVector<float>(*aspect_ratios) : 0;
17529 + auto variances__ = variances ? _fbb.CreateVector<float>(*variances) : 0;
17589 + const auto end = fbb_.EndTable(start_);
17590 + auto o = flatbuffers::Offset<PReLUFusion>(end);
17633 + const auto end = fbb_.EndTable(start_);
17634 + auto o = flatbuffers::Offset<Rank>(end);
17725 + const auto end = fbb_.EndTable(start_);
17726 + auto o = flatbuffers::Offset<Range>(end);
17775 + const auto end = fbb_.EndTable(start_);
17776 + auto o = flatbuffers::Offset<Reciprocal>(end);
17817 + const auto end = fbb_.EndTable(start_);
17818 + auto o = flatbuffers::Offset<RealDiv>(end);
17909 + const auto end = fbb_.EndTable(start_);
17910 + auto o = flatbuffers::Offset<ReduceFusion>(end);
17959 + const auto end = fbb_.EndTable(start_);
17960 + auto o = flatbuffers::Offset<Reshape>(end);
18123 + const auto end = fbb_.EndTable(start_);
18124 + auto o = flatbuffers::Offset<Resize>(end);
18211 + const auto end = fbb_.EndTable(start_);
18212 + auto o = flatbuffers::Offset<ReverseSequence>(end);
18272 + const auto end = fbb_.EndTable(start_);
18273 + auto o = flatbuffers::Offset<ReverseV2>(end);
18289 + auto axis__ = axis ? _fbb.CreateVector<int64_t>(*axis) : 0;
18339 + const auto end = fbb_.EndTable(start_);
18340 + auto o = flatbuffers::Offset<Rfft>(end);
18421 + const auto end = fbb_.EndTable(start_);
18422 + auto o = flatbuffers::Offset<ROIPooling>(end);
18469 + const auto end = fbb_.EndTable(start_);
18470 + auto o = flatbuffers::Offset<Round>(end);
18511 + const auto end = fbb_.EndTable(start_);
18512 + auto o = flatbuffers::Offset<Rsqrt>(end);
18579 + const auto end = fbb_.EndTable(start_);
18580 + auto o = flatbuffers::Offset<QuantDTypeCast>(end);
18651 + const auto end = fbb_.EndTable(start_);
18652 + auto o = flatbuffers::Offset<ScaleFusion>(end);
18697 + const auto end = fbb_.EndTable(start_);
18698 + auto o = flatbuffers::Offset<ScatterNd>(end);
18777 + const auto end = fbb_.EndTable(start_);
18778 + auto o = flatbuffers::Offset<SGD>(end);
18825 + const auto end = fbb_.EndTable(start_);
18826 + auto o = flatbuffers::Offset<Shape>(end);
18867 + const auto end = fbb_.EndTable(start_);
18868 + auto o = flatbuffers::Offset<SigmoidCrossEntropyWithLogits>(end);
18909 + const auto end = fbb_.EndTable(start_);
18910 + auto o = flatbuffers::Offset<SigmoidCrossEntropyWithLogitsGrad>(end);
18951 + const auto end = fbb_.EndTable(start_);
18952 + auto o = flatbuffers::Offset<Sin>(end);
19031 + const auto end = fbb_.EndTable(start_);
19032 + auto o = flatbuffers::Offset<SkipGram>(end);
19094 + const auto end = fbb_.EndTable(start_);
19095 + auto o = flatbuffers::Offset<SliceFusion>(end);
19111 + auto axes__ = axes ? _fbb.CreateVector<int64_t>(*axes) : 0;
19161 + const auto end = fbb_.EndTable(start_);
19162 + auto o = flatbuffers::Offset<SmoothL1Loss>(end);
19219 + const auto end = fbb_.EndTable(start_);
19220 + auto o = flatbuffers::Offset<SmoothL1LossGrad>(end);
19278 + const auto end = fbb_.EndTable(start_);
19279 + auto o = flatbuffers::Offset<Softmax>(end);
19295 + auto axis__ = axis ? _fbb.CreateVector<int64_t>(*axis) : 0;
19331 + const auto end = fbb_.EndTable(start_);
19332 + auto o = flatbuffers::Offset<SoftmaxCrossEntropyWithLogits>(end);
19401 + const auto end = fbb_.EndTable(start_);
19402 + auto o = flatbuffers::Offset<SpaceToBatch>(end);
19421 + auto block_size__ = block_size ? _fbb.CreateVector<int64_t>(*block_size) : 0;
19486 + const auto end = fbb_.EndTable(start_);
19487 + auto o = flatbuffers::Offset<SpaceToBatchND>(end);
19506 + auto block_shape__ = block_shape ? _fbb.CreateVector<int64_t>(*block_shape) : 0;
19569 + const auto end = fbb_.EndTable(start_);
19570 + auto o = flatbuffers::Offset<SpaceToDepth>(end);
19629 + const auto end = fbb_.EndTable(start_);
19630 + auto o = flatbuffers::Offset<SparseSoftmaxCrossEntropyWithLogits>(end);
19673 + const auto end = fbb_.EndTable(start_);
19674 + auto o = flatbuffers::Offset<SparseToDense>(end);
19754 + const auto end = fbb_.EndTable(start_);
19755 + auto o = flatbuffers::Offset<Split>(end);
19777 + auto size_splits__ = size_splits ? _fbb.CreateVector<int64_t>(*size_splits) : 0;
19815 + const auto end = fbb_.EndTable(start_);
19816 + auto o = flatbuffers::Offset<Sqrt>(end);
19872 + const auto end = fbb_.EndTable(start_);
19873 + auto o = flatbuffers::Offset<Squeeze>(end);
19889 + auto axis__ = axis ? _fbb.CreateVector<int64_t>(*axis) : 0;
19925 + const auto end = fbb_.EndTable(start_);
19926 + auto o = flatbuffers::Offset<Square>(end);
19967 + const auto end = fbb_.EndTable(start_);
19968 + auto o = flatbuffers::Offset<SquaredDifference>(end);
20023 + const auto end = fbb_.EndTable(start_);
20024 + auto o = flatbuffers::Offset<Stack>(end);
20129 + const auto end = fbb_.EndTable(start_);
20130 + auto o = flatbuffers::Offset<StridedSlice>(end);
20195 + const auto end = fbb_.EndTable(start_);
20196 + auto o = flatbuffers::Offset<SubFusion>(end);
20239 + const auto end = fbb_.EndTable(start_);
20240 + auto o = flatbuffers::Offset<SubGrad>(end);
20281 + const auto end = fbb_.EndTable(start_);
20282 + auto o = flatbuffers::Offset<Switch>(end);
20349 + const auto end = fbb_.EndTable(start_);
20350 + auto o = flatbuffers::Offset<TensorListFromTensor>(end);
20409 + const auto end = fbb_.EndTable(start_);
20410 + auto o = flatbuffers::Offset<TensorListGetItem>(end);
20479 + const auto end = fbb_.EndTable(start_);
20480 + auto o = flatbuffers::Offset<TensorListReserve>(end);
20539 + const auto end = fbb_.EndTable(start_);
20540 + auto o = flatbuffers::Offset<TensorListSetItem>(end);
20609 + const auto end = fbb_.EndTable(start_);
20610 + auto o = flatbuffers::Offset<TensorListStack>(end);
20670 + const auto end = fbb_.EndTable(start_);
20671 + auto o = flatbuffers::Offset<TileFusion>(end);
20687 + auto dims__ = dims ? _fbb.CreateVector<int64_t>(*dims) : 0;
20761 + const auto end = fbb_.EndTable(start_);
20762 + auto o = flatbuffers::Offset<TopKFusion>(end);
20809 + const auto end = fbb_.EndTable(start_);
20810 + auto o = flatbuffers::Offset<Transpose>(end);
20851 + const auto end = fbb_.EndTable(start_);
20852 + auto o = flatbuffers::Offset<Unique>(end);
20893 + const auto end = fbb_.EndTable(start_);
20894 + auto o = flatbuffers::Offset<UnsortedSegmentSum>(end);
20950 + const auto end = fbb_.EndTable(start_);
20951 + auto o = flatbuffers::Offset<Unsqueeze>(end);
20967 + auto axis__ = axis ? _fbb.CreateVector<int64_t>(*axis) : 0;
21017 + const auto end = fbb_.EndTable(start_);
21018 + auto o = flatbuffers::Offset<Unstack>(end);
21061 + const auto end = fbb_.EndTable(start_);
21062 + auto o = flatbuffers::Offset<Where>(end);
21103 + const auto end = fbb_.EndTable(start_);
21104 + auto o = flatbuffers::Offset<ZerosLike>(end);
21145 + const auto end = fbb_.EndTable(start_);
21146 + auto o = flatbuffers::Offset<Select>(end);
21201 + const auto end = fbb_.EndTable(start_);
21202 + auto o = flatbuffers::Offset<GRU>(end);
21245 + const auto end = fbb_.EndTable(start_);
21246 + auto o = flatbuffers::Offset<NonZero>(end);
21287 + const auto end = fbb_.EndTable(start_);
21288 + auto o = flatbuffers::Offset<InvertPermutation>(end);
21329 + const auto end = fbb_.EndTable(start_);
21330 + auto o = flatbuffers::Offset<Size>(end);
21397 + const auto end = fbb_.EndTable(start_);
21398 + auto o = flatbuffers::Offset<RandomStandardNormal>(end);
21469 + const auto end = fbb_.EndTable(start_);
21470 + auto o = flatbuffers::Offset<CropAndResize>(end);
21515 + const auto end = fbb_.EndTable(start_);
21516 + auto o = flatbuffers::Offset<Erf>(end);
21619 + const auto end = fbb_.EndTable(start_);
21620 + auto o = flatbuffers::Offset<StridedSliceGrad>(end);
21671 + const auto end = fbb_.EndTable(start_);
21672 + auto o = flatbuffers::Offset<IsFinite>(end);
21713 + const auto end = fbb_.EndTable(start_);
21714 + auto o = flatbuffers::Offset<LinSpace>(end);
21781 + const auto end = fbb_.EndTable(start_);
21782 + auto o = flatbuffers::Offset<UniformReal>(end);
21827 + const auto end = fbb_.EndTable(start_);
21828 + auto o = flatbuffers::Offset<AbsGrad>(end);
21869 + const auto end = fbb_.EndTable(start_);
21870 + auto o = flatbuffers::Offset<RsqrtGrad>(end);
21911 + const auto end = fbb_.EndTable(start_);
21912 + auto o = flatbuffers::Offset<SqrtGrad>(end);
21979 + const auto end = fbb_.EndTable(start_);
21980 + auto o = flatbuffers::Offset<LayerNormGrad>(end);
22051 + const auto end = fbb_.EndTable(start_);
22052 + auto o = flatbuffers::Offset<ResizeGrad>(end);
22137 + const auto end = fbb_.EndTable(start_);
22138 + auto o = flatbuffers::Offset<Splice>(end);
22160 + auto context__ = context ? _fbb.CreateVector<int64_t>(*context) : 0;
22161 + auto forward_indexes__ = forward_indexes ? _fbb.CreateVector<int64_t>(*forward_indexes) : 0;
22213 + const auto end = fbb_.EndTable(start_);
22214 + auto o = flatbuffers::Offset<LogSoftmax>(end);
22271 + const auto end = fbb_.EndTable(start_);
22272 + auto o = flatbuffers::Offset<Call>(end);
22341 + const auto end = fbb_.EndTable(start_);
22342 + auto o = flatbuffers::Offset<CumSum>(end);
22416 + const auto end = fbb_.EndTable(start_);
22417 + auto o = flatbuffers::Offset<Custom>(end);
22436 + auto type__ = type ? _fbb.CreateString(type) : 0;
22437 + auto attr__ = attr ? _fbb.CreateVector<flatbuffers::Offset<mindspore::schema::Attribute>>(*attr)…
22539 + const auto end = fbb_.EndTable(start_);
22540 + auto o = flatbuffers::Offset<SplitWithOverlap>(end);
22568 + auto ratio__ = ratio ? _fbb.CreateVector<int64_t>(*ratio) : 0;
22569 + auto extend_top__ = extend_top ? _fbb.CreateVector<int64_t>(*extend_top) : 0;
22570 + auto extend_bottom__ = extend_bottom ? _fbb.CreateVector<int64_t>(*extend_bottom) : 0;
23002 + const auto end = fbb_.EndTable(start_);
23003 + auto o = flatbuffers::Offset<GenOP>(end);
23112 + auto kernel_size__ = kernel_size ? _fbb.CreateVector<int64_t>(*kernel_size) : 0;
23113 + auto stride__ = stride ? _fbb.CreateVector<int64_t>(*stride) : 0;
23114 + auto dilation__ = dilation ? _fbb.CreateVector<int64_t>(*dilation) : 0;
23115 + auto pad_list__ = pad_list ? _fbb.CreateVector<int64_t>(*pad_list) : 0;
23116 + auto pad__ = pad ? _fbb.CreateVector<int64_t>(*pad) : 0;
23117 + auto axes__ = axes ? _fbb.CreateVector<int64_t>(*axes) : 0;
23184 + const auto end = fbb_.EndTable(start_);
23185 + auto o = flatbuffers::Offset<RaggedRange>(end);
23240 + const auto end = fbb_.EndTable(start_);
23241 + auto o = flatbuffers::Offset<GLU>(end);
23335 + const auto end = fbb_.EndTable(start_);
23336 + auto o = flatbuffers::Offset<TensorArray>(end);
23361 + auto element_shape__ = element_shape ? _fbb.CreateVector<int32_t>(*element_shape) : 0;
23400 + const auto end = fbb_.EndTable(start_);
23401 + auto o = flatbuffers::Offset<TensorArrayRead>(end);
23442 + const auto end = fbb_.EndTable(start_);
23443 + auto o = flatbuffers::Offset<TensorArrayWrite>(end);
23547 + const auto end = fbb_.EndTable(start_);
23548 + auto o = flatbuffers::Offset<Affine>(end);
23576 + auto context__ = context ? _fbb.CreateVector<int64_t>(*context) : 0;
23616 + const auto end = fbb_.EndTable(start_);
23617 + auto o = flatbuffers::Offset<ScatterNdUpdate>(end);
23685 + const auto end = fbb_.EndTable(start_);
23686 + auto o = flatbuffers::Offset<AllGather>(end);
23705 + auto group__ = group ? _fbb.CreateString(group) : 0;
23781 + const auto end = fbb_.EndTable(start_);
23782 + auto o = flatbuffers::Offset<ReduceScatter>(end);
23804 + auto group__ = group ? _fbb.CreateString(group) : 0;
23868 + const auto end = fbb_.EndTable(start_);
23869 + auto o = flatbuffers::Offset<DynamicQuant>(end);
24024 + const auto end = fbb_.EndTable(start_);
24025 + auto o = flatbuffers::Offset<LSTMGradData>(end);
24194 + const auto end = fbb_.EndTable(start_);
24195 + auto o = flatbuffers::Offset<LSTMGradWeight>(end);
24292 + const auto end = fbb_.EndTable(start_);
24293 + auto o = flatbuffers::Offset<RandomNormal>(end);
24354 + const auto end = fbb_.EndTable(start_);
24355 + auto o = flatbuffers::Offset<NLLLoss>(end);
24412 + const auto end = fbb_.EndTable(start_);
24413 + auto o = flatbuffers::Offset<NLLLossGrad>(end);
24482 + const auto end = fbb_.EndTable(start_);
24483 + auto o = flatbuffers::Offset<FormatTranspose>(end);
24528 + const auto end = fbb_.EndTable(start_);
24529 + auto o = flatbuffers::Offset<GatherD>(end);
24608 + const auto end = fbb_.EndTable(start_);
24609 + auto o = flatbuffers::Offset<GroupNormFusion>(end);
24629 + auto _o = std::unique_ptr<AbsT>(new AbsT());
24652 + auto _o = std::unique_ptr<ActivationT>(new ActivationT());
24660 + { auto _e = activation_type(); _o->activation_type = _e; }
24661 + { auto _e = alpha(); _o->alpha = _e; }
24662 + { auto _e = min_val(); _o->min_val = _e; }
24663 + { auto _e = max_val(); _o->max_val = _e; }
24664 + { auto _e = approximate(); _o->approximate = _e; }
24675 + auto _activation_type = _o->activation_type;
24676 + auto _alpha = _o->alpha;
24677 + auto _min_val = _o->min_val;
24678 + auto _max_val = _o->max_val;
24679 + auto _approximate = _o->approximate;
24690 + auto _o = std::unique_ptr<ActivationGradT>(new ActivationGradT());
24698 + { auto _e = activation_type(); _o->activation_type = _e; }
24699 + { auto _e = alpha(); _o->alpha = _e; }
24710 + auto _activation_type = _o->activation_type;
24711 + auto _alpha = _o->alpha;
24719 + auto _o = std::unique_ptr<AdamT>(new AdamT());
24727 + { auto _e = use_locking(); _o->use_locking = _e; }
24728 + { auto _e = use_nesterov(); _o->use_nesterov = _e; }
24739 + auto _use_locking = _o->use_locking;
24740 + auto _use_nesterov = _o->use_nesterov;
24748 + auto _o = std::unique_ptr<AddFusionT>(new AddFusionT());
24756 + { auto _e = activation_type(); _o->activation_type = _e; }
24767 + auto _activation_type = _o->activation_type;
24774 + auto _o = std::unique_ptr<AdderFusionT>(new AdderFusionT());
24782 + { auto _e = format(); _o->format = _e; }
24783 + { auto _e = kernel_size(); if (_e) { _o->kernel_size.resize(_e->size()); for (flatbuffers::uoffs…
24784 + { auto _e = stride(); if (_e) { _o->stride.resize(_e->size()); for (flatbuffers::uoffset_t _i = …
24785 + { auto _e = dilation(); if (_e) { _o->dilation.resize(_e->size()); for (flatbuffers::uoffset_t _…
24786 + { auto _e = pad_mode(); _o->pad_mode = _e; }
24787 + { auto _e = pad_list(); if (_e) { _o->pad_list.resize(_e->size()); for (flatbuffers::uoffset_t _…
24788 + { auto _e = group(); _o->group = _e; }
24789 + { auto _e = in_channel(); _o->in_channel = _e; }
24790 + { auto _e = out_channel(); _o->out_channel = _e; }
24791 + { auto _e = activation_type(); _o->activation_type = _e; }
24802 + auto _format = _o->format;
24803 + auto _kernel_size = _o->kernel_size.size() ? _fbb.CreateVector(_o->kernel_size) : 0;
24804 + auto _stride = _o->stride.size() ? _fbb.CreateVector(_o->stride) : 0;
24805 + auto _dilation = _o->dilation.size() ? _fbb.CreateVector(_o->dilation) : 0;
24806 + auto _pad_mode = _o->pad_mode;
24807 + auto _pad_list = _o->pad_list.size() ? _fbb.CreateVector(_o->pad_list) : 0;
24808 + auto _group = _o->group;
24809 + auto _in_channel = _o->in_channel;
24810 + auto _out_channel = _o->out_channel;
24811 + auto _activation_type = _o->activation_type;
24827 + auto _o = std::unique_ptr<AddGradT>(new AddGradT());
24850 + auto _o = std::unique_ptr<AddNT>(new AddNT());
24873 + auto _o = std::unique_ptr<AllT>(new AllT());
24881 + { auto _e = keep_dims(); _o->keep_dims = _e; }
24892 + auto _keep_dims = _o->keep_dims;
24899 + auto _o = std::unique_ptr<ApplyMomentumT>(new ApplyMomentumT());
24907 + { auto _e = use_nesterov(); _o->use_nesterov = _e; }
24908 + { auto _e = use_locking(); _o->use_locking = _e; }
24909 + { auto _e = gradient_scale(); _o->gradient_scale = _e; }
24920 + auto _use_nesterov = _o->use_nesterov;
24921 + auto _use_locking = _o->use_locking;
24922 + auto _gradient_scale = _o->gradient_scale;
24931 + auto _o = std::unique_ptr<ArgMaxFusionT>(new ArgMaxFusionT());
24939 + { auto _e = axis(); _o->axis = _e; }
24940 + { auto _e = top_k(); _o->top_k = _e; }
24941 + { auto _e = keep_dims(); _o->keep_dims = _e; }
24942 + { auto _e = out_max_value(); _o->out_max_value = _e; }
24953 + auto _axis = _o->axis;
24954 + auto _top_k = _o->top_k;
24955 + auto _keep_dims = _o->keep_dims;
24956 + auto _out_max_value = _o->out_max_value;
24966 + auto _o = std::unique_ptr<ArgMinFusionT>(new ArgMinFusionT());
24974 + { auto _e = axis(); _o->axis = _e; }
24975 + { auto _e = top_k(); _o->top_k = _e; }
24976 + { auto _e = keep_dims(); _o->keep_dims = _e; }
24977 + { auto _e = out_max_value(); _o->out_max_value = _e; }
24988 + auto _axis = _o->axis;
24989 + auto _top_k = _o->top_k;
24990 + auto _keep_dims = _o->keep_dims;
24991 + auto _out_max_value = _o->out_max_value;
25001 + auto _o = std::unique_ptr<AssertT>(new AssertT());
25009 + { auto _e = summarize(); _o->summarize = _e; }
25020 + auto _summarize = _o->summarize;
25027 + auto _o = std::unique_ptr<AssignT>(new AssignT());
25050 + auto _o = std::unique_ptr<AssignAddT>(new AssignAddT());
25073 + auto _o = std::unique_ptr<AudioSpectrogramT>(new AudioSpectrogramT());
25081 + { auto _e = window_size(); _o->window_size = _e; }
25082 + { auto _e = stride(); _o->stride = _e; }
25083 + { auto _e = mag_square(); _o->mag_square = _e; }
25094 + auto _window_size = _o->window_size;
25095 + auto _stride = _o->stride;
25096 + auto _mag_square = _o->mag_square;
25105 + auto _o = std::unique_ptr<AvgPoolFusionT>(new AvgPoolFusionT());
25113 + { auto _e = kernel_size(); if (_e) { _o->kernel_size.resize(_e->size()); for (flatbuffers::uoffs…
25114 + { auto _e = strides(); if (_e) { _o->strides.resize(_e->size()); for (flatbuffers::uoffset_t _i …
25115 + { auto _e = pad(); if (_e) { _o->pad.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _i …
25116 + { auto _e = pad_mode(); _o->pad_mode = _e; }
25117 + { auto _e = round_mode(); _o->round_mode = _e; }
25118 + { auto _e = format(); _o->format = _e; }
25119 + { auto _e = global(); _o->global = _e; }
25120 + { auto _e = activation_type(); _o->activation_type = _e; }
25131 + auto _kernel_size = _o->kernel_size.size() ? _fbb.CreateVector(_o->kernel_size) : 0;
25132 + auto _strides = _o->strides.size() ? _fbb.CreateVector(_o->strides) : 0;
25133 + auto _pad = _o->pad.size() ? _fbb.CreateVector(_o->pad) : 0;
25134 + auto _pad_mode = _o->pad_mode;
25135 + auto _round_mode = _o->round_mode;
25136 + auto _format = _o->format;
25137 + auto _global = _o->global;
25138 + auto _activation_type = _o->activation_type;
25152 + auto _o = std::unique_ptr<AvgPoolGradT>(new AvgPoolGradT());
25160 + { auto _e = kernel_size(); if (_e) { _o->kernel_size.resize(_e->size()); for (flatbuffers::uoffs…
25161 + { auto _e = strides(); if (_e) { _o->strides.resize(_e->size()); for (flatbuffers::uoffset_t _i …
25162 + { auto _e = pad_mode(); _o->pad_mode = _e; }
25163 + { auto _e = format(); _o->format = _e; }
25174 + auto _kernel_size = _o->kernel_size.size() ? _fbb.CreateVector(_o->kernel_size) : 0;
25175 + auto _strides = _o->strides.size() ? _fbb.CreateVector(_o->strides) : 0;
25176 + auto _pad_mode = _o->pad_mode;
25177 + auto _format = _o->format;
25187 + auto _o = std::unique_ptr<BatchNormT>(new BatchNormT());
25195 + { auto _e = epsilon(); _o->epsilon = _e; }
25196 + { auto _e = format(); _o->format = _e; }
25197 + { auto _e = is_training(); _o->is_training = _e; }
25208 + auto _epsilon = _o->epsilon;
25209 + auto _format = _o->format;
25210 + auto _is_training = _o->is_training;
25219 + auto _o = std::unique_ptr<BatchNormGradT>(new BatchNormGradT());
25227 + { auto _e = epsilon(); _o->epsilon = _e; }
25228 + { auto _e = is_training(); _o->is_training = _e; }
25239 + auto _epsilon = _o->epsilon;
25240 + auto _is_training = _o->is_training;
25248 + auto _o = std::unique_ptr<BatchToSpaceT>(new BatchToSpaceT());
25256 + { auto _e = block_size(); if (_e) { _o->block_size.resize(_e->size()); for (flatbuffers::uoffset…
25257 + { auto _e = crops(); if (_e) _o->crops = std::unique_ptr<mindspore::schema::Vec2DT>(_e->UnPack(_…
25268 + auto _block_size = _o->block_size.size() ? _fbb.CreateVector(_o->block_size) : 0;
25269 + auto _crops = _o->crops ? CreateVec2D(_fbb, _o->crops.get(), _rehasher) : 0;
25277 + auto _o = std::unique_ptr<BatchToSpaceNDT>(new BatchToSpaceNDT());
25285 + { auto _e = block_shape(); if (_e) { _o->block_shape.resize(_e->size()); for (flatbuffers::uoffs…
25286 + { auto _e = crops(); if (_e) _o->crops = std::unique_ptr<mindspore::schema::Vec2DT>(_e->UnPack(_…
25297 + auto _block_shape = _o->block_shape.size() ? _fbb.CreateVector(_o->block_shape) : 0;
25298 + auto _crops = _o->crops ? CreateVec2D(_fbb, _o->crops.get(), _rehasher) : 0;
25306 + auto _o = std::unique_ptr<BiasAddT>(new BiasAddT());
25314 + { auto _e = format(); _o->format = _e; }
25325 + auto _format = _o->format;
25332 + auto _o = std::unique_ptr<BinaryCrossEntropyT>(new BinaryCrossEntropyT());
25340 + { auto _e = reduction(); _o->reduction = _e; }
25351 + auto _reduction = _o->reduction;
25358 + auto _o = std::unique_ptr<BinaryCrossEntropyGradT>(new BinaryCrossEntropyGradT());
25366 + { auto _e = reduction(); _o->reduction = _e; }
25377 + auto _reduction = _o->reduction;
25384 + auto _o = std::unique_ptr<BiasAddGradT>(new BiasAddGradT());
25407 + auto _o = std::unique_ptr<BroadcastToT>(new BroadcastToT());
25415 + { auto _e = shape(); if (_e) { _o->shape.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0;…
25426 + auto _shape = _o->shape.size() ? _fbb.CreateVector(_o->shape) : 0;
25433 + auto _o = std::unique_ptr<CastT>(new CastT());
25456 + auto _o = std::unique_ptr<CeilT>(new CeilT());
25479 + auto _o = std::unique_ptr<ClipT>(new ClipT());
25487 + { auto _e = max(); _o->max = _e; }
25488 + { auto _e = min(); _o->min = _e; }
25499 + auto _max = _o->max;
25500 + auto _min = _o->min;
25508 + auto _o = std::unique_ptr<ConcatT>(new ConcatT());
25516 + { auto _e = axis(); _o->axis = _e; }
25527 + auto _axis = _o->axis;
25534 + auto _o = std::unique_ptr<AttentionT>(new AttentionT());
25557 + auto _o = std::unique_ptr<Conv2DBackpropFilterFusionT>(new Conv2DBackpropFilterFusionT());
25565 + { auto _e = format(); _o->format = _e; }
25566 + { auto _e = kernel_size(); if (_e) { _o->kernel_size.resize(_e->size()); for (flatbuffers::uoffs…
25567 + { auto _e = stride(); if (_e) { _o->stride.resize(_e->size()); for (flatbuffers::uoffset_t _i = …
25568 + { auto _e = dilation(); if (_e) { _o->dilation.resize(_e->size()); for (flatbuffers::uoffset_t _…
25569 + { auto _e = pad_mode(); _o->pad_mode = _e; }
25570 + { auto _e = pad_list(); if (_e) { _o->pad_list.resize(_e->size()); for (flatbuffers::uoffset_t _…
25571 + { auto _e = mode(); _o->mode = _e; }
25572 + { auto _e = group(); _o->group = _e; }
25573 + { auto _e = in_channel(); _o->in_channel = _e; }
25574 + { auto _e = out_channel(); _o->out_channel = _e; }
25575 + { auto _e = activation_type(); _o->activation_type = _e; }
25586 + auto _format = _o->format;
25587 + auto _kernel_size = _o->kernel_size.size() ? _fbb.CreateVector(_o->kernel_size) : 0;
25588 + auto _stride = _o->stride.size() ? _fbb.CreateVector(_o->stride) : 0;
25589 + auto _dilation = _o->dilation.size() ? _fbb.CreateVector(_o->dilation) : 0;
25590 + auto _pad_mode = _o->pad_mode;
25591 + auto _pad_list = _o->pad_list.size() ? _fbb.CreateVector(_o->pad_list) : 0;
25592 + auto _mode = _o->mode;
25593 + auto _group = _o->group;
25594 + auto _in_channel = _o->in_channel;
25595 + auto _out_channel = _o->out_channel;
25596 + auto _activation_type = _o->activation_type;
25613 + auto _o = std::unique_ptr<Conv2DBackpropInputFusionT>(new Conv2DBackpropInputFusionT());
25621 + { auto _e = format(); _o->format = _e; }
25622 + { auto _e = kernel_size(); if (_e) { _o->kernel_size.resize(_e->size()); for (flatbuffers::uoffs…
25623 + { auto _e = stride(); if (_e) { _o->stride.resize(_e->size()); for (flatbuffers::uoffset_t _i = …
25624 + { auto _e = dilation(); if (_e) { _o->dilation.resize(_e->size()); for (flatbuffers::uoffset_t _…
25625 + { auto _e = pad_mode(); _o->pad_mode = _e; }
25626 + { auto _e = pad(); if (_e) { _o->pad.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _i …
25627 + { auto _e = pad_list(); if (_e) { _o->pad_list.resize(_e->size()); for (flatbuffers::uoffset_t _…
25628 + { auto _e = mode(); _o->mode = _e; }
25629 + { auto _e = group(); _o->group = _e; }
25630 + { auto _e = in_channel(); _o->in_channel = _e; }
25631 + { auto _e = out_channel(); _o->out_channel = _e; }
25632 + { auto _e = activation_type(); _o->activation_type = _e; }
25643 + auto _format = _o->format;
25644 + auto _kernel_size = _o->kernel_size.size() ? _fbb.CreateVector(_o->kernel_size) : 0;
25645 + auto _stride = _o->stride.size() ? _fbb.CreateVector(_o->stride) : 0;
25646 + auto _dilation = _o->dilation.size() ? _fbb.CreateVector(_o->dilation) : 0;
25647 + auto _pad_mode = _o->pad_mode;
25648 + auto _pad = _o->pad.size() ? _fbb.CreateVector(_o->pad) : 0;
25649 + auto _pad_list = _o->pad_list.size() ? _fbb.CreateVector(_o->pad_list) : 0;
25650 + auto _mode = _o->mode;
25651 + auto _group = _o->group;
25652 + auto _in_channel = _o->in_channel;
25653 + auto _out_channel = _o->out_channel;
25654 + auto _activation_type = _o->activation_type;
25672 + auto _o = std::unique_ptr<Conv2DFusionT>(new Conv2DFusionT());
25680 + { auto _e = format(); _o->format = _e; }
25681 + { auto _e = kernel_size(); if (_e) { _o->kernel_size.resize(_e->size()); for (flatbuffers::uoffs…
25682 + { auto _e = stride(); if (_e) { _o->stride.resize(_e->size()); for (flatbuffers::uoffset_t _i = …
25683 + { auto _e = dilation(); if (_e) { _o->dilation.resize(_e->size()); for (flatbuffers::uoffset_t _…
25684 + { auto _e = pad_mode(); _o->pad_mode = _e; }
25685 + { auto _e = pad_list(); if (_e) { _o->pad_list.resize(_e->size()); for (flatbuffers::uoffset_t _…
25686 + { auto _e = mode(); _o->mode = _e; }
25687 + { auto _e = group(); _o->group = _e; }
25688 + { auto _e = in_channel(); _o->in_channel = _e; }
25689 + { auto _e = out_channel(); _o->out_channel = _e; }
25690 + { auto _e = activation_type(); _o->activation_type = _e; }
25701 + auto _format = _o->format;
25702 + auto _kernel_size = _o->kernel_size.size() ? _fbb.CreateVector(_o->kernel_size) : 0;
25703 + auto _stride = _o->stride.size() ? _fbb.CreateVector(_o->stride) : 0;
25704 + auto _dilation = _o->dilation.size() ? _fbb.CreateVector(_o->dilation) : 0;
25705 + auto _pad_mode = _o->pad_mode;
25706 + auto _pad_list = _o->pad_list.size() ? _fbb.CreateVector(_o->pad_list) : 0;
25707 + auto _mode = _o->mode;
25708 + auto _group = _o->group;
25709 + auto _in_channel = _o->in_channel;
25710 + auto _out_channel = _o->out_channel;
25711 + auto _activation_type = _o->activation_type;
25728 + auto _o = std::unique_ptr<Conv2dTransposeFusionT>(new Conv2dTransposeFusionT());
25736 + { auto _e = format(); _o->format = _e; }
25737 + { auto _e = kernel_size(); if (_e) { _o->kernel_size.resize(_e->size()); for (flatbuffers::uoffs…
25738 + { auto _e = stride(); if (_e) { _o->stride.resize(_e->size()); for (flatbuffers::uoffset_t _i = …
25739 + { auto _e = dilation(); if (_e) { _o->dilation.resize(_e->size()); for (flatbuffers::uoffset_t _…
25740 + { auto _e = pad_mode(); _o->pad_mode = _e; }
25741 + { auto _e = pad(); if (_e) { _o->pad.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _i …
25742 + { auto _e = pad_list(); if (_e) { _o->pad_list.resize(_e->size()); for (flatbuffers::uoffset_t _…
25743 + { auto _e = mode(); _o->mode = _e; }
25744 + { auto _e = group(); _o->group = _e; }
25745 + { auto _e = in_channel(); _o->in_channel = _e; }
25746 + { auto _e = out_channel(); _o->out_channel = _e; }
25747 + { auto _e = activation_type(); _o->activation_type = _e; }
25748 + { auto _e = output_paddings(); if (_e) { _o->output_paddings.resize(_e->size()); for (flatbuffer…
25759 + auto _format = _o->format;
25760 + auto _kernel_size = _o->kernel_size.size() ? _fbb.CreateVector(_o->kernel_size) : 0;
25761 + auto _stride = _o->stride.size() ? _fbb.CreateVector(_o->stride) : 0;
25762 + auto _dilation = _o->dilation.size() ? _fbb.CreateVector(_o->dilation) : 0;
25763 + auto _pad_mode = _o->pad_mode;
25764 + auto _pad = _o->pad.size() ? _fbb.CreateVector(_o->pad) : 0;
25765 + auto _pad_list = _o->pad_list.size() ? _fbb.CreateVector(_o->pad_list) : 0;
25766 + auto _mode = _o->mode;
25767 + auto _group = _o->group;
25768 + auto _in_channel = _o->in_channel;
25769 + auto _out_channel = _o->out_channel;
25770 + auto _activation_type = _o->activation_type;
25771 + auto _output_paddings = _o->output_paddings.size() ? _fbb.CreateVector(_o->output_paddings) : 0;
25790 + auto _o = std::unique_ptr<CosT>(new CosT());
25813 + auto _o = std::unique_ptr<ConstantOfShapeT>(new ConstantOfShapeT());
25821 + { auto _e = data_type(); _o->data_type = _e; }
25822 + { auto _e = value(); if (_e) { _o->value.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0;…
25833 + auto _data_type = _o->data_type;
25834 + auto _value = _o->value.size() ? _fbb.CreateVector(_o->value) : 0;
25842 + auto _o = std::unique_ptr<CropT>(new CropT());
25850 + { auto _e = axis(); _o->axis = _e; }
25851 + { auto _e = offsets(); if (_e) { _o->offsets.resize(_e->size()); for (flatbuffers::uoffset_t _i …
25862 + auto _axis = _o->axis;
25863 + auto _offsets = _o->offsets.size() ? _fbb.CreateVector(_o->offsets) : 0;
25871 + auto _o = std::unique_ptr<CustomExtractFeaturesT>(new CustomExtractFeaturesT());
25894 + auto _o = std::unique_ptr<CustomNormalizeT>(new CustomNormalizeT());
25917 + auto _o = std::unique_ptr<CustomPredictT>(new CustomPredictT());
25925 + { auto _e = output_num(); _o->output_num = _e; }
25926 + { auto _e = weight_threshold(); _o->weight_threshold = _e; }
25937 + auto _output_num = _o->output_num;
25938 + auto _weight_threshold = _o->weight_threshold;
25946 + auto _o = std::unique_ptr<DeConv2DGradFilterT>(new DeConv2DGradFilterT());
25954 + { auto _e = in_channel(); _o->in_channel = _e; }
25955 + { auto _e = out_channel(); _o->out_channel = _e; }
25956 + { auto _e = kernel_size(); if (_e) { _o->kernel_size.resize(_e->size()); for (flatbuffers::uoffs…
25957 + { auto _e = pad_mode(); _o->pad_mode = _e; }
25958 + { auto _e = pad_list(); if (_e) { _o->pad_list.resize(_e->size()); for (flatbuffers::uoffset_t _…
25959 + { auto _e = stride(); if (_e) { _o->stride.resize(_e->size()); for (flatbuffers::uoffset_t _i = …
25960 + { auto _e = dilation(); if (_e) { _o->dilation.resize(_e->size()); for (flatbuffers::uoffset_t _…
25961 + { auto _e = group(); _o->group = _e; }
25962 + { auto _e = format(); _o->format = _e; }
25963 + { auto _e = activation_type(); _o->activation_type = _e; }
25974 + auto _in_channel = _o->in_channel;
25975 + auto _out_channel = _o->out_channel;
25976 + auto _kernel_size = _o->kernel_size.size() ? _fbb.CreateVector(_o->kernel_size) : 0;
25977 + auto _pad_mode = _o->pad_mode;
25978 + auto _pad_list = _o->pad_list.size() ? _fbb.CreateVector(_o->pad_list) : 0;
25979 + auto _stride = _o->stride.size() ? _fbb.CreateVector(_o->stride) : 0;
25980 + auto _dilation = _o->dilation.size() ? _fbb.CreateVector(_o->dilation) : 0;
25981 + auto _group = _o->group;
25982 + auto _format = _o->format;
25983 + auto _activation_type = _o->activation_type;
25999 + auto _o = std::unique_ptr<DependT>(new DependT());
26022 + auto _o = std::unique_ptr<DepthToSpaceT>(new DepthToSpaceT());
26030 + { auto _e = block_size(); _o->block_size = _e; }
26031 + { auto _e = format(); _o->format = _e; }
26042 + auto _block_size = _o->block_size;
26043 + auto _format = _o->format;
26051 + auto _o = std::unique_ptr<DetectionPostProcessT>(new DetectionPostProcessT());
26059 + { auto _e = format(); _o->format = _e; }
26060 + { auto _e = input_size(); _o->input_size = _e; }
26061 + { auto _e = scale(); if (_e) { _o->scale.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0;…
26062 + { auto _e = nms_iou_threshold(); _o->nms_iou_threshold = _e; }
26063 + { auto _e = nms_score_threshold(); _o->nms_score_threshold = _e; }
26064 + { auto _e = max_detections(); _o->max_detections = _e; }
26065 + { auto _e = detections_per_class(); _o->detections_per_class = _e; }
26066 + { auto _e = max_classes_per_detection(); _o->max_classes_per_detection = _e; }
26067 + { auto _e = num_classes(); _o->num_classes = _e; }
26068 + { auto _e = use_regular_nms(); _o->use_regular_nms = _e; }
26069 + { auto _e = out_quantized(); _o->out_quantized = _e; }
26080 + auto _format = _o->format;
26081 + auto _input_size = _o->input_size;
26082 + auto _scale = _o->scale.size() ? _fbb.CreateVector(_o->scale) : 0;
26083 + auto _nms_iou_threshold = _o->nms_iou_threshold;
26084 + auto _nms_score_threshold = _o->nms_score_threshold;
26085 + auto _max_detections = _o->max_detections;
26086 + auto _detections_per_class = _o->detections_per_class;
26087 + auto _max_classes_per_detection = _o->max_classes_per_detection;
26088 + auto _num_classes = _o->num_classes;
26089 + auto _use_regular_nms = _o->use_regular_nms;
26090 + auto _out_quantized = _o->out_quantized;
26107 + auto _o = std::unique_ptr<DivFusionT>(new DivFusionT());
26115 + { auto _e = activation_type(); _o->activation_type = _e; }
26126 + auto _activation_type = _o->activation_type;
26133 + auto _o = std::unique_ptr<DivGradT>(new DivGradT());
26156 + auto _o = std::unique_ptr<DropoutT>(new DropoutT());
26164 + { auto _e = keep_prob(); _o->keep_prob = _e; }
26175 + auto _keep_prob = _o->keep_prob;
26182 + auto _o = std::unique_ptr<DropoutGradT>(new DropoutGradT());
26190 + { auto _e = keep_prob(); _o->keep_prob = _e; }
26201 + auto _keep_prob = _o->keep_prob;
26208 + auto _o = std::unique_ptr<EluT>(new EluT());
26216 + { auto _e = alpha(); _o->alpha = _e; }
26227 + auto _alpha = _o->alpha;
26234 + auto _o = std::unique_ptr<EltwiseT>(new EltwiseT());
26242 + { auto _e = mode(); _o->mode = _e; }
26253 + auto _mode = _o->mode;
26260 + auto _o = std::unique_ptr<EqualT>(new EqualT());
26283 + auto _o = std::unique_ptr<EmbeddingLookupFusionT>(new EmbeddingLookupFusionT());
26291 + { auto _e = max_norm(); _o->max_norm = _e; }
26302 + auto _max_norm = _o->max_norm;
26309 + auto _o = std::unique_ptr<ExpFusionT>(new ExpFusionT());
26317 + { auto _e = base(); _o->base = _e; }
26318 + { auto _e = scale(); _o->scale = _e; }
26319 + { auto _e = shift(); _o->shift = _e; }
26330 + auto _base = _o->base;
26331 + auto _scale = _o->scale;
26332 + auto _shift = _o->shift;
26341 + auto _o = std::unique_ptr<ExpandDimsT>(new ExpandDimsT());
26364 + auto _o = std::unique_ptr<FakeQuantWithMinMaxVarsT>(new FakeQuantWithMinMaxVarsT());
26372 + { auto _e = num_bits(); _o->num_bits = _e; }
26373 + { auto _e = narrow_range(); _o->narrow_range = _e; }
26384 + auto _num_bits = _o->num_bits;
26385 + auto _narrow_range = _o->narrow_range;
26393 + auto _o = std::unique_ptr<FakeQuantWithMinMaxVarsPerChannelT>(new FakeQuantWithMinMaxVarsPerChan…
26401 + { auto _e = num_bits(); _o->num_bits = _e; }
26402 + { auto _e = narrow_range(); _o->narrow_range = _e; }
26413 + auto _num_bits = _o->num_bits;
26414 + auto _narrow_range = _o->narrow_range;
26422 + auto _o = std::unique_ptr<FftRealT>(new FftRealT());
26445 + auto _o = std::unique_ptr<FftImagT>(new FftImagT());
26468 + auto _o = std::unique_ptr<FlattenT>(new FlattenT());
26476 + { auto _e = axis(); _o->axis = _e; }
26487 + auto _axis = _o->axis;
26494 + auto _o = std::unique_ptr<FlattenGradT>(new FlattenGradT());
26517 + auto _o = std::unique_ptr<FloorT>(new FloorT());
26540 + auto _o = std::unique_ptr<FloorDivT>(new FloorDivT());
26563 + auto _o = std::unique_ptr<FloorModT>(new FloorModT());
26586 + auto _o = std::unique_ptr<FillT>(new FillT());
26609 + auto _o = std::unique_ptr<FullConnectionT>(new FullConnectionT());
26617 + { auto _e = has_bias(); _o->has_bias = _e; }
26618 + { auto _e = use_axis(); _o->use_axis = _e; }
26619 + { auto _e = axis(); _o->axis = _e; }
26620 + { auto _e = activation_type(); _o->activation_type = _e; }
26631 + auto _has_bias = _o->has_bias;
26632 + auto _use_axis = _o->use_axis;
26633 + auto _axis = _o->axis;
26634 + auto _activation_type = _o->activation_type;
26644 + auto _o = std::unique_ptr<FusedBatchNormT>(new FusedBatchNormT());
26652 + { auto _e = epsilon(); _o->epsilon = _e; }
26653 + { auto _e = momentum(); _o->momentum = _e; }
26654 + { auto _e = mode(); _o->mode = _e; }
26665 + auto _epsilon = _o->epsilon;
26666 + auto _momentum = _o->momentum;
26667 + auto _mode = _o->mode;
26676 + auto _o = std::unique_ptr<GatherT>(new GatherT());
26699 + auto _o = std::unique_ptr<GatherNdT>(new GatherNdT());
26722 + auto _o = std::unique_ptr<GreaterT>(new GreaterT());
26745 + auto _o = std::unique_ptr<GreaterEqualT>(new GreaterEqualT());
26768 + auto _o = std::unique_ptr<HashtableLookupT>(new HashtableLookupT());
26791 + auto _o = std::unique_ptr<InstanceNormT>(new InstanceNormT());
26799 + { auto _e = epsilon(); _o->epsilon = _e; }
26810 + auto _epsilon = _o->epsilon;
26817 + auto _o = std::unique_ptr<LayerNormFusionT>(new LayerNormFusionT());
26825 + { auto _e = begin_norm_axis(); _o->begin_norm_axis = _e; }
26826 + { auto _e = epsilon(); _o->epsilon = _e; }
26827 + { auto _e = elementwise_affine(); _o->elementwise_affine = _e; }
26828 + { auto _e = begin_params_axis(); _o->begin_params_axis = _e; }
26839 + auto _begin_norm_axis = _o->begin_norm_axis;
26840 + auto _epsilon = _o->epsilon;
26841 + auto _elementwise_affine = _o->elementwise_affine;
26842 + auto _begin_params_axis = _o->begin_params_axis;
26852 + auto _o = std::unique_ptr<LeakyReluT>(new LeakyReluT());
26860 + { auto _e = negative_slope(); _o->negative_slope = _e; }
26871 + auto _negative_slope = _o->negative_slope;
26878 + auto _o = std::unique_ptr<LessT>(new LessT());
26901 + auto _o = std::unique_ptr<LessEqualT>(new LessEqualT());
26924 + auto _o = std::unique_ptr<LogT>(new LogT());
26947 + auto _o = std::unique_ptr<LogGradT>(new LogGradT());
26970 + auto _o = std::unique_ptr<LogicalAndT>(new LogicalAndT());
26993 + auto _o = std::unique_ptr<LogicalNotT>(new LogicalNotT());
27016 + auto _o = std::unique_ptr<LogicalOrT>(new LogicalOrT());
27039 + auto _o = std::unique_ptr<LpNormalizationT>(new LpNormalizationT());
27047 + { auto _e = axis(); _o->axis = _e; }
27048 + { auto _e = p(); _o->p = _e; }
27059 + auto _axis = _o->axis;
27060 + auto _p = _o->p;
27068 + auto _o = std::unique_ptr<LRNT>(new LRNT());
27076 + { auto _e = depth_radius(); _o->depth_radius = _e; }
27077 + { auto _e = bias(); _o->bias = _e; }
27078 + { auto _e = alpha(); _o->alpha = _e; }
27079 + { auto _e = beta(); _o->beta = _e; }
27080 + { auto _e = norm_region(); if (_e) _o->norm_region = _e->str(); }
27091 + auto _depth_radius = _o->depth_radius;
27092 + auto _bias = _o->bias;
27093 + auto _alpha = _o->alpha;
27094 + auto _beta = _o->beta;
27095 + auto _norm_region = _o->norm_region.empty() ? 0 : _fbb.CreateString(_o->norm_region);
27106 + auto _o = std::unique_ptr<LshProjectionT>(new LshProjectionT());
27114 + { auto _e = type(); _o->type = _e; }
27125 + auto _type = _o->type;
27132 + auto _o = std::unique_ptr<LSTMT>(new LSTMT());
27140 + { auto _e = bidirectional(); _o->bidirectional = _e; }
27141 + { auto _e = has_bias(); _o->has_bias = _e; }
27142 + { auto _e = input_size(); _o->input_size = _e; }
27143 + { auto _e = hidden_size(); _o->hidden_size = _e; }
27144 + { auto _e = num_layers(); _o->num_layers = _e; }
27145 + { auto _e = num_directions(); _o->num_directions = _e; }
27146 + { auto _e = dropout(); _o->dropout = _e; }
27147 + { auto _e = zoneout_cell(); _o->zoneout_cell = _e; }
27148 + { auto _e = zoneout_hidden(); _o->zoneout_hidden = _e; }
27159 + auto _bidirectional = _o->bidirectional;
27160 + auto _has_bias = _o->has_bias;
27161 + auto _input_size = _o->input_size;
27162 + auto _hidden_size = _o->hidden_size;
27163 + auto _num_layers = _o->num_layers;
27164 + auto _num_directions = _o->num_directions;
27165 + auto _dropout = _o->dropout;
27166 + auto _zoneout_cell = _o->zoneout_cell;
27167 + auto _zoneout_hidden = _o->zoneout_hidden;
27182 + auto _o = std::unique_ptr<LSTMGradT>(new LSTMGradT());
27190 + { auto _e = bidirectional(); _o->bidirectional = _e; }
27191 + { auto _e = has_bias(); _o->has_bias = _e; }
27192 + { auto _e = input_size(); _o->input_size = _e; }
27193 + { auto _e = hidden_size(); _o->hidden_size = _e; }
27194 + { auto _e = num_layers(); _o->num_layers = _e; }
27195 + { auto _e = num_directions(); _o->num_directions = _e; }
27196 + { auto _e = dropout(); _o->dropout = _e; }
27197 + { auto _e = zoneout_cell(); _o->zoneout_cell = _e; }
27198 + { auto _e = zoneout_hidden(); _o->zoneout_hidden = _e; }
27209 + auto _bidirectional = _o->bidirectional;
27210 + auto _has_bias = _o->has_bias;
27211 + auto _input_size = _o->input_size;
27212 + auto _hidden_size = _o->hidden_size;
27213 + auto _num_layers = _o->num_layers;
27214 + auto _num_directions = _o->num_directions;
27215 + auto _dropout = _o->dropout;
27216 + auto _zoneout_cell = _o->zoneout_cell;
27217 + auto _zoneout_hidden = _o->zoneout_hidden;
27232 + auto _o = std::unique_ptr<L2NormalizeFusionT>(new L2NormalizeFusionT());
27240 + { auto _e = axis(); if (_e) { _o->axis.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _…
27241 + { auto _e = epsilon(); _o->epsilon = _e; }
27242 + { auto _e = activation_type(); _o->activation_type = _e; }
27253 + auto _axis = _o->axis.size() ? _fbb.CreateVector(_o->axis) : 0;
27254 + auto _epsilon = _o->epsilon;
27255 + auto _activation_type = _o->activation_type;
27264 + auto _o = std::unique_ptr<MatMulFusionT>(new MatMulFusionT());
27272 + { auto _e = transpose_a(); _o->transpose_a = _e; }
27273 + { auto _e = transpose_b(); _o->transpose_b = _e; }
27274 + { auto _e = activation_type(); _o->activation_type = _e; }
27285 + auto _transpose_a = _o->transpose_a;
27286 + auto _transpose_b = _o->transpose_b;
27287 + auto _activation_type = _o->activation_type;
27296 + auto _o = std::unique_ptr<MaximumT>(new MaximumT());
27319 + auto _o = std::unique_ptr<MaximumGradT>(new MaximumGradT());
27327 + { auto _e = grad_x(); _o->grad_x = _e; }
27328 + { auto _e = grad_y(); _o->grad_y = _e; }
27339 + auto _grad_x = _o->grad_x;
27340 + auto _grad_y = _o->grad_y;
27348 + auto _o = std::unique_ptr<MaxPoolFusionT>(new MaxPoolFusionT());
27356 + { auto _e = kernel_size(); if (_e) { _o->kernel_size.resize(_e->size()); for (flatbuffers::uoffs…
27357 + { auto _e = strides(); if (_e) { _o->strides.resize(_e->size()); for (flatbuffers::uoffset_t _i …
27358 + { auto _e = pad(); if (_e) { _o->pad.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _i …
27359 + { auto _e = pad_mode(); _o->pad_mode = _e; }
27360 + { auto _e = round_mode(); _o->round_mode = _e; }
27361 + { auto _e = format(); _o->format = _e; }
27362 + { auto _e = global(); _o->global = _e; }
27363 + { auto _e = activation_type(); _o->activation_type = _e; }
27374 + auto _kernel_size = _o->kernel_size.size() ? _fbb.CreateVector(_o->kernel_size) : 0;
27375 + auto _strides = _o->strides.size() ? _fbb.CreateVector(_o->strides) : 0;
27376 + auto _pad = _o->pad.size() ? _fbb.CreateVector(_o->pad) : 0;
27377 + auto _pad_mode = _o->pad_mode;
27378 + auto _round_mode = _o->round_mode;
27379 + auto _format = _o->format;
27380 + auto _global = _o->global;
27381 + auto _activation_type = _o->activation_type;
27395 + auto _o = std::unique_ptr<MaxPoolGradT>(new MaxPoolGradT());
27403 + { auto _e = kernel_size(); if (_e) { _o->kernel_size.resize(_e->size()); for (flatbuffers::uoffs…
27404 + { auto _e = strides(); if (_e) { _o->strides.resize(_e->size()); for (flatbuffers::uoffset_t _i …
27405 + { auto _e = pad_mode(); _o->pad_mode = _e; }
27406 + { auto _e = format(); _o->format = _e; }
27417 + auto _kernel_size = _o->kernel_size.size() ? _fbb.CreateVector(_o->kernel_size) : 0;
27418 + auto _strides = _o->strides.size() ? _fbb.CreateVector(_o->strides) : 0;
27419 + auto _pad_mode = _o->pad_mode;
27420 + auto _format = _o->format;
27430 + auto _o = std::unique_ptr<SwitchLayerT>(new SwitchLayerT());
27453 + auto _o = std::unique_ptr<MfccT>(new MfccT());
27461 + { auto _e = freq_upper_limit(); _o->freq_upper_limit = _e; }
27462 + { auto _e = freq_lower_limit(); _o->freq_lower_limit = _e; }
27463 + { auto _e = filter_bank_channel_num(); _o->filter_bank_channel_num = _e; }
27464 + { auto _e = dct_coeff_num(); _o->dct_coeff_num = _e; }
27475 + auto _freq_upper_limit = _o->freq_upper_limit;
27476 + auto _freq_lower_limit = _o->freq_lower_limit;
27477 + auto _filter_bank_channel_num = _o->filter_bank_channel_num;
27478 + auto _dct_coeff_num = _o->dct_coeff_num;
27488 + auto _o = std::unique_ptr<MinimumT>(new MinimumT());
27511 + auto _o = std::unique_ptr<MinimumGradT>(new MinimumGradT());
27519 + { auto _e = grad_x(); _o->grad_x = _e; }
27520 + { auto _e = grad_y(); _o->grad_y = _e; }
27531 + auto _grad_x = _o->grad_x;
27532 + auto _grad_y = _o->grad_y;
27540 + auto _o = std::unique_ptr<ModT>(new ModT());
27563 + auto _o = std::unique_ptr<MulFusionT>(new MulFusionT());
27571 + { auto _e = activation_type(); _o->activation_type = _e; }
27582 + auto _activation_type = _o->activation_type;
27589 + auto _o = std::unique_ptr<MulGradT>(new MulGradT());
27612 + auto _o = std::unique_ptr<NegT>(new NegT());
27635 + auto _o = std::unique_ptr<NegGradT>(new NegGradT());
27658 + auto _o = std::unique_ptr<NotEqualT>(new NotEqualT());
27681 + auto _o = std::unique_ptr<NonMaxSuppressionT>(new NonMaxSuppressionT());
27689 + { auto _e = center_point_box(); _o->center_point_box = _e; }
27700 + auto _center_point_box = _o->center_point_box;
27707 + auto _o = std::unique_ptr<OneHotT>(new OneHotT());
27715 + { auto _e = axis(); _o->axis = _e; }
27726 + auto _axis = _o->axis;
27733 + auto _o = std::unique_ptr<OnesLikeT>(new OnesLikeT());
27756 + auto _o = std::unique_ptr<PadFusionT>(new PadFusionT());
27764 + { auto _e = paddings(); if (_e) _o->paddings = std::unique_ptr<mindspore::schema::Vec2DT>(_e->Un…
27765 + { auto _e = padding_mode(); _o->padding_mode = _e; }
27766 + { auto _e = constant_value(); _o->constant_value = _e; }
27777 + auto _paddings = _o->paddings ? CreateVec2D(_fbb, _o->paddings.get(), _rehasher) : 0;
27778 + auto _padding_mode = _o->padding_mode;
27779 + auto _constant_value = _o->constant_value;
27788 + auto _o = std::unique_ptr<PartialFusionT>(new PartialFusionT());
27796 + { auto _e = sub_graph_index(); _o->sub_graph_index = _e; }
27807 + auto _sub_graph_index = _o->sub_graph_index;
27814 + auto _o = std::unique_ptr<PowerGradT>(new PowerGradT());
27822 + { auto _e = power(); _o->power = _e; }
27823 + { auto _e = scale(); _o->scale = _e; }
27824 + { auto _e = shift(); _o->shift = _e; }
27835 + auto _power = _o->power;
27836 + auto _scale = _o->scale;
27837 + auto _shift = _o->shift;
27846 + auto _o = std::unique_ptr<PowFusionT>(new PowFusionT());
27854 + { auto _e = scale(); _o->scale = _e; }
27855 + { auto _e = shift(); _o->shift = _e; }
27866 + auto _scale = _o->scale;
27867 + auto _shift = _o->shift;
27875 + auto _o = std::unique_ptr<PriorBoxT>(new PriorBoxT());
27883 + { auto _e = min_sizes(); if (_e) { _o->min_sizes.resize(_e->size()); for (flatbuffers::uoffset_t…
27884 + { auto _e = max_sizes(); if (_e) { _o->max_sizes.resize(_e->size()); for (flatbuffers::uoffset_t…
27885 + { auto _e = aspect_ratios(); if (_e) { _o->aspect_ratios.resize(_e->size()); for (flatbuffers::u…
27886 + { auto _e = variances(); if (_e) { _o->variances.resize(_e->size()); for (flatbuffers::uoffset_t…
27887 + { auto _e = image_size_w(); _o->image_size_w = _e; }
27888 + { auto _e = image_size_h(); _o->image_size_h = _e; }
27889 + { auto _e = step_w(); _o->step_w = _e; }
27890 + { auto _e = step_h(); _o->step_h = _e; }
27891 + { auto _e = clip(); _o->clip = _e; }
27892 + { auto _e = flip(); _o->flip = _e; }
27893 + { auto _e = offset(); _o->offset = _e; }
27904 + auto _min_sizes = _o->min_sizes.size() ? _fbb.CreateVector(_o->min_sizes) : 0;
27905 + auto _max_sizes = _o->max_sizes.size() ? _fbb.CreateVector(_o->max_sizes) : 0;
27906 + auto _aspect_ratios = _o->aspect_ratios.size() ? _fbb.CreateVector(_o->aspect_ratios) : 0;
27907 + auto _variances = _o->variances.size() ? _fbb.CreateVector(_o->variances) : 0;
27908 + auto _image_size_w = _o->image_size_w;
27909 + auto _image_size_h = _o->image_size_h;
27910 + auto _step_w = _o->step_w;
27911 + auto _step_h = _o->step_h;
27912 + auto _clip = _o->clip;
27913 + auto _flip = _o->flip;
27914 + auto _offset = _o->offset;
27931 + auto _o = std::unique_ptr<PReLUFusionT>(new PReLUFusionT());
27939 + { auto _e = channel_shared(); _o->channel_shared = _e; }
27950 + auto _channel_shared = _o->channel_shared;
27957 + auto _o = std::unique_ptr<RankT>(new RankT());
27980 + auto _o = std::unique_ptr<RangeT>(new RangeT());
27988 + { auto _e = d_type(); _o->d_type = _e; }
27989 + { auto _e = start(); _o->start = _e; }
27990 + { auto _e = limit(); _o->limit = _e; }
27991 + { auto _e = delta(); _o->delta = _e; }
28002 + auto _d_type = _o->d_type;
28003 + auto _start = _o->start;
28004 + auto _limit = _o->limit;
28005 + auto _delta = _o->delta;
28015 + auto _o = std::unique_ptr<ReciprocalT>(new ReciprocalT());
28038 + auto _o = std::unique_ptr<RealDivT>(new RealDivT());
28061 + auto _o = std::unique_ptr<ReduceFusionT>(new ReduceFusionT());
28069 + { auto _e = keep_dims(); _o->keep_dims = _e; }
28070 + { auto _e = mode(); _o->mode = _e; }
28071 + { auto _e = reduce_to_end(); _o->reduce_to_end = _e; }
28072 + { auto _e = coeff(); _o->coeff = _e; }
28083 + auto _keep_dims = _o->keep_dims;
28084 + auto _mode = _o->mode;
28085 + auto _reduce_to_end = _o->reduce_to_end;
28086 + auto _coeff = _o->coeff;
28096 + auto _o = std::unique_ptr<ReshapeT>(new ReshapeT());
28119 + auto _o = std::unique_ptr<ResizeT>(new ResizeT());
28127 + { auto _e = format(); _o->format = _e; }
28128 + { auto _e = method(); _o->method = _e; }
28129 + { auto _e = new_height(); _o->new_height = _e; }
28130 + { auto _e = new_width(); _o->new_width = _e; }
28131 + { auto _e = preserve_aspect_ratio(); _o->preserve_aspect_ratio = _e; }
28132 + { auto _e = coordinate_transform_mode(); _o->coordinate_transform_mode = _e; }
28133 + { auto _e = cubic_coeff(); _o->cubic_coeff = _e; }
28134 + { auto _e = exclude_outside(); _o->exclude_outside = _e; }
28135 + { auto _e = extrapolation_value(); _o->extrapolation_value = _e; }
28136 + { auto _e = nearest_mode(); _o->nearest_mode = _e; }
28147 + auto _format = _o->format;
28148 + auto _method = _o->method;
28149 + auto _new_height = _o->new_height;
28150 + auto _new_width = _o->new_width;
28151 + auto _preserve_aspect_ratio = _o->preserve_aspect_ratio;
28152 + auto _coordinate_transform_mode = _o->coordinate_transform_mode;
28153 + auto _cubic_coeff = _o->cubic_coeff;
28154 + auto _exclude_outside = _o->exclude_outside;
28155 + auto _extrapolation_value = _o->extrapolation_value;
28156 + auto _nearest_mode = _o->nearest_mode;
28172 + auto _o = std::unique_ptr<ReverseSequenceT>(new ReverseSequenceT());
28180 + { auto _e = seq_dim(); _o->seq_dim = _e; }
28181 + { auto _e = batch_dim(); _o->batch_dim = _e; }
28192 + auto _seq_dim = _o->seq_dim;
28193 + auto _batch_dim = _o->batch_dim;
28201 + auto _o = std::unique_ptr<ReverseV2T>(new ReverseV2T());
28209 + { auto _e = axis(); if (_e) { _o->axis.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _…
28220 + auto _axis = _o->axis.size() ? _fbb.CreateVector(_o->axis) : 0;
28227 + auto _o = std::unique_ptr<RfftT>(new RfftT());
28235 + { auto _e = fft_length(); _o->fft_length = _e; }
28246 + auto _fft_length = _o->fft_length;
28253 + auto _o = std::unique_ptr<ROIPoolingT>(new ROIPoolingT());
28261 + { auto _e = pooled_h(); _o->pooled_h = _e; }
28262 + { auto _e = pooled_w(); _o->pooled_w = _e; }
28263 + { auto _e = scale(); _o->scale = _e; }
28274 + auto _pooled_h = _o->pooled_h;
28275 + auto _pooled_w = _o->pooled_w;
28276 + auto _scale = _o->scale;
28285 + auto _o = std::unique_ptr<RoundT>(new RoundT());
28308 + auto _o = std::unique_ptr<RsqrtT>(new RsqrtT());
28331 + auto _o = std::unique_ptr<QuantDTypeCastT>(new QuantDTypeCastT());
28339 + { auto _e = src_t(); _o->src_t = _e; }
28340 + { auto _e = dst_t(); _o->dst_t = _e; }
28351 + auto _src_t = _o->src_t;
28352 + auto _dst_t = _o->dst_t;
28360 + auto _o = std::unique_ptr<ScaleFusionT>(new ScaleFusionT());
28368 + { auto _e = axis(); _o->axis = _e; }
28369 + { auto _e = activation_type(); _o->activation_type = _e; }
28380 + auto _axis = _o->axis;
28381 + auto _activation_type = _o->activation_type;
28389 + auto _o = std::unique_ptr<ScatterNdT>(new ScatterNdT());
28412 + auto _o = std::unique_ptr<SGDT>(new SGDT());
28420 + { auto _e = nesterov(); _o->nesterov = _e; }
28421 + { auto _e = dampening(); _o->dampening = _e; }
28422 + { auto _e = weight_decay(); _o->weight_decay = _e; }
28433 + auto _nesterov = _o->nesterov;
28434 + auto _dampening = _o->dampening;
28435 + auto _weight_decay = _o->weight_decay;
28444 + auto _o = std::unique_ptr<ShapeT>(new ShapeT());
28467 + auto _o = std::unique_ptr<SigmoidCrossEntropyWithLogitsT>(new SigmoidCrossEntropyWithLogitsT());
28490 + auto _o = std::unique_ptr<SigmoidCrossEntropyWithLogitsGradT>(new SigmoidCrossEntropyWithLogitsG…
28513 + auto _o = std::unique_ptr<SinT>(new SinT());
28536 + auto _o = std::unique_ptr<SkipGramT>(new SkipGramT());
28544 + { auto _e = include_all_grams(); _o->include_all_grams = _e; }
28545 + { auto _e = max_skip_size(); _o->max_skip_size = _e; }
28546 + { auto _e = ngram_size(); _o->ngram_size = _e; }
28557 + auto _include_all_grams = _o->include_all_grams;
28558 + auto _max_skip_size = _o->max_skip_size;
28559 + auto _ngram_size = _o->ngram_size;
28568 + auto _o = std::unique_ptr<SliceFusionT>(new SliceFusionT());
28576 + { auto _e = axes(); if (_e) { _o->axes.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _…
28587 + auto _axes = _o->axes.size() ? _fbb.CreateVector(_o->axes) : 0;
28594 + auto _o = std::unique_ptr<SmoothL1LossT>(new SmoothL1LossT());
28602 + { auto _e = beta(); _o->beta = _e; }
28613 + auto _beta = _o->beta;
28620 + auto _o = std::unique_ptr<SmoothL1LossGradT>(new SmoothL1LossGradT());
28628 + { auto _e = beta(); _o->beta = _e; }
28639 + auto _beta = _o->beta;
28646 + auto _o = std::unique_ptr<SoftmaxT>(new SoftmaxT());
28654 + { auto _e = axis(); if (_e) { _o->axis.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _…
28665 + auto _axis = _o->axis.size() ? _fbb.CreateVector(_o->axis) : 0;
28672 + auto _o = std::unique_ptr<SoftmaxCrossEntropyWithLogitsT>(new SoftmaxCrossEntropyWithLogitsT());
28695 + auto _o = std::unique_ptr<SpaceToBatchT>(new SpaceToBatchT());
28703 + { auto _e = block_size(); if (_e) { _o->block_size.resize(_e->size()); for (flatbuffers::uoffset…
28704 + { auto _e = paddings(); if (_e) _o->paddings = std::unique_ptr<mindspore::schema::Vec2DT>(_e->Un…
28715 + auto _block_size = _o->block_size.size() ? _fbb.CreateVector(_o->block_size) : 0;
28716 + auto _paddings = _o->paddings ? CreateVec2D(_fbb, _o->paddings.get(), _rehasher) : 0;
28724 + auto _o = std::unique_ptr<SpaceToBatchNDT>(new SpaceToBatchNDT());
28732 + { auto _e = block_shape(); if (_e) { _o->block_shape.resize(_e->size()); for (flatbuffers::uoffs…
28733 + { auto _e = paddings(); if (_e) _o->paddings = std::unique_ptr<mindspore::schema::Vec2DT>(_e->Un…
28744 + auto _block_shape = _o->block_shape.size() ? _fbb.CreateVector(_o->block_shape) : 0;
28745 + auto _paddings = _o->paddings ? CreateVec2D(_fbb, _o->paddings.get(), _rehasher) : 0;
28753 + auto _o = std::unique_ptr<SpaceToDepthT>(new SpaceToDepthT());
28761 + { auto _e = block_size(); _o->block_size = _e; }
28762 + { auto _e = format(); _o->format = _e; }
28773 + auto _block_size = _o->block_size;
28774 + auto _format = _o->format;
28782 + auto _o = std::unique_ptr<SparseSoftmaxCrossEntropyWithLogitsT>(new SparseSoftmaxCrossEntropyWit…
28790 + { auto _e = is_grad(); _o->is_grad = _e; }
28801 + auto _is_grad = _o->is_grad;
28808 + auto _o = std::unique_ptr<SparseToDenseT>(new SparseToDenseT());
28831 + auto _o = std::unique_ptr<SplitT>(new SplitT());
28839 + { auto _e = output_num(); _o->output_num = _e; }
28840 + { auto _e = size_splits(); if (_e) { _o->size_splits.resize(_e->size()); for (flatbuffers::uoffs…
28841 + { auto _e = axis(); _o->axis = _e; }
28852 + auto _output_num = _o->output_num;
28853 + auto _size_splits = _o->size_splits.size() ? _fbb.CreateVector(_o->size_splits) : 0;
28854 + auto _axis = _o->axis;
28863 + auto _o = std::unique_ptr<SqrtT>(new SqrtT());
28886 + auto _o = std::unique_ptr<SqueezeT>(new SqueezeT());
28894 + { auto _e = axis(); if (_e) { _o->axis.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _…
28905 + auto _axis = _o->axis.size() ? _fbb.CreateVector(_o->axis) : 0;
28912 + auto _o = std::unique_ptr<SquareT>(new SquareT());
28935 + auto _o = std::unique_ptr<SquaredDifferenceT>(new SquaredDifferenceT());
28958 + auto _o = std::unique_ptr<StackT>(new StackT());
28966 + { auto _e = axis(); _o->axis = _e; }
28977 + auto _axis = _o->axis;
28984 + auto _o = std::unique_ptr<StridedSliceT>(new StridedSliceT());
28992 + { auto _e = begin_mask(); _o->begin_mask = _e; }
28993 + { auto _e = end_mask(); _o->end_mask = _e; }
28994 + { auto _e = ellipsis_mask(); _o->ellipsis_mask = _e; }
28995 + { auto _e = new_axis_mask(); _o->new_axis_mask = _e; }
28996 + { auto _e = shrink_axis_mask(); _o->shrink_axis_mask = _e; }
29007 + auto _begin_mask = _o->begin_mask;
29008 + auto _end_mask = _o->end_mask;
29009 + auto _ellipsis_mask = _o->ellipsis_mask;
29010 + auto _new_axis_mask = _o->new_axis_mask;
29011 + auto _shrink_axis_mask = _o->shrink_axis_mask;
29022 + auto _o = std::unique_ptr<SubFusionT>(new SubFusionT());
29030 + { auto _e = activation_type(); _o->activation_type = _e; }
29041 + auto _activation_type = _o->activation_type;
29048 + auto _o = std::unique_ptr<SubGradT>(new SubGradT());
29071 + auto _o = std::unique_ptr<SwitchT>(new SwitchT());
29094 + auto _o = std::unique_ptr<TensorListFromTensorT>(new TensorListFromTensorT());
29102 + { auto _e = element_dtype(); _o->element_dtype = _e; }
29103 + { auto _e = shape_type(); _o->shape_type = _e; }
29114 + auto _element_dtype = _o->element_dtype;
29115 + auto _shape_type = _o->shape_type;
29123 + auto _o = std::unique_ptr<TensorListGetItemT>(new TensorListGetItemT());
29131 + { auto _e = element_dtype(); _o->element_dtype = _e; }
29142 + auto _element_dtype = _o->element_dtype;
29149 + auto _o = std::unique_ptr<TensorListReserveT>(new TensorListReserveT());
29157 + { auto _e = element_dtype(); _o->element_dtype = _e; }
29158 + { auto _e = shape_type(); _o->shape_type = _e; }
29169 + auto _element_dtype = _o->element_dtype;
29170 + auto _shape_type = _o->shape_type;
29178 + auto _o = std::unique_ptr<TensorListSetItemT>(new TensorListSetItemT());
29186 + { auto _e = element_dtype(); _o->element_dtype = _e; }
29197 + auto _element_dtype = _o->element_dtype;
29204 + auto _o = std::unique_ptr<TensorListStackT>(new TensorListStackT());
29212 + { auto _e = num_elements(); _o->num_elements = _e; }
29213 + { auto _e = element_dtype(); _o->element_dtype = _e; }
29224 + auto _num_elements = _o->num_elements;
29225 + auto _element_dtype = _o->element_dtype;
29233 + auto _o = std::unique_ptr<TileFusionT>(new TileFusionT());
29241 + { auto _e = dims(); if (_e) { _o->dims.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _…
29252 + auto _dims = _o->dims.size() ? _fbb.CreateVector(_o->dims) : 0;
29259 + auto _o = std::unique_ptr<TopKFusionT>(new TopKFusionT());
29267 + { auto _e = sorted(); _o->sorted = _e; }
29268 + { auto _e = axis(); _o->axis = _e; }
29269 + { auto _e = largest(); _o->largest = _e; }
29280 + auto _sorted = _o->sorted;
29281 + auto _axis = _o->axis;
29282 + auto _largest = _o->largest;
29291 + auto _o = std::unique_ptr<TransposeT>(new TransposeT());
29314 + auto _o = std::unique_ptr<UniqueT>(new UniqueT());
29337 + auto _o = std::unique_ptr<UnsortedSegmentSumT>(new UnsortedSegmentSumT());
29360 + auto _o = std::unique_ptr<UnsqueezeT>(new UnsqueezeT());
29368 + { auto _e = axis(); if (_e) { _o->axis.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _…
29379 + auto _axis = _o->axis.size() ? _fbb.CreateVector(_o->axis) : 0;
29386 + auto _o = std::unique_ptr<UnstackT>(new UnstackT());
29394 + { auto _e = axis(); _o->axis = _e; }
29405 + auto _axis = _o->axis;
29412 + auto _o = std::unique_ptr<WhereT>(new WhereT());
29435 + auto _o = std::unique_ptr<ZerosLikeT>(new ZerosLikeT());
29458 + auto _o = std::unique_ptr<SelectT>(new SelectT());
29481 + auto _o = std::unique_ptr<GRUT>(new GRUT());
29489 + { auto _e = bidirectional(); _o->bidirectional = _e; }
29500 + auto _bidirectional = _o->bidirectional;
29507 + auto _o = std::unique_ptr<NonZeroT>(new NonZeroT());
29530 + auto _o = std::unique_ptr<InvertPermutationT>(new InvertPermutationT());
29553 + auto _o = std::unique_ptr<SizeT>(new SizeT());
29576 + auto _o = std::unique_ptr<RandomStandardNormalT>(new RandomStandardNormalT());
29584 + { auto _e = seed(); _o->seed = _e; }
29585 + { auto _e = seed2(); _o->seed2 = _e; }
29596 + auto _seed = _o->seed;
29597 + auto _seed2 = _o->seed2;
29605 + auto _o = std::unique_ptr<CropAndResizeT>(new CropAndResizeT());
29613 + { auto _e = method(); _o->method = _e; }
29614 + { auto _e = extrapolation_value(); _o->extrapolation_value = _e; }
29625 + auto _method = _o->method;
29626 + auto _extrapolation_value = _o->extrapolation_value;
29634 + auto _o = std::unique_ptr<ErfT>(new ErfT());
29657 + auto _o = std::unique_ptr<StridedSliceGradT>(new StridedSliceGradT());
29665 + { auto _e = begin_mask(); _o->begin_mask = _e; }
29666 + { auto _e = end_mask(); _o->end_mask = _e; }
29667 + { auto _e = ellipsis_mask(); _o->ellipsis_mask = _e; }
29668 + { auto _e = new_axis_mask(); _o->new_axis_mask = _e; }
29669 + { auto _e = shrink_axis_mask(); _o->shrink_axis_mask = _e; }
29680 + auto _begin_mask = _o->begin_mask;
29681 + auto _end_mask = _o->end_mask;
29682 + auto _ellipsis_mask = _o->ellipsis_mask;
29683 + auto _new_axis_mask = _o->new_axis_mask;
29684 + auto _shrink_axis_mask = _o->shrink_axis_mask;
29695 + auto _o = std::unique_ptr<IsFiniteT>(new IsFiniteT());
29718 + auto _o = std::unique_ptr<LinSpaceT>(new LinSpaceT());
29741 + auto _o = std::unique_ptr<UniformRealT>(new UniformRealT());
29749 + { auto _e = seed(); _o->seed = _e; }
29750 + { auto _e = seed2(); _o->seed2 = _e; }
29761 + auto _seed = _o->seed;
29762 + auto _seed2 = _o->seed2;
29770 + auto _o = std::unique_ptr<AbsGradT>(new AbsGradT());
29793 + auto _o = std::unique_ptr<RsqrtGradT>(new RsqrtGradT());
29816 + auto _o = std::unique_ptr<SqrtGradT>(new SqrtGradT());
29839 + auto _o = std::unique_ptr<LayerNormGradT>(new LayerNormGradT());
29847 + { auto _e = begin_norm_axis(); _o->begin_norm_axis = _e; }
29848 + { auto _e = begin_params_axis(); _o->begin_params_axis = _e; }
29859 + auto _begin_norm_axis = _o->begin_norm_axis;
29860 + auto _begin_params_axis = _o->begin_params_axis;
29868 + auto _o = std::unique_ptr<ResizeGradT>(new ResizeGradT());
29876 + { auto _e = method(); _o->method = _e; }
29877 + { auto _e = align_corners(); _o->align_corners = _e; }
29888 + auto _method = _o->method;
29889 + auto _align_corners = _o->align_corners;
29897 + auto _o = std::unique_ptr<SpliceT>(new SpliceT());
29905 + { auto _e = context(); if (_e) { _o->context.resize(_e->size()); for (flatbuffers::uoffset_t _i …
29906 + { auto _e = forward_indexes(); if (_e) { _o->forward_indexes.resize(_e->size()); for (flatbuffer…
29907 + { auto _e = output_dim(); _o->output_dim = _e; }
29918 + auto _context = _o->context.size() ? _fbb.CreateVector(_o->context) : 0;
29919 + auto _forward_indexes = _o->forward_indexes.size() ? _fbb.CreateVector(_o->forward_indexes) : 0;
29920 + auto _output_dim = _o->output_dim;
29929 + auto _o = std::unique_ptr<LogSoftmaxT>(new LogSoftmaxT());
29937 + { auto _e = axis(); _o->axis = _e; }
29948 + auto _axis = _o->axis;
29955 + auto _o = std::unique_ptr<CallT>(new CallT());
29963 + { auto _e = is_tail_call(); _o->is_tail_call = _e; }
29974 + auto _is_tail_call = _o->is_tail_call;
29981 + auto _o = std::unique_ptr<CumSumT>(new CumSumT());
29989 + { auto _e = exclusive(); _o->exclusive = _e; }
29990 + { auto _e = reverse(); _o->reverse = _e; }
30001 + auto _exclusive = _o->exclusive;
30002 + auto _reverse = _o->reverse;
30010 + auto _o = std::unique_ptr<CustomT>(new CustomT());
30018 + { auto _e = type(); if (_e) _o->type = _e->str(); }
30019 + { auto _e = attr(); if (_e) { _o->attr.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _…
30030 + auto _type = _o->type.empty() ? 0 : _fbb.CreateString(_o->type);
30031 + auto _attr = _o->attr.size() ? _fbb.CreateVector<flatbuffers::Offset<mindspore::schema::Attribut…
30039 + auto _o = std::unique_ptr<SplitWithOverlapT>(new SplitWithOverlapT());
30047 + { auto _e = split_dim(); _o->split_dim = _e; }
30048 + { auto _e = number_split(); _o->number_split = _e; }
30049 + { auto _e = ratio(); if (_e) { _o->ratio.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0;…
30050 + { auto _e = extend_top(); if (_e) { _o->extend_top.resize(_e->size()); for (flatbuffers::uoffset…
30051 + { auto _e = extend_bottom(); if (_e) { _o->extend_bottom.resize(_e->size()); for (flatbuffers::u…
30062 + auto _split_dim = _o->split_dim;
30063 + auto _number_split = _o->number_split;
30064 + auto _ratio = _o->ratio.size() ? _fbb.CreateVector(_o->ratio) : 0;
30065 + auto _extend_top = _o->extend_top.size() ? _fbb.CreateVector(_o->extend_top) : 0;
30066 + auto _extend_bottom = _o->extend_bottom.size() ? _fbb.CreateVector(_o->extend_bottom) : 0;
30077 + auto _o = std::unique_ptr<GenOPT>(new GenOPT());
30085 + { auto _e = activation_type(); _o->activation_type = _e; }
30086 + { auto _e = alpha(); _o->alpha = _e; }
30087 + { auto _e = min_val(); _o->min_val = _e; }
30088 + { auto _e = max_val(); _o->max_val = _e; }
30089 + { auto _e = is_training(); _o->is_training = _e; }
30090 + { auto _e = format(); _o->format = _e; }
30091 + { auto _e = kernel_size(); if (_e) { _o->kernel_size.resize(_e->size()); for (flatbuffers::uoffs…
30092 + { auto _e = stride(); if (_e) { _o->stride.resize(_e->size()); for (flatbuffers::uoffset_t _i = …
30093 + { auto _e = dilation(); if (_e) { _o->dilation.resize(_e->size()); for (flatbuffers::uoffset_t _…
30094 + { auto _e = pad_mode(); _o->pad_mode = _e; }
30095 + { auto _e = pad_list(); if (_e) { _o->pad_list.resize(_e->size()); for (flatbuffers::uoffset_t _…
30096 + { auto _e = mode(); _o->mode = _e; }
30097 + { auto _e = group(); _o->group = _e; }
30098 + { auto _e = in_channel(); _o->in_channel = _e; }
30099 + { auto _e = out_channel(); _o->out_channel = _e; }
30100 + { auto _e = eltwise_mode(); _o->eltwise_mode = _e; }
30101 + { auto _e = has_bias(); _o->has_bias = _e; }
30102 + { auto _e = use_axis(); _o->use_axis = _e; }
30103 + { auto _e = axis(); _o->axis = _e; }
30104 + { auto _e = epsilon(); _o->epsilon = _e; }
30105 + { auto _e = momentum(); _o->momentum = _e; }
30106 + { auto _e = transpose_a(); _o->transpose_a = _e; }
30107 + { auto _e = transpose_b(); _o->transpose_b = _e; }
30108 + { auto _e = pad(); if (_e) { _o->pad.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _i …
30109 + { auto _e = round_mode(); _o->round_mode = _e; }
30110 + { auto _e = global(); _o->global = _e; }
30111 + { auto _e = channel_shared(); _o->channel_shared = _e; }
30112 + { auto _e = axes(); if (_e) { _o->axes.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _…
30113 + { auto _e = keep_dims(); _o->keep_dims = _e; }
30114 + { auto _e = reduce_mode(); _o->reduce_mode = _e; }
30115 + { auto _e = reduce_to_end(); _o->reduce_to_end = _e; }
30116 + { auto _e = coeff(); _o->coeff = _e; }
30127 + auto _activation_type = _o->activation_type;
30128 + auto _alpha = _o->alpha;
30129 + auto _min_val = _o->min_val;
30130 + auto _max_val = _o->max_val;
30131 + auto _is_training = _o->is_training;
30132 + auto _format = _o->format;
30133 + auto _kernel_size = _o->kernel_size.size() ? _fbb.CreateVector(_o->kernel_size) : 0;
30134 + auto _stride = _o->stride.size() ? _fbb.CreateVector(_o->stride) : 0;
30135 + auto _dilation = _o->dilation.size() ? _fbb.CreateVector(_o->dilation) : 0;
30136 + auto _pad_mode = _o->pad_mode;
30137 + auto _pad_list = _o->pad_list.size() ? _fbb.CreateVector(_o->pad_list) : 0;
30138 + auto _mode = _o->mode;
30139 + auto _group = _o->group;
30140 + auto _in_channel = _o->in_channel;
30141 + auto _out_channel = _o->out_channel;
30142 + auto _eltwise_mode = _o->eltwise_mode;
30143 + auto _has_bias = _o->has_bias;
30144 + auto _use_axis = _o->use_axis;
30145 + auto _axis = _o->axis;
30146 + auto _epsilon = _o->epsilon;
30147 + auto _momentum = _o->momentum;
30148 + auto _transpose_a = _o->transpose_a;
30149 + auto _transpose_b = _o->transpose_b;
30150 + auto _pad = _o->pad.size() ? _fbb.CreateVector(_o->pad) : 0;
30151 + auto _round_mode = _o->round_mode;
30152 + auto _global = _o->global;
30153 + auto _channel_shared = _o->channel_shared;
30154 + auto _axes = _o->axes.size() ? _fbb.CreateVector(_o->axes) : 0;
30155 + auto _keep_dims = _o->keep_dims;
30156 + auto _reduce_mode = _o->reduce_mode;
30157 + auto _reduce_to_end = _o->reduce_to_end;
30158 + auto _coeff = _o->coeff;
30196 + auto _o = std::unique_ptr<RaggedRangeT>(new RaggedRangeT());
30219 + auto _o = std::unique_ptr<GLUT>(new GLUT());
30227 + { auto _e = axis(); _o->axis = _e; }
30238 + auto _axis = _o->axis;
30245 + auto _o = std::unique_ptr<TensorArrayT>(new TensorArrayT());
30253 + { auto _e = dynamic_size(); _o->dynamic_size = _e; }
30254 + { auto _e = identical_element_shapes(); _o->identical_element_shapes = _e; }
30255 + { auto _e = element_shape(); if (_e) { _o->element_shape.resize(_e->size()); for (flatbuffers::u…
30256 + { auto _e = data_type(); _o->data_type = _e; }
30267 + auto _dynamic_size = _o->dynamic_size;
30268 + auto _identical_element_shapes = _o->identical_element_shapes;
30269 + auto _element_shape = _o->element_shape.size() ? _fbb.CreateVector(_o->element_shape) : 0;
30270 + auto _data_type = _o->data_type;
30280 + auto _o = std::unique_ptr<TensorArrayReadT>(new TensorArrayReadT());
30303 + auto _o = std::unique_ptr<TensorArrayWriteT>(new TensorArrayWriteT());
30326 + auto _o = std::unique_ptr<AffineT>(new AffineT());
30334 + { auto _e = context(); if (_e) { _o->context.resize(_e->size()); for (flatbuffers::uoffset_t _i …
30335 + { auto _e = output_dim(); _o->output_dim = _e; }
30336 + { auto _e = activation_type(); _o->activation_type = _e; }
30337 + { auto _e = transpose_a(); _o->transpose_a = _e; }
30338 + { auto _e = transpose_b(); _o->transpose_b = _e; }
30349 + auto _context = _o->context.size() ? _fbb.CreateVector(_o->context) : 0;
30350 + auto _output_dim = _o->output_dim;
30351 + auto _activation_type = _o->activation_type;
30352 + auto _transpose_a = _o->transpose_a;
30353 + auto _transpose_b = _o->transpose_b;
30364 + auto _o = std::unique_ptr<ScatterNdUpdateT>(new ScatterNdUpdateT());
30387 + auto _o = std::unique_ptr<AllGatherT>(new AllGatherT());
30395 + { auto _e = group(); if (_e) _o->group = _e->str(); }
30396 + { auto _e = rank_size(); _o->rank_size = _e; }
30407 + auto _group = _o->group.empty() ? 0 : _fbb.CreateString(_o->group);
30408 + auto _rank_size = _o->rank_size;
30416 + auto _o = std::unique_ptr<ReduceScatterT>(new ReduceScatterT());
30424 + { auto _e = group(); if (_e) _o->group = _e->str(); }
30425 + { auto _e = mode(); _o->mode = _e; }
30426 + { auto _e = rank_size(); _o->rank_size = _e; }
30437 + auto _group = _o->group.empty() ? 0 : _fbb.CreateString(_o->group);
30438 + auto _mode = _o->mode;
30439 + auto _rank_size = _o->rank_size;
30448 + auto _o = std::unique_ptr<DynamicQuantT>(new DynamicQuantT());
30456 + { auto _e = symmetric(); _o->symmetric = _e; }
30457 + { auto _e = dst_type(); _o->dst_type = _e; }
30468 + auto _symmetric = _o->symmetric;
30469 + auto _dst_type = _o->dst_type;
30477 + auto _o = std::unique_ptr<LSTMGradDataT>(new LSTMGradDataT());
30485 + { auto _e = bidirectional(); _o->bidirectional = _e; }
30486 + { auto _e = has_bias(); _o->has_bias = _e; }
30487 + { auto _e = input_size(); _o->input_size = _e; }
30488 + { auto _e = hidden_size(); _o->hidden_size = _e; }
30489 + { auto _e = num_layers(); _o->num_layers = _e; }
30490 + { auto _e = num_directions(); _o->num_directions = _e; }
30491 + { auto _e = dropout(); _o->dropout = _e; }
30492 + { auto _e = zoneout_cell(); _o->zoneout_cell = _e; }
30493 + { auto _e = zoneout_hidden(); _o->zoneout_hidden = _e; }
30504 + auto _bidirectional = _o->bidirectional;
30505 + auto _has_bias = _o->has_bias;
30506 + auto _input_size = _o->input_size;
30507 + auto _hidden_size = _o->hidden_size;
30508 + auto _num_layers = _o->num_layers;
30509 + auto _num_directions = _o->num_directions;
30510 + auto _dropout = _o->dropout;
30511 + auto _zoneout_cell = _o->zoneout_cell;
30512 + auto _zoneout_hidden = _o->zoneout_hidden;
30527 + auto _o = std::unique_ptr<LSTMGradWeightT>(new LSTMGradWeightT());
30535 + { auto _e = bidirectional(); _o->bidirectional = _e; }
30536 + { auto _e = has_bias(); _o->has_bias = _e; }
30537 + { auto _e = input_size(); _o->input_size = _e; }
30538 + { auto _e = hidden_size(); _o->hidden_size = _e; }
30539 + { auto _e = num_layers(); _o->num_layers = _e; }
30540 + { auto _e = num_directions(); _o->num_directions = _e; }
30541 + { auto _e = dropout(); _o->dropout = _e; }
30542 + { auto _e = zoneout_cell(); _o->zoneout_cell = _e; }
30543 + { auto _e = zoneout_hidden(); _o->zoneout_hidden = _e; }
30554 + auto _bidirectional = _o->bidirectional;
30555 + auto _has_bias = _o->has_bias;
30556 + auto _input_size = _o->input_size;
30557 + auto _hidden_size = _o->hidden_size;
30558 + auto _num_layers = _o->num_layers;
30559 + auto _num_directions = _o->num_directions;
30560 + auto _dropout = _o->dropout;
30561 + auto _zoneout_cell = _o->zoneout_cell;
30562 + auto _zoneout_hidden = _o->zoneout_hidden;
30577 + auto _o = std::unique_ptr<RandomNormalT>(new RandomNormalT());
30585 + { auto _e = seed(); _o->seed = _e; }
30586 + { auto _e = mean(); _o->mean = _e; }
30587 + { auto _e = scale(); _o->scale = _e; }
30598 + auto _seed = _o->seed;
30599 + auto _mean = _o->mean;
30600 + auto _scale = _o->scale;
30609 + auto _o = std::unique_ptr<NLLLossT>(new NLLLossT());
30617 + { auto _e = reduction(); _o->reduction = _e; }
30628 + auto _reduction = _o->reduction;
30635 + auto _o = std::unique_ptr<NLLLossGradT>(new NLLLossGradT());
30643 + { auto _e = reduction(); _o->reduction = _e; }
30654 + auto _reduction = _o->reduction;
30661 + auto _o = std::unique_ptr<FormatTransposeT>(new FormatTransposeT());
30669 + { auto _e = src_format(); _o->src_format = _e; }
30670 + { auto _e = dst_format(); _o->dst_format = _e; }
30681 + auto _src_format = _o->src_format;
30682 + auto _dst_format = _o->dst_format;
30690 + auto _o = std::unique_ptr<GatherDT>(new GatherDT());
30713 + auto _o = std::unique_ptr<GroupNormFusionT>(new GroupNormFusionT());
30721 + { auto _e = num_groups(); _o->num_groups = _e; }
30722 + { auto _e = epsilon(); _o->epsilon = _e; }
30723 + { auto _e = affine(); _o->affine = _e; }
30734 + auto _num_groups = _o->num_groups;
30735 + auto _epsilon = _o->epsilon;
30736 + auto _affine = _o->affine;
30750 + auto ptr = reinterpret_cast<const mindspore::schema::Abs *>(obj);
30754 + auto ptr = reinterpret_cast<const mindspore::schema::Activation *>(obj);
30758 + auto ptr = reinterpret_cast<const mindspore::schema::ActivationGrad *>(obj);
30762 + auto ptr = reinterpret_cast<const mindspore::schema::Adam *>(obj);
30766 + auto ptr = reinterpret_cast<const mindspore::schema::AddFusion *>(obj);
30770 + auto ptr = reinterpret_cast<const mindspore::schema::AdderFusion *>(obj);
30774 + auto ptr = reinterpret_cast<const mindspore::schema::AddGrad *>(obj);
30778 + auto ptr = reinterpret_cast<const mindspore::schema::AddN *>(obj);
30782 + auto ptr = reinterpret_cast<const mindspore::schema::All *>(obj);
30786 + auto ptr = reinterpret_cast<const mindspore::schema::ApplyMomentum *>(obj);
30790 + auto ptr = reinterpret_cast<const mindspore::schema::ArgMaxFusion *>(obj);
30794 + auto ptr = reinterpret_cast<const mindspore::schema::ArgMinFusion *>(obj);
30798 + auto ptr = reinterpret_cast<const mindspore::schema::Assert *>(obj);
30802 + auto ptr = reinterpret_cast<const mindspore::schema::Assign *>(obj);
30806 + auto ptr = reinterpret_cast<const mindspore::schema::AssignAdd *>(obj);
30810 + auto ptr = reinterpret_cast<const mindspore::schema::AudioSpectrogram *>(obj);
30814 + auto ptr = reinterpret_cast<const mindspore::schema::AvgPoolFusion *>(obj);
30818 + auto ptr = reinterpret_cast<const mindspore::schema::AvgPoolGrad *>(obj);
30822 + auto ptr = reinterpret_cast<const mindspore::schema::BatchNorm *>(obj);
30826 + auto ptr = reinterpret_cast<const mindspore::schema::BatchNormGrad *>(obj);
30830 + auto ptr = reinterpret_cast<const mindspore::schema::BatchToSpace *>(obj);
30834 + auto ptr = reinterpret_cast<const mindspore::schema::BatchToSpaceND *>(obj);
30838 + auto ptr = reinterpret_cast<const mindspore::schema::BiasAdd *>(obj);
30842 + auto ptr = reinterpret_cast<const mindspore::schema::BinaryCrossEntropy *>(obj);
30846 + auto ptr = reinterpret_cast<const mindspore::schema::BinaryCrossEntropyGrad *>(obj);
30850 + auto ptr = reinterpret_cast<const mindspore::schema::BiasAddGrad *>(obj);
30854 + auto ptr = reinterpret_cast<const mindspore::schema::BroadcastTo *>(obj);
30858 + auto ptr = reinterpret_cast<const mindspore::schema::Cast *>(obj);
30862 + auto ptr = reinterpret_cast<const mindspore::schema::Ceil *>(obj);
30866 + auto ptr = reinterpret_cast<const mindspore::schema::Clip *>(obj);
30870 + auto ptr = reinterpret_cast<const mindspore::schema::Concat *>(obj);
30874 + auto ptr = reinterpret_cast<const mindspore::schema::Attention *>(obj);
30878 + auto ptr = reinterpret_cast<const mindspore::schema::Conv2DBackpropFilterFusion *>(obj);
30882 + auto ptr = reinterpret_cast<const mindspore::schema::Conv2DBackpropInputFusion *>(obj);
30886 + auto ptr = reinterpret_cast<const mindspore::schema::Conv2DFusion *>(obj);
30890 + auto ptr = reinterpret_cast<const mindspore::schema::Conv2dTransposeFusion *>(obj);
30894 + auto ptr = reinterpret_cast<const mindspore::schema::Cos *>(obj);
30898 + auto ptr = reinterpret_cast<const mindspore::schema::ConstantOfShape *>(obj);
30902 + auto ptr = reinterpret_cast<const mindspore::schema::Crop *>(obj);
30906 + auto ptr = reinterpret_cast<const mindspore::schema::CustomExtractFeatures *>(obj);
30910 + auto ptr = reinterpret_cast<const mindspore::schema::CustomNormalize *>(obj);
30914 + auto ptr = reinterpret_cast<const mindspore::schema::CustomPredict *>(obj);
30918 + auto ptr = reinterpret_cast<const mindspore::schema::DeConv2DGradFilter *>(obj);
30922 + auto ptr = reinterpret_cast<const mindspore::schema::Depend *>(obj);
30926 + auto ptr = reinterpret_cast<const mindspore::schema::DepthToSpace *>(obj);
30930 + auto ptr = reinterpret_cast<const mindspore::schema::DetectionPostProcess *>(obj);
30934 + auto ptr = reinterpret_cast<const mindspore::schema::DivFusion *>(obj);
30938 + auto ptr = reinterpret_cast<const mindspore::schema::DivGrad *>(obj);
30942 + auto ptr = reinterpret_cast<const mindspore::schema::Dropout *>(obj);
30946 + auto ptr = reinterpret_cast<const mindspore::schema::DropoutGrad *>(obj);
30950 + auto ptr = reinterpret_cast<const mindspore::schema::Elu *>(obj);
30954 + auto ptr = reinterpret_cast<const mindspore::schema::Eltwise *>(obj);
30958 + auto ptr = reinterpret_cast<const mindspore::schema::Equal *>(obj);
30962 + auto ptr = reinterpret_cast<const mindspore::schema::EmbeddingLookupFusion *>(obj);
30966 + auto ptr = reinterpret_cast<const mindspore::schema::ExpFusion *>(obj);
30970 + auto ptr = reinterpret_cast<const mindspore::schema::ExpandDims *>(obj);
30974 + auto ptr = reinterpret_cast<const mindspore::schema::FakeQuantWithMinMaxVars *>(obj);
30978 + auto ptr = reinterpret_cast<const mindspore::schema::FakeQuantWithMinMaxVarsPerChannel *>(ob…
30982 + auto ptr = reinterpret_cast<const mindspore::schema::FftReal *>(obj);
30986 + auto ptr = reinterpret_cast<const mindspore::schema::FftImag *>(obj);
30990 + auto ptr = reinterpret_cast<const mindspore::schema::Flatten *>(obj);
30994 + auto ptr = reinterpret_cast<const mindspore::schema::FlattenGrad *>(obj);
30998 + auto ptr = reinterpret_cast<const mindspore::schema::Floor *>(obj);
31002 + auto ptr = reinterpret_cast<const mindspore::schema::FloorDiv *>(obj);
31006 + auto ptr = reinterpret_cast<const mindspore::schema::FloorMod *>(obj);
31010 + auto ptr = reinterpret_cast<const mindspore::schema::Fill *>(obj);
31014 + auto ptr = reinterpret_cast<const mindspore::schema::FullConnection *>(obj);
31018 + auto ptr = reinterpret_cast<const mindspore::schema::FusedBatchNorm *>(obj);
31022 + auto ptr = reinterpret_cast<const mindspore::schema::Gather *>(obj);
31026 + auto ptr = reinterpret_cast<const mindspore::schema::GatherNd *>(obj);
31030 + auto ptr = reinterpret_cast<const mindspore::schema::Greater *>(obj);
31034 + auto ptr = reinterpret_cast<const mindspore::schema::GreaterEqual *>(obj);
31038 + auto ptr = reinterpret_cast<const mindspore::schema::HashtableLookup *>(obj);
31042 + auto ptr = reinterpret_cast<const mindspore::schema::InstanceNorm *>(obj);
31046 + auto ptr = reinterpret_cast<const mindspore::schema::LayerNormFusion *>(obj);
31050 + auto ptr = reinterpret_cast<const mindspore::schema::LeakyRelu *>(obj);
31054 + auto ptr = reinterpret_cast<const mindspore::schema::Less *>(obj);
31058 + auto ptr = reinterpret_cast<const mindspore::schema::LessEqual *>(obj);
31062 + auto ptr = reinterpret_cast<const mindspore::schema::Log *>(obj);
31066 + auto ptr = reinterpret_cast<const mindspore::schema::LogGrad *>(obj);
31070 + auto ptr = reinterpret_cast<const mindspore::schema::LogicalAnd *>(obj);
31074 + auto ptr = reinterpret_cast<const mindspore::schema::LogicalNot *>(obj);
31078 + auto ptr = reinterpret_cast<const mindspore::schema::LogicalOr *>(obj);
31082 + auto ptr = reinterpret_cast<const mindspore::schema::LpNormalization *>(obj);
31086 + auto ptr = reinterpret_cast<const mindspore::schema::LRN *>(obj);
31090 + auto ptr = reinterpret_cast<const mindspore::schema::LshProjection *>(obj);
31094 + auto ptr = reinterpret_cast<const mindspore::schema::LSTM *>(obj);
31098 + auto ptr = reinterpret_cast<const mindspore::schema::L2NormalizeFusion *>(obj);
31102 + auto ptr = reinterpret_cast<const mindspore::schema::MatMulFusion *>(obj);
31106 + auto ptr = reinterpret_cast<const mindspore::schema::Maximum *>(obj);
31110 + auto ptr = reinterpret_cast<const mindspore::schema::MaximumGrad *>(obj);
31114 + auto ptr = reinterpret_cast<const mindspore::schema::MaxPoolFusion *>(obj);
31118 + auto ptr = reinterpret_cast<const mindspore::schema::MaxPoolGrad *>(obj);
31122 + auto ptr = reinterpret_cast<const mindspore::schema::SwitchLayer *>(obj);
31126 + auto ptr = reinterpret_cast<const mindspore::schema::Mfcc *>(obj);
31130 + auto ptr = reinterpret_cast<const mindspore::schema::Minimum *>(obj);
31134 + auto ptr = reinterpret_cast<const mindspore::schema::MinimumGrad *>(obj);
31138 + auto ptr = reinterpret_cast<const mindspore::schema::Mod *>(obj);
31142 + auto ptr = reinterpret_cast<const mindspore::schema::MulFusion *>(obj);
31146 + auto ptr = reinterpret_cast<const mindspore::schema::MulGrad *>(obj);
31150 + auto ptr = reinterpret_cast<const mindspore::schema::Neg *>(obj);
31154 + auto ptr = reinterpret_cast<const mindspore::schema::NegGrad *>(obj);
31158 + auto ptr = reinterpret_cast<const mindspore::schema::NotEqual *>(obj);
31162 + auto ptr = reinterpret_cast<const mindspore::schema::NonMaxSuppression *>(obj);
31166 + auto ptr = reinterpret_cast<const mindspore::schema::OneHot *>(obj);
31170 + auto ptr = reinterpret_cast<const mindspore::schema::OnesLike *>(obj);
31174 + auto ptr = reinterpret_cast<const mindspore::schema::PadFusion *>(obj);
31178 + auto ptr = reinterpret_cast<const mindspore::schema::PartialFusion *>(obj);
31182 + auto ptr = reinterpret_cast<const mindspore::schema::PowerGrad *>(obj);
31186 + auto ptr = reinterpret_cast<const mindspore::schema::PowFusion *>(obj);
31190 + auto ptr = reinterpret_cast<const mindspore::schema::PriorBox *>(obj);
31194 + auto ptr = reinterpret_cast<const mindspore::schema::PReLUFusion *>(obj);
31198 + auto ptr = reinterpret_cast<const mindspore::schema::QuantDTypeCast *>(obj);
31202 + auto ptr = reinterpret_cast<const mindspore::schema::Rank *>(obj);
31206 + auto ptr = reinterpret_cast<const mindspore::schema::Range *>(obj);
31210 + auto ptr = reinterpret_cast<const mindspore::schema::Reciprocal *>(obj);
31214 + auto ptr = reinterpret_cast<const mindspore::schema::RealDiv *>(obj);
31218 + auto ptr = reinterpret_cast<const mindspore::schema::ReduceFusion *>(obj);
31222 + auto ptr = reinterpret_cast<const mindspore::schema::Reshape *>(obj);
31226 + auto ptr = reinterpret_cast<const mindspore::schema::Resize *>(obj);
31230 + auto ptr = reinterpret_cast<const mindspore::schema::ReverseSequence *>(obj);
31234 + auto ptr = reinterpret_cast<const mindspore::schema::ReverseV2 *>(obj);
31238 + auto ptr = reinterpret_cast<const mindspore::schema::Rfft *>(obj);
31242 + auto ptr = reinterpret_cast<const mindspore::schema::ROIPooling *>(obj);
31246 + auto ptr = reinterpret_cast<const mindspore::schema::Round *>(obj);
31250 + auto ptr = reinterpret_cast<const mindspore::schema::Rsqrt *>(obj);
31254 + auto ptr = reinterpret_cast<const mindspore::schema::ScaleFusion *>(obj);
31258 + auto ptr = reinterpret_cast<const mindspore::schema::ScatterNd *>(obj);
31262 + auto ptr = reinterpret_cast<const mindspore::schema::SGD *>(obj);
31266 + auto ptr = reinterpret_cast<const mindspore::schema::Shape *>(obj);
31270 + auto ptr = reinterpret_cast<const mindspore::schema::SigmoidCrossEntropyWithLogits *>(obj);
31274 + auto ptr = reinterpret_cast<const mindspore::schema::SigmoidCrossEntropyWithLogitsGrad *>(ob…
31278 + auto ptr = reinterpret_cast<const mindspore::schema::Sin *>(obj);
31282 + auto ptr = reinterpret_cast<const mindspore::schema::SkipGram *>(obj);
31286 + auto ptr = reinterpret_cast<const mindspore::schema::SliceFusion *>(obj);
31290 + auto ptr = reinterpret_cast<const mindspore::schema::SmoothL1Loss *>(obj);
31294 + auto ptr = reinterpret_cast<const mindspore::schema::SmoothL1LossGrad *>(obj);
31298 + auto ptr = reinterpret_cast<const mindspore::schema::Softmax *>(obj);
31302 + auto ptr = reinterpret_cast<const mindspore::schema::SoftmaxCrossEntropyWithLogits *>(obj);
31306 + auto ptr = reinterpret_cast<const mindspore::schema::SpaceToBatch *>(obj);
31310 + auto ptr = reinterpret_cast<const mindspore::schema::SpaceToBatchND *>(obj);
31314 + auto ptr = reinterpret_cast<const mindspore::schema::SpaceToDepth *>(obj);
31318 + auto ptr = reinterpret_cast<const mindspore::schema::SparseSoftmaxCrossEntropyWithLogits *>(…
31322 + auto ptr = reinterpret_cast<const mindspore::schema::SparseToDense *>(obj);
31326 + auto ptr = reinterpret_cast<const mindspore::schema::Split *>(obj);
31330 + auto ptr = reinterpret_cast<const mindspore::schema::Sqrt *>(obj);
31334 + auto ptr = reinterpret_cast<const mindspore::schema::Squeeze *>(obj);
31338 + auto ptr = reinterpret_cast<const mindspore::schema::Square *>(obj);
31342 + auto ptr = reinterpret_cast<const mindspore::schema::SquaredDifference *>(obj);
31346 + auto ptr = reinterpret_cast<const mindspore::schema::Stack *>(obj);
31350 + auto ptr = reinterpret_cast<const mindspore::schema::StridedSlice *>(obj);
31354 + auto ptr = reinterpret_cast<const mindspore::schema::SubFusion *>(obj);
31358 + auto ptr = reinterpret_cast<const mindspore::schema::SubGrad *>(obj);
31362 + auto ptr = reinterpret_cast<const mindspore::schema::Switch *>(obj);
31366 + auto ptr = reinterpret_cast<const mindspore::schema::TensorListFromTensor *>(obj);
31370 + auto ptr = reinterpret_cast<const mindspore::schema::TensorListGetItem *>(obj);
31374 + auto ptr = reinterpret_cast<const mindspore::schema::TensorListReserve *>(obj);
31378 + auto ptr = reinterpret_cast<const mindspore::schema::TensorListSetItem *>(obj);
31382 + auto ptr = reinterpret_cast<const mindspore::schema::TensorListStack *>(obj);
31386 + auto ptr = reinterpret_cast<const mindspore::schema::TileFusion *>(obj);
31390 + auto ptr = reinterpret_cast<const mindspore::schema::TopKFusion *>(obj);
31394 + auto ptr = reinterpret_cast<const mindspore::schema::Transpose *>(obj);
31398 + auto ptr = reinterpret_cast<const mindspore::schema::Unique *>(obj);
31402 + auto ptr = reinterpret_cast<const mindspore::schema::UnsortedSegmentSum *>(obj);
31406 + auto ptr = reinterpret_cast<const mindspore::schema::Unsqueeze *>(obj);
31410 + auto ptr = reinterpret_cast<const mindspore::schema::Unstack *>(obj);
31414 + auto ptr = reinterpret_cast<const mindspore::schema::LSTMGrad *>(obj);
31418 + auto ptr = reinterpret_cast<const mindspore::schema::Where *>(obj);
31422 + auto ptr = reinterpret_cast<const mindspore::schema::ZerosLike *>(obj);
31426 + auto ptr = reinterpret_cast<const mindspore::schema::Select *>(obj);
31430 + auto ptr = reinterpret_cast<const mindspore::schema::ScatterNdUpdate *>(obj);
31434 + auto ptr = reinterpret_cast<const mindspore::schema::GRU *>(obj);
31438 + auto ptr = reinterpret_cast<const mindspore::schema::NonZero *>(obj);
31442 + auto ptr = reinterpret_cast<const mindspore::schema::InvertPermutation *>(obj);
31446 + auto ptr = reinterpret_cast<const mindspore::schema::Size *>(obj);
31450 + auto ptr = reinterpret_cast<const mindspore::schema::RandomStandardNormal *>(obj);
31454 + auto ptr = reinterpret_cast<const mindspore::schema::CropAndResize *>(obj);
31458 + auto ptr = reinterpret_cast<const mindspore::schema::Erf *>(obj);
31462 + auto ptr = reinterpret_cast<const mindspore::schema::StridedSliceGrad *>(obj);
31466 + auto ptr = reinterpret_cast<const mindspore::schema::IsFinite *>(obj);
31470 + auto ptr = reinterpret_cast<const mindspore::schema::LinSpace *>(obj);
31474 + auto ptr = reinterpret_cast<const mindspore::schema::UniformReal *>(obj);
31478 + auto ptr = reinterpret_cast<const mindspore::schema::AbsGrad *>(obj);
31482 + auto ptr = reinterpret_cast<const mindspore::schema::RsqrtGrad *>(obj);
31486 + auto ptr = reinterpret_cast<const mindspore::schema::SqrtGrad *>(obj);
31490 + auto ptr = reinterpret_cast<const mindspore::schema::LayerNormGrad *>(obj);
31494 + auto ptr = reinterpret_cast<const mindspore::schema::ResizeGrad *>(obj);
31498 + auto ptr = reinterpret_cast<const mindspore::schema::Splice *>(obj);
31502 + auto ptr = reinterpret_cast<const mindspore::schema::LogSoftmax *>(obj);
31506 + auto ptr = reinterpret_cast<const mindspore::schema::Call *>(obj);
31510 + auto ptr = reinterpret_cast<const mindspore::schema::Custom *>(obj);
31514 + auto ptr = reinterpret_cast<const mindspore::schema::CumSum *>(obj);
31518 + auto ptr = reinterpret_cast<const mindspore::schema::SplitWithOverlap *>(obj);
31522 + auto ptr = reinterpret_cast<const mindspore::schema::GenOP *>(obj);
31526 + auto ptr = reinterpret_cast<const mindspore::schema::RaggedRange *>(obj);
31530 + auto ptr = reinterpret_cast<const mindspore::schema::GLU *>(obj);
31534 + auto ptr = reinterpret_cast<const mindspore::schema::TensorArray *>(obj);
31538 + auto ptr = reinterpret_cast<const mindspore::schema::TensorArrayRead *>(obj);
31542 + auto ptr = reinterpret_cast<const mindspore::schema::TensorArrayWrite *>(obj);
31546 + auto ptr = reinterpret_cast<const mindspore::schema::Affine *>(obj);
31550 + auto ptr = reinterpret_cast<const mindspore::schema::AllGather *>(obj);
31554 + auto ptr = reinterpret_cast<const mindspore::schema::ReduceScatter *>(obj);
31558 + auto ptr = reinterpret_cast<const mindspore::schema::DynamicQuant *>(obj);
31562 + auto ptr = reinterpret_cast<const mindspore::schema::LSTMGradData *>(obj);
31566 + auto ptr = reinterpret_cast<const mindspore::schema::LSTMGradWeight *>(obj);
31570 + auto ptr = reinterpret_cast<const mindspore::schema::RandomNormal *>(obj);
31574 + auto ptr = reinterpret_cast<const mindspore::schema::NLLLoss *>(obj);
31578 + auto ptr = reinterpret_cast<const mindspore::schema::NLLLossGrad *>(obj);
31582 + auto ptr = reinterpret_cast<const mindspore::schema::FormatTranspose *>(obj);
31586 + auto ptr = reinterpret_cast<const mindspore::schema::GatherD *>(obj);
31590 + auto ptr = reinterpret_cast<const mindspore::schema::GroupNormFusion *>(obj);
31612 + auto ptr = reinterpret_cast<const mindspore::schema::Abs *>(obj);
31616 + auto ptr = reinterpret_cast<const mindspore::schema::Activation *>(obj);
31620 + auto ptr = reinterpret_cast<const mindspore::schema::ActivationGrad *>(obj);
31624 + auto ptr = reinterpret_cast<const mindspore::schema::Adam *>(obj);
31628 + auto ptr = reinterpret_cast<const mindspore::schema::AddFusion *>(obj);
31632 + auto ptr = reinterpret_cast<const mindspore::schema::AdderFusion *>(obj);
31636 + auto ptr = reinterpret_cast<const mindspore::schema::AddGrad *>(obj);
31640 + auto ptr = reinterpret_cast<const mindspore::schema::AddN *>(obj);
31644 + auto ptr = reinterpret_cast<const mindspore::schema::All *>(obj);
31648 + auto ptr = reinterpret_cast<const mindspore::schema::ApplyMomentum *>(obj);
31652 + auto ptr = reinterpret_cast<const mindspore::schema::ArgMaxFusion *>(obj);
31656 + auto ptr = reinterpret_cast<const mindspore::schema::ArgMinFusion *>(obj);
31660 + auto ptr = reinterpret_cast<const mindspore::schema::Assert *>(obj);
31664 + auto ptr = reinterpret_cast<const mindspore::schema::Assign *>(obj);
31668 + auto ptr = reinterpret_cast<const mindspore::schema::AssignAdd *>(obj);
31672 + auto ptr = reinterpret_cast<const mindspore::schema::AudioSpectrogram *>(obj);
31676 + auto ptr = reinterpret_cast<const mindspore::schema::AvgPoolFusion *>(obj);
31680 + auto ptr = reinterpret_cast<const mindspore::schema::AvgPoolGrad *>(obj);
31684 + auto ptr = reinterpret_cast<const mindspore::schema::BatchNorm *>(obj);
31688 + auto ptr = reinterpret_cast<const mindspore::schema::BatchNormGrad *>(obj);
31692 + auto ptr = reinterpret_cast<const mindspore::schema::BatchToSpace *>(obj);
31696 + auto ptr = reinterpret_cast<const mindspore::schema::BatchToSpaceND *>(obj);
31700 + auto ptr = reinterpret_cast<const mindspore::schema::BiasAdd *>(obj);
31704 + auto ptr = reinterpret_cast<const mindspore::schema::BinaryCrossEntropy *>(obj);
31708 + auto ptr = reinterpret_cast<const mindspore::schema::BinaryCrossEntropyGrad *>(obj);
31712 + auto ptr = reinterpret_cast<const mindspore::schema::BiasAddGrad *>(obj);
31716 + auto ptr = reinterpret_cast<const mindspore::schema::BroadcastTo *>(obj);
31720 + auto ptr = reinterpret_cast<const mindspore::schema::Cast *>(obj);
31724 + auto ptr = reinterpret_cast<const mindspore::schema::Ceil *>(obj);
31728 + auto ptr = reinterpret_cast<const mindspore::schema::Clip *>(obj);
31732 + auto ptr = reinterpret_cast<const mindspore::schema::Concat *>(obj);
31736 + auto ptr = reinterpret_cast<const mindspore::schema::Attention *>(obj);
31740 + auto ptr = reinterpret_cast<const mindspore::schema::Conv2DBackpropFilterFusion *>(obj);
31744 + auto ptr = reinterpret_cast<const mindspore::schema::Conv2DBackpropInputFusion *>(obj);
31748 + auto ptr = reinterpret_cast<const mindspore::schema::Conv2DFusion *>(obj);
31752 + auto ptr = reinterpret_cast<const mindspore::schema::Conv2dTransposeFusion *>(obj);
31756 + auto ptr = reinterpret_cast<const mindspore::schema::Cos *>(obj);
31760 + auto ptr = reinterpret_cast<const mindspore::schema::ConstantOfShape *>(obj);
31764 + auto ptr = reinterpret_cast<const mindspore::schema::Crop *>(obj);
31768 + auto ptr = reinterpret_cast<const mindspore::schema::CustomExtractFeatures *>(obj);
31772 + auto ptr = reinterpret_cast<const mindspore::schema::CustomNormalize *>(obj);
31776 + auto ptr = reinterpret_cast<const mindspore::schema::CustomPredict *>(obj);
31780 + auto ptr = reinterpret_cast<const mindspore::schema::DeConv2DGradFilter *>(obj);
31784 + auto ptr = reinterpret_cast<const mindspore::schema::Depend *>(obj);
31788 + auto ptr = reinterpret_cast<const mindspore::schema::DepthToSpace *>(obj);
31792 + auto ptr = reinterpret_cast<const mindspore::schema::DetectionPostProcess *>(obj);
31796 + auto ptr = reinterpret_cast<const mindspore::schema::DivFusion *>(obj);
31800 + auto ptr = reinterpret_cast<const mindspore::schema::DivGrad *>(obj);
31804 + auto ptr = reinterpret_cast<const mindspore::schema::Dropout *>(obj);
31808 + auto ptr = reinterpret_cast<const mindspore::schema::DropoutGrad *>(obj);
31812 + auto ptr = reinterpret_cast<const mindspore::schema::Elu *>(obj);
31816 + auto ptr = reinterpret_cast<const mindspore::schema::Eltwise *>(obj);
31820 + auto ptr = reinterpret_cast<const mindspore::schema::Equal *>(obj);
31824 + auto ptr = reinterpret_cast<const mindspore::schema::EmbeddingLookupFusion *>(obj);
31828 + auto ptr = reinterpret_cast<const mindspore::schema::ExpFusion *>(obj);
31832 + auto ptr = reinterpret_cast<const mindspore::schema::ExpandDims *>(obj);
31836 + auto ptr = reinterpret_cast<const mindspore::schema::FakeQuantWithMinMaxVars *>(obj);
31840 + auto ptr = reinterpret_cast<const mindspore::schema::FakeQuantWithMinMaxVarsPerChannel *>(ob…
31844 + auto ptr = reinterpret_cast<const mindspore::schema::FftReal *>(obj);
31848 + auto ptr = reinterpret_cast<const mindspore::schema::FftImag *>(obj);
31852 + auto ptr = reinterpret_cast<const mindspore::schema::Flatten *>(obj);
31856 + auto ptr = reinterpret_cast<const mindspore::schema::FlattenGrad *>(obj);
31860 + auto ptr = reinterpret_cast<const mindspore::schema::Floor *>(obj);
31864 + auto ptr = reinterpret_cast<const mindspore::schema::FloorDiv *>(obj);
31868 + auto ptr = reinterpret_cast<const mindspore::schema::FloorMod *>(obj);
31872 + auto ptr = reinterpret_cast<const mindspore::schema::Fill *>(obj);
31876 + auto ptr = reinterpret_cast<const mindspore::schema::FullConnection *>(obj);
31880 + auto ptr = reinterpret_cast<const mindspore::schema::FusedBatchNorm *>(obj);
31884 + auto ptr = reinterpret_cast<const mindspore::schema::Gather *>(obj);
31888 + auto ptr = reinterpret_cast<const mindspore::schema::GatherNd *>(obj);
31892 + auto ptr = reinterpret_cast<const mindspore::schema::Greater *>(obj);
31896 + auto ptr = reinterpret_cast<const mindspore::schema::GreaterEqual *>(obj);
31900 + auto ptr = reinterpret_cast<const mindspore::schema::HashtableLookup *>(obj);
31904 + auto ptr = reinterpret_cast<const mindspore::schema::InstanceNorm *>(obj);
31908 + auto ptr = reinterpret_cast<const mindspore::schema::LayerNormFusion *>(obj);
31912 + auto ptr = reinterpret_cast<const mindspore::schema::LeakyRelu *>(obj);
31916 + auto ptr = reinterpret_cast<const mindspore::schema::Less *>(obj);
31920 + auto ptr = reinterpret_cast<const mindspore::schema::LessEqual *>(obj);
31924 + auto ptr = reinterpret_cast<const mindspore::schema::Log *>(obj);
31928 + auto ptr = reinterpret_cast<const mindspore::schema::LogGrad *>(obj);
31932 + auto ptr = reinterpret_cast<const mindspore::schema::LogicalAnd *>(obj);
31936 + auto ptr = reinterpret_cast<const mindspore::schema::LogicalNot *>(obj);
31940 + auto ptr = reinterpret_cast<const mindspore::schema::LogicalOr *>(obj);
31944 + auto ptr = reinterpret_cast<const mindspore::schema::LpNormalization *>(obj);
31948 + auto ptr = reinterpret_cast<const mindspore::schema::LRN *>(obj);
31952 + auto ptr = reinterpret_cast<const mindspore::schema::LshProjection *>(obj);
31956 + auto ptr = reinterpret_cast<const mindspore::schema::LSTM *>(obj);
31960 + auto ptr = reinterpret_cast<const mindspore::schema::L2NormalizeFusion *>(obj);
31964 + auto ptr = reinterpret_cast<const mindspore::schema::MatMulFusion *>(obj);
31968 + auto ptr = reinterpret_cast<const mindspore::schema::Maximum *>(obj);
31972 + auto ptr = reinterpret_cast<const mindspore::schema::MaximumGrad *>(obj);
31976 + auto ptr = reinterpret_cast<const mindspore::schema::MaxPoolFusion *>(obj);
31980 + auto ptr = reinterpret_cast<const mindspore::schema::MaxPoolGrad *>(obj);
31984 + auto ptr = reinterpret_cast<const mindspore::schema::SwitchLayer *>(obj);
31988 + auto ptr = reinterpret_cast<const mindspore::schema::Mfcc *>(obj);
31992 + auto ptr = reinterpret_cast<const mindspore::schema::Minimum *>(obj);
31996 + auto ptr = reinterpret_cast<const mindspore::schema::MinimumGrad *>(obj);
32000 + auto ptr = reinterpret_cast<const mindspore::schema::Mod *>(obj);
32004 + auto ptr = reinterpret_cast<const mindspore::schema::MulFusion *>(obj);
32008 + auto ptr = reinterpret_cast<const mindspore::schema::MulGrad *>(obj);
32012 + auto ptr = reinterpret_cast<const mindspore::schema::Neg *>(obj);
32016 + auto ptr = reinterpret_cast<const mindspore::schema::NegGrad *>(obj);
32020 + auto ptr = reinterpret_cast<const mindspore::schema::NotEqual *>(obj);
32024 + auto ptr = reinterpret_cast<const mindspore::schema::NonMaxSuppression *>(obj);
32028 + auto ptr = reinterpret_cast<const mindspore::schema::OneHot *>(obj);
32032 + auto ptr = reinterpret_cast<const mindspore::schema::OnesLike *>(obj);
32036 + auto ptr = reinterpret_cast<const mindspore::schema::PadFusion *>(obj);
32040 + auto ptr = reinterpret_cast<const mindspore::schema::PartialFusion *>(obj);
32044 + auto ptr = reinterpret_cast<const mindspore::schema::PowerGrad *>(obj);
32048 + auto ptr = reinterpret_cast<const mindspore::schema::PowFusion *>(obj);
32052 + auto ptr = reinterpret_cast<const mindspore::schema::PriorBox *>(obj);
32056 + auto ptr = reinterpret_cast<const mindspore::schema::PReLUFusion *>(obj);
32060 + auto ptr = reinterpret_cast<const mindspore::schema::QuantDTypeCast *>(obj);
32064 + auto ptr = reinterpret_cast<const mindspore::schema::Rank *>(obj);
32068 + auto ptr = reinterpret_cast<const mindspore::schema::Range *>(obj);
32072 + auto ptr = reinterpret_cast<const mindspore::schema::Reciprocal *>(obj);
32076 + auto ptr = reinterpret_cast<const mindspore::schema::RealDiv *>(obj);
32080 + auto ptr = reinterpret_cast<const mindspore::schema::ReduceFusion *>(obj);
32084 + auto ptr = reinterpret_cast<const mindspore::schema::Reshape *>(obj);
32088 + auto ptr = reinterpret_cast<const mindspore::schema::Resize *>(obj);
32092 + auto ptr = reinterpret_cast<const mindspore::schema::ReverseSequence *>(obj);
32096 + auto ptr = reinterpret_cast<const mindspore::schema::ReverseV2 *>(obj);
32100 + auto ptr = reinterpret_cast<const mindspore::schema::Rfft *>(obj);
32104 + auto ptr = reinterpret_cast<const mindspore::schema::ROIPooling *>(obj);
32108 + auto ptr = reinterpret_cast<const mindspore::schema::Round *>(obj);
32112 + auto ptr = reinterpret_cast<const mindspore::schema::Rsqrt *>(obj);
32116 + auto ptr = reinterpret_cast<const mindspore::schema::ScaleFusion *>(obj);
32120 + auto ptr = reinterpret_cast<const mindspore::schema::ScatterNd *>(obj);
32124 + auto ptr = reinterpret_cast<const mindspore::schema::SGD *>(obj);
32128 + auto ptr = reinterpret_cast<const mindspore::schema::Shape *>(obj);
32132 + auto ptr = reinterpret_cast<const mindspore::schema::SigmoidCrossEntropyWithLogits *>(obj);
32136 + auto ptr = reinterpret_cast<const mindspore::schema::SigmoidCrossEntropyWithLogitsGrad *>(ob…
32140 + auto ptr = reinterpret_cast<const mindspore::schema::Sin *>(obj);
32144 + auto ptr = reinterpret_cast<const mindspore::schema::SkipGram *>(obj);
32148 + auto ptr = reinterpret_cast<const mindspore::schema::SliceFusion *>(obj);
32152 + auto ptr = reinterpret_cast<const mindspore::schema::SmoothL1Loss *>(obj);
32156 + auto ptr = reinterpret_cast<const mindspore::schema::SmoothL1LossGrad *>(obj);
32160 + auto ptr = reinterpret_cast<const mindspore::schema::Softmax *>(obj);
32164 + auto ptr = reinterpret_cast<const mindspore::schema::SoftmaxCrossEntropyWithLogits *>(obj);
32168 + auto ptr = reinterpret_cast<const mindspore::schema::SpaceToBatch *>(obj);
32172 + auto ptr = reinterpret_cast<const mindspore::schema::SpaceToBatchND *>(obj);
32176 + auto ptr = reinterpret_cast<const mindspore::schema::SpaceToDepth *>(obj);
32180 + auto ptr = reinterpret_cast<const mindspore::schema::SparseSoftmaxCrossEntropyWithLogits *>(…
32184 + auto ptr = reinterpret_cast<const mindspore::schema::SparseToDense *>(obj);
32188 + auto ptr = reinterpret_cast<const mindspore::schema::Split *>(obj);
32192 + auto ptr = reinterpret_cast<const mindspore::schema::Sqrt *>(obj);
32196 + auto ptr = reinterpret_cast<const mindspore::schema::Squeeze *>(obj);
32200 + auto ptr = reinterpret_cast<const mindspore::schema::Square *>(obj);
32204 + auto ptr = reinterpret_cast<const mindspore::schema::SquaredDifference *>(obj);
32208 + auto ptr = reinterpret_cast<const mindspore::schema::Stack *>(obj);
32212 + auto ptr = reinterpret_cast<const mindspore::schema::StridedSlice *>(obj);
32216 + auto ptr = reinterpret_cast<const mindspore::schema::SubFusion *>(obj);
32220 + auto ptr = reinterpret_cast<const mindspore::schema::SubGrad *>(obj);
32224 + auto ptr = reinterpret_cast<const mindspore::schema::Switch *>(obj);
32228 + auto ptr = reinterpret_cast<const mindspore::schema::TensorListFromTensor *>(obj);
32232 + auto ptr = reinterpret_cast<const mindspore::schema::TensorListGetItem *>(obj);
32236 + auto ptr = reinterpret_cast<const mindspore::schema::TensorListReserve *>(obj);
32240 + auto ptr = reinterpret_cast<const mindspore::schema::TensorListSetItem *>(obj);
32244 + auto ptr = reinterpret_cast<const mindspore::schema::TensorListStack *>(obj);
32248 + auto ptr = reinterpret_cast<const mindspore::schema::TileFusion *>(obj);
32252 + auto ptr = reinterpret_cast<const mindspore::schema::TopKFusion *>(obj);
32256 + auto ptr = reinterpret_cast<const mindspore::schema::Transpose *>(obj);
32260 + auto ptr = reinterpret_cast<const mindspore::schema::Unique *>(obj);
32264 + auto ptr = reinterpret_cast<const mindspore::schema::UnsortedSegmentSum *>(obj);
32268 + auto ptr = reinterpret_cast<const mindspore::schema::Unsqueeze *>(obj);
32272 + auto ptr = reinterpret_cast<const mindspore::schema::Unstack *>(obj);
32276 + auto ptr = reinterpret_cast<const mindspore::schema::LSTMGrad *>(obj);
32280 + auto ptr = reinterpret_cast<const mindspore::schema::Where *>(obj);
32284 + auto ptr = reinterpret_cast<const mindspore::schema::ZerosLike *>(obj);
32288 + auto ptr = reinterpret_cast<const mindspore::schema::Select *>(obj);
32292 + auto ptr = reinterpret_cast<const mindspore::schema::ScatterNdUpdate *>(obj);
32296 + auto ptr = reinterpret_cast<const mindspore::schema::GRU *>(obj);
32300 + auto ptr = reinterpret_cast<const mindspore::schema::NonZero *>(obj);
32304 + auto ptr = reinterpret_cast<const mindspore::schema::InvertPermutation *>(obj);
32308 + auto ptr = reinterpret_cast<const mindspore::schema::Size *>(obj);
32312 + auto ptr = reinterpret_cast<const mindspore::schema::RandomStandardNormal *>(obj);
32316 + auto ptr = reinterpret_cast<const mindspore::schema::CropAndResize *>(obj);
32320 + auto ptr = reinterpret_cast<const mindspore::schema::Erf *>(obj);
32324 + auto ptr = reinterpret_cast<const mindspore::schema::StridedSliceGrad *>(obj);
32328 + auto ptr = reinterpret_cast<const mindspore::schema::IsFinite *>(obj);
32332 + auto ptr = reinterpret_cast<const mindspore::schema::LinSpace *>(obj);
32336 + auto ptr = reinterpret_cast<const mindspore::schema::UniformReal *>(obj);
32340 + auto ptr = reinterpret_cast<const mindspore::schema::AbsGrad *>(obj);
32344 + auto ptr = reinterpret_cast<const mindspore::schema::RsqrtGrad *>(obj);
32348 + auto ptr = reinterpret_cast<const mindspore::schema::SqrtGrad *>(obj);
32352 + auto ptr = reinterpret_cast<const mindspore::schema::LayerNormGrad *>(obj);
32356 + auto ptr = reinterpret_cast<const mindspore::schema::ResizeGrad *>(obj);
32360 + auto ptr = reinterpret_cast<const mindspore::schema::Splice *>(obj);
32364 + auto ptr = reinterpret_cast<const mindspore::schema::LogSoftmax *>(obj);
32368 + auto ptr = reinterpret_cast<const mindspore::schema::Call *>(obj);
32372 + auto ptr = reinterpret_cast<const mindspore::schema::Custom *>(obj);
32376 + auto ptr = reinterpret_cast<const mindspore::schema::CumSum *>(obj);
32380 + auto ptr = reinterpret_cast<const mindspore::schema::SplitWithOverlap *>(obj);
32384 + auto ptr = reinterpret_cast<const mindspore::schema::GenOP *>(obj);
32388 + auto ptr = reinterpret_cast<const mindspore::schema::RaggedRange *>(obj);
32392 + auto ptr = reinterpret_cast<const mindspore::schema::GLU *>(obj);
32396 + auto ptr = reinterpret_cast<const mindspore::schema::TensorArray *>(obj);
32400 + auto ptr = reinterpret_cast<const mindspore::schema::TensorArrayRead *>(obj);
32404 + auto ptr = reinterpret_cast<const mindspore::schema::TensorArrayWrite *>(obj);
32408 + auto ptr = reinterpret_cast<const mindspore::schema::Affine *>(obj);
32412 + auto ptr = reinterpret_cast<const mindspore::schema::AllGather *>(obj);
32416 + auto ptr = reinterpret_cast<const mindspore::schema::ReduceScatter *>(obj);
32420 + auto ptr = reinterpret_cast<const mindspore::schema::DynamicQuant *>(obj);
32424 + auto ptr = reinterpret_cast<const mindspore::schema::LSTMGradData *>(obj);
32428 + auto ptr = reinterpret_cast<const mindspore::schema::LSTMGradWeight *>(obj);
32432 + auto ptr = reinterpret_cast<const mindspore::schema::RandomNormal *>(obj);
32436 + auto ptr = reinterpret_cast<const mindspore::schema::NLLLoss *>(obj);
32440 + auto ptr = reinterpret_cast<const mindspore::schema::NLLLossGrad *>(obj);
32444 + auto ptr = reinterpret_cast<const mindspore::schema::FormatTranspose *>(obj);
32448 + auto ptr = reinterpret_cast<const mindspore::schema::GatherD *>(obj);
32452 + auto ptr = reinterpret_cast<const mindspore::schema::GroupNormFusion *>(obj);
32462 + auto ptr = reinterpret_cast<const mindspore::schema::AbsT *>(value);
32466 + auto ptr = reinterpret_cast<const mindspore::schema::ActivationT *>(value);
32470 + auto ptr = reinterpret_cast<const mindspore::schema::ActivationGradT *>(value);
32474 + auto ptr = reinterpret_cast<const mindspore::schema::AdamT *>(value);
32478 + auto ptr = reinterpret_cast<const mindspore::schema::AddFusionT *>(value);
32482 + auto ptr = reinterpret_cast<const mindspore::schema::AdderFusionT *>(value);
32486 + auto ptr = reinterpret_cast<const mindspore::schema::AddGradT *>(value);
32490 + auto ptr = reinterpret_cast<const mindspore::schema::AddNT *>(value);
32494 + auto ptr = reinterpret_cast<const mindspore::schema::AllT *>(value);
32498 + auto ptr = reinterpret_cast<const mindspore::schema::ApplyMomentumT *>(value);
32502 + auto ptr = reinterpret_cast<const mindspore::schema::ArgMaxFusionT *>(value);
32506 + auto ptr = reinterpret_cast<const mindspore::schema::ArgMinFusionT *>(value);
32510 + auto ptr = reinterpret_cast<const mindspore::schema::AssertT *>(value);
32514 + auto ptr = reinterpret_cast<const mindspore::schema::AssignT *>(value);
32518 + auto ptr = reinterpret_cast<const mindspore::schema::AssignAddT *>(value);
32522 + auto ptr = reinterpret_cast<const mindspore::schema::AudioSpectrogramT *>(value);
32526 + auto ptr = reinterpret_cast<const mindspore::schema::AvgPoolFusionT *>(value);
32530 + auto ptr = reinterpret_cast<const mindspore::schema::AvgPoolGradT *>(value);
32534 + auto ptr = reinterpret_cast<const mindspore::schema::BatchNormT *>(value);
32538 + auto ptr = reinterpret_cast<const mindspore::schema::BatchNormGradT *>(value);
32542 + auto ptr = reinterpret_cast<const mindspore::schema::BatchToSpaceT *>(value);
32546 + auto ptr = reinterpret_cast<const mindspore::schema::BatchToSpaceNDT *>(value);
32550 + auto ptr = reinterpret_cast<const mindspore::schema::BiasAddT *>(value);
32554 + auto ptr = reinterpret_cast<const mindspore::schema::BinaryCrossEntropyT *>(value);
32558 + auto ptr = reinterpret_cast<const mindspore::schema::BinaryCrossEntropyGradT *>(value);
32562 + auto ptr = reinterpret_cast<const mindspore::schema::BiasAddGradT *>(value);
32566 + auto ptr = reinterpret_cast<const mindspore::schema::BroadcastToT *>(value);
32570 + auto ptr = reinterpret_cast<const mindspore::schema::CastT *>(value);
32574 + auto ptr = reinterpret_cast<const mindspore::schema::CeilT *>(value);
32578 + auto ptr = reinterpret_cast<const mindspore::schema::ClipT *>(value);
32582 + auto ptr = reinterpret_cast<const mindspore::schema::ConcatT *>(value);
32586 + auto ptr = reinterpret_cast<const mindspore::schema::AttentionT *>(value);
32590 + auto ptr = reinterpret_cast<const mindspore::schema::Conv2DBackpropFilterFusionT *>(value);
32594 + auto ptr = reinterpret_cast<const mindspore::schema::Conv2DBackpropInputFusionT *>(value);
32598 + auto ptr = reinterpret_cast<const mindspore::schema::Conv2DFusionT *>(value);
32602 + auto ptr = reinterpret_cast<const mindspore::schema::Conv2dTransposeFusionT *>(value);
32606 + auto ptr = reinterpret_cast<const mindspore::schema::CosT *>(value);
32610 + auto ptr = reinterpret_cast<const mindspore::schema::ConstantOfShapeT *>(value);
32614 + auto ptr = reinterpret_cast<const mindspore::schema::CropT *>(value);
32618 + auto ptr = reinterpret_cast<const mindspore::schema::CustomExtractFeaturesT *>(value);
32622 + auto ptr = reinterpret_cast<const mindspore::schema::CustomNormalizeT *>(value);
32626 + auto ptr = reinterpret_cast<const mindspore::schema::CustomPredictT *>(value);
32630 + auto ptr = reinterpret_cast<const mindspore::schema::DeConv2DGradFilterT *>(value);
32634 + auto ptr = reinterpret_cast<const mindspore::schema::DependT *>(value);
32638 + auto ptr = reinterpret_cast<const mindspore::schema::DepthToSpaceT *>(value);
32642 + auto ptr = reinterpret_cast<const mindspore::schema::DetectionPostProcessT *>(value);
32646 + auto ptr = reinterpret_cast<const mindspore::schema::DivFusionT *>(value);
32650 + auto ptr = reinterpret_cast<const mindspore::schema::DivGradT *>(value);
32654 + auto ptr = reinterpret_cast<const mindspore::schema::DropoutT *>(value);
32658 + auto ptr = reinterpret_cast<const mindspore::schema::DropoutGradT *>(value);
32662 + auto ptr = reinterpret_cast<const mindspore::schema::EluT *>(value);
32666 + auto ptr = reinterpret_cast<const mindspore::schema::EltwiseT *>(value);
32670 + auto ptr = reinterpret_cast<const mindspore::schema::EqualT *>(value);
32674 + auto ptr = reinterpret_cast<const mindspore::schema::EmbeddingLookupFusionT *>(value);
32678 + auto ptr = reinterpret_cast<const mindspore::schema::ExpFusionT *>(value);
32682 + auto ptr = reinterpret_cast<const mindspore::schema::ExpandDimsT *>(value);
32686 + auto ptr = reinterpret_cast<const mindspore::schema::FakeQuantWithMinMaxVarsT *>(value);
32690 + auto ptr = reinterpret_cast<const mindspore::schema::FakeQuantWithMinMaxVarsPerChannelT *>(v…
32694 + auto ptr = reinterpret_cast<const mindspore::schema::FftRealT *>(value);
32698 + auto ptr = reinterpret_cast<const mindspore::schema::FftImagT *>(value);
32702 + auto ptr = reinterpret_cast<const mindspore::schema::FlattenT *>(value);
32706 + auto ptr = reinterpret_cast<const mindspore::schema::FlattenGradT *>(value);
32710 + auto ptr = reinterpret_cast<const mindspore::schema::FloorT *>(value);
32714 + auto ptr = reinterpret_cast<const mindspore::schema::FloorDivT *>(value);
32718 + auto ptr = reinterpret_cast<const mindspore::schema::FloorModT *>(value);
32722 + auto ptr = reinterpret_cast<const mindspore::schema::FillT *>(value);
32726 + auto ptr = reinterpret_cast<const mindspore::schema::FullConnectionT *>(value);
32730 + auto ptr = reinterpret_cast<const mindspore::schema::FusedBatchNormT *>(value);
32734 + auto ptr = reinterpret_cast<const mindspore::schema::GatherT *>(value);
32738 + auto ptr = reinterpret_cast<const mindspore::schema::GatherNdT *>(value);
32742 + auto ptr = reinterpret_cast<const mindspore::schema::GreaterT *>(value);
32746 + auto ptr = reinterpret_cast<const mindspore::schema::GreaterEqualT *>(value);
32750 + auto ptr = reinterpret_cast<const mindspore::schema::HashtableLookupT *>(value);
32754 + auto ptr = reinterpret_cast<const mindspore::schema::InstanceNormT *>(value);
32758 + auto ptr = reinterpret_cast<const mindspore::schema::LayerNormFusionT *>(value);
32762 + auto ptr = reinterpret_cast<const mindspore::schema::LeakyReluT *>(value);
32766 + auto ptr = reinterpret_cast<const mindspore::schema::LessT *>(value);
32770 + auto ptr = reinterpret_cast<const mindspore::schema::LessEqualT *>(value);
32774 + auto ptr = reinterpret_cast<const mindspore::schema::LogT *>(value);
32778 + auto ptr = reinterpret_cast<const mindspore::schema::LogGradT *>(value);
32782 + auto ptr = reinterpret_cast<const mindspore::schema::LogicalAndT *>(value);
32786 + auto ptr = reinterpret_cast<const mindspore::schema::LogicalNotT *>(value);
32790 + auto ptr = reinterpret_cast<const mindspore::schema::LogicalOrT *>(value);
32794 + auto ptr = reinterpret_cast<const mindspore::schema::LpNormalizationT *>(value);
32798 + auto ptr = reinterpret_cast<const mindspore::schema::LRNT *>(value);
32802 + auto ptr = reinterpret_cast<const mindspore::schema::LshProjectionT *>(value);
32806 + auto ptr = reinterpret_cast<const mindspore::schema::LSTMT *>(value);
32810 + auto ptr = reinterpret_cast<const mindspore::schema::L2NormalizeFusionT *>(value);
32814 + auto ptr = reinterpret_cast<const mindspore::schema::MatMulFusionT *>(value);
32818 + auto ptr = reinterpret_cast<const mindspore::schema::MaximumT *>(value);
32822 + auto ptr = reinterpret_cast<const mindspore::schema::MaximumGradT *>(value);
32826 + auto ptr = reinterpret_cast<const mindspore::schema::MaxPoolFusionT *>(value);
32830 + auto ptr = reinterpret_cast<const mindspore::schema::MaxPoolGradT *>(value);
32834 + auto ptr = reinterpret_cast<const mindspore::schema::SwitchLayerT *>(value);
32838 + auto ptr = reinterpret_cast<const mindspore::schema::MfccT *>(value);
32842 + auto ptr = reinterpret_cast<const mindspore::schema::MinimumT *>(value);
32846 + auto ptr = reinterpret_cast<const mindspore::schema::MinimumGradT *>(value);
32850 + auto ptr = reinterpret_cast<const mindspore::schema::ModT *>(value);
32854 + auto ptr = reinterpret_cast<const mindspore::schema::MulFusionT *>(value);
32858 + auto ptr = reinterpret_cast<const mindspore::schema::MulGradT *>(value);
32862 + auto ptr = reinterpret_cast<const mindspore::schema::NegT *>(value);
32866 + auto ptr = reinterpret_cast<const mindspore::schema::NegGradT *>(value);
32870 + auto ptr = reinterpret_cast<const mindspore::schema::NotEqualT *>(value);
32874 + auto ptr = reinterpret_cast<const mindspore::schema::NonMaxSuppressionT *>(value);
32878 + auto ptr = reinterpret_cast<const mindspore::schema::OneHotT *>(value);
32882 + auto ptr = reinterpret_cast<const mindspore::schema::OnesLikeT *>(value);
32886 + auto ptr = reinterpret_cast<const mindspore::schema::PadFusionT *>(value);
32890 + auto ptr = reinterpret_cast<const mindspore::schema::PartialFusionT *>(value);
32894 + auto ptr = reinterpret_cast<const mindspore::schema::PowerGradT *>(value);
32898 + auto ptr = reinterpret_cast<const mindspore::schema::PowFusionT *>(value);
32902 + auto ptr = reinterpret_cast<const mindspore::schema::PriorBoxT *>(value);
32906 + auto ptr = reinterpret_cast<const mindspore::schema::PReLUFusionT *>(value);
32910 + auto ptr = reinterpret_cast<const mindspore::schema::QuantDTypeCastT *>(value);
32914 + auto ptr = reinterpret_cast<const mindspore::schema::RankT *>(value);
32918 + auto ptr = reinterpret_cast<const mindspore::schema::RangeT *>(value);
32922 + auto ptr = reinterpret_cast<const mindspore::schema::ReciprocalT *>(value);
32926 + auto ptr = reinterpret_cast<const mindspore::schema::RealDivT *>(value);
32930 + auto ptr = reinterpret_cast<const mindspore::schema::ReduceFusionT *>(value);
32934 + auto ptr = reinterpret_cast<const mindspore::schema::ReshapeT *>(value);
32938 + auto ptr = reinterpret_cast<const mindspore::schema::ResizeT *>(value);
32942 + auto ptr = reinterpret_cast<const mindspore::schema::ReverseSequenceT *>(value);
32946 + auto ptr = reinterpret_cast<const mindspore::schema::ReverseV2T *>(value);
32950 + auto ptr = reinterpret_cast<const mindspore::schema::RfftT *>(value);
32954 + auto ptr = reinterpret_cast<const mindspore::schema::ROIPoolingT *>(value);
32958 + auto ptr = reinterpret_cast<const mindspore::schema::RoundT *>(value);
32962 + auto ptr = reinterpret_cast<const mindspore::schema::RsqrtT *>(value);
32966 + auto ptr = reinterpret_cast<const mindspore::schema::ScaleFusionT *>(value);
32970 + auto ptr = reinterpret_cast<const mindspore::schema::ScatterNdT *>(value);
32974 + auto ptr = reinterpret_cast<const mindspore::schema::SGDT *>(value);
32978 + auto ptr = reinterpret_cast<const mindspore::schema::ShapeT *>(value);
32982 + auto ptr = reinterpret_cast<const mindspore::schema::SigmoidCrossEntropyWithLogitsT *>(value…
32986 + auto ptr = reinterpret_cast<const mindspore::schema::SigmoidCrossEntropyWithLogitsGradT *>(v…
32990 + auto ptr = reinterpret_cast<const mindspore::schema::SinT *>(value);
32994 + auto ptr = reinterpret_cast<const mindspore::schema::SkipGramT *>(value);
32998 + auto ptr = reinterpret_cast<const mindspore::schema::SliceFusionT *>(value);
33002 + auto ptr = reinterpret_cast<const mindspore::schema::SmoothL1LossT *>(value);
33006 + auto ptr = reinterpret_cast<const mindspore::schema::SmoothL1LossGradT *>(value);
33010 + auto ptr = reinterpret_cast<const mindspore::schema::SoftmaxT *>(value);
33014 + auto ptr = reinterpret_cast<const mindspore::schema::SoftmaxCrossEntropyWithLogitsT *>(value…
33018 + auto ptr = reinterpret_cast<const mindspore::schema::SpaceToBatchT *>(value);
33022 + auto ptr = reinterpret_cast<const mindspore::schema::SpaceToBatchNDT *>(value);
33026 + auto ptr = reinterpret_cast<const mindspore::schema::SpaceToDepthT *>(value);
33030 + auto ptr = reinterpret_cast<const mindspore::schema::SparseSoftmaxCrossEntropyWithLogitsT *>…
33034 + auto ptr = reinterpret_cast<const mindspore::schema::SparseToDenseT *>(value);
33038 + auto ptr = reinterpret_cast<const mindspore::schema::SplitT *>(value);
33042 + auto ptr = reinterpret_cast<const mindspore::schema::SqrtT *>(value);
33046 + auto ptr = reinterpret_cast<const mindspore::schema::SqueezeT *>(value);
33050 + auto ptr = reinterpret_cast<const mindspore::schema::SquareT *>(value);
33054 + auto ptr = reinterpret_cast<const mindspore::schema::SquaredDifferenceT *>(value);
33058 + auto ptr = reinterpret_cast<const mindspore::schema::StackT *>(value);
33062 + auto ptr = reinterpret_cast<const mindspore::schema::StridedSliceT *>(value);
33066 + auto ptr = reinterpret_cast<const mindspore::schema::SubFusionT *>(value);
33070 + auto ptr = reinterpret_cast<const mindspore::schema::SubGradT *>(value);
33074 + auto ptr = reinterpret_cast<const mindspore::schema::SwitchT *>(value);
33078 + auto ptr = reinterpret_cast<const mindspore::schema::TensorListFromTensorT *>(value);
33082 + auto ptr = reinterpret_cast<const mindspore::schema::TensorListGetItemT *>(value);
33086 + auto ptr = reinterpret_cast<const mindspore::schema::TensorListReserveT *>(value);
33090 + auto ptr = reinterpret_cast<const mindspore::schema::TensorListSetItemT *>(value);
33094 + auto ptr = reinterpret_cast<const mindspore::schema::TensorListStackT *>(value);
33098 + auto ptr = reinterpret_cast<const mindspore::schema::TileFusionT *>(value);
33102 + auto ptr = reinterpret_cast<const mindspore::schema::TopKFusionT *>(value);
33106 + auto ptr = reinterpret_cast<const mindspore::schema::TransposeT *>(value);
33110 + auto ptr = reinterpret_cast<const mindspore::schema::UniqueT *>(value);
33114 + auto ptr = reinterpret_cast<const mindspore::schema::UnsortedSegmentSumT *>(value);
33118 + auto ptr = reinterpret_cast<const mindspore::schema::UnsqueezeT *>(value);
33122 + auto ptr = reinterpret_cast<const mindspore::schema::UnstackT *>(value);
33126 + auto ptr = reinterpret_cast<const mindspore::schema::LSTMGradT *>(value);
33130 + auto ptr = reinterpret_cast<const mindspore::schema::WhereT *>(value);
33134 + auto ptr = reinterpret_cast<const mindspore::schema::ZerosLikeT *>(value);
33138 + auto ptr = reinterpret_cast<const mindspore::schema::SelectT *>(value);
33142 + auto ptr = reinterpret_cast<const mindspore::schema::ScatterNdUpdateT *>(value);
33146 + auto ptr = reinterpret_cast<const mindspore::schema::GRUT *>(value);
33150 + auto ptr = reinterpret_cast<const mindspore::schema::NonZeroT *>(value);
33154 + auto ptr = reinterpret_cast<const mindspore::schema::InvertPermutationT *>(value);
33158 + auto ptr = reinterpret_cast<const mindspore::schema::SizeT *>(value);
33162 + auto ptr = reinterpret_cast<const mindspore::schema::RandomStandardNormalT *>(value);
33166 + auto ptr = reinterpret_cast<const mindspore::schema::CropAndResizeT *>(value);
33170 + auto ptr = reinterpret_cast<const mindspore::schema::ErfT *>(value);
33174 + auto ptr = reinterpret_cast<const mindspore::schema::StridedSliceGradT *>(value);
33178 + auto ptr = reinterpret_cast<const mindspore::schema::IsFiniteT *>(value);
33182 + auto ptr = reinterpret_cast<const mindspore::schema::LinSpaceT *>(value);
33186 + auto ptr = reinterpret_cast<const mindspore::schema::UniformRealT *>(value);
33190 + auto ptr = reinterpret_cast<const mindspore::schema::AbsGradT *>(value);
33194 + auto ptr = reinterpret_cast<const mindspore::schema::RsqrtGradT *>(value);
33198 + auto ptr = reinterpret_cast<const mindspore::schema::SqrtGradT *>(value);
33202 + auto ptr = reinterpret_cast<const mindspore::schema::LayerNormGradT *>(value);
33206 + auto ptr = reinterpret_cast<const mindspore::schema::ResizeGradT *>(value);
33210 + auto ptr = reinterpret_cast<const mindspore::schema::SpliceT *>(value);
33214 + auto ptr = reinterpret_cast<const mindspore::schema::LogSoftmaxT *>(value);
33218 + auto ptr = reinterpret_cast<const mindspore::schema::CallT *>(value);
33222 + auto ptr = reinterpret_cast<const mindspore::schema::CustomT *>(value);
33226 + auto ptr = reinterpret_cast<const mindspore::schema::CumSumT *>(value);
33230 + auto ptr = reinterpret_cast<const mindspore::schema::SplitWithOverlapT *>(value);
33234 + auto ptr = reinterpret_cast<const mindspore::schema::GenOPT *>(value);
33238 + auto ptr = reinterpret_cast<const mindspore::schema::RaggedRangeT *>(value);
33242 + auto ptr = reinterpret_cast<const mindspore::schema::GLUT *>(value);
33246 + auto ptr = reinterpret_cast<const mindspore::schema::TensorArrayT *>(value);
33250 + auto ptr = reinterpret_cast<const mindspore::schema::TensorArrayReadT *>(value);
33254 + auto ptr = reinterpret_cast<const mindspore::schema::TensorArrayWriteT *>(value);
33258 + auto ptr = reinterpret_cast<const mindspore::schema::AffineT *>(value);
33262 + auto ptr = reinterpret_cast<const mindspore::schema::AllGatherT *>(value);
33266 + auto ptr = reinterpret_cast<const mindspore::schema::ReduceScatterT *>(value);
33270 + auto ptr = reinterpret_cast<const mindspore::schema::DynamicQuantT *>(value);
33274 + auto ptr = reinterpret_cast<const mindspore::schema::LSTMGradDataT *>(value);
33278 + auto ptr = reinterpret_cast<const mindspore::schema::LSTMGradWeightT *>(value);
33282 + auto ptr = reinterpret_cast<const mindspore::schema::RandomNormalT *>(value);
33286 + auto ptr = reinterpret_cast<const mindspore::schema::NLLLossT *>(value);
33290 + auto ptr = reinterpret_cast<const mindspore::schema::NLLLossGradT *>(value);
33294 + auto ptr = reinterpret_cast<const mindspore::schema::FormatTransposeT *>(value);
33298 + auto ptr = reinterpret_cast<const mindspore::schema::GatherDT *>(value);
33302 + auto ptr = reinterpret_cast<const mindspore::schema::GroupNormFusionT *>(value);
34163 + auto ptr = reinterpret_cast<mindspore::schema::AbsT *>(value);
34168 + auto ptr = reinterpret_cast<mindspore::schema::ActivationT *>(value);
34173 + auto ptr = reinterpret_cast<mindspore::schema::ActivationGradT *>(value);
34178 + auto ptr = reinterpret_cast<mindspore::schema::AdamT *>(value);
34183 + auto ptr = reinterpret_cast<mindspore::schema::AddFusionT *>(value);
34188 + auto ptr = reinterpret_cast<mindspore::schema::AdderFusionT *>(value);
34193 + auto ptr = reinterpret_cast<mindspore::schema::AddGradT *>(value);
34198 + auto ptr = reinterpret_cast<mindspore::schema::AddNT *>(value);
34203 + auto ptr = reinterpret_cast<mindspore::schema::AllT *>(value);
34208 + auto ptr = reinterpret_cast<mindspore::schema::ApplyMomentumT *>(value);
34213 + auto ptr = reinterpret_cast<mindspore::schema::ArgMaxFusionT *>(value);
34218 + auto ptr = reinterpret_cast<mindspore::schema::ArgMinFusionT *>(value);
34223 + auto ptr = reinterpret_cast<mindspore::schema::AssertT *>(value);
34228 + auto ptr = reinterpret_cast<mindspore::schema::AssignT *>(value);
34233 + auto ptr = reinterpret_cast<mindspore::schema::AssignAddT *>(value);
34238 + auto ptr = reinterpret_cast<mindspore::schema::AudioSpectrogramT *>(value);
34243 + auto ptr = reinterpret_cast<mindspore::schema::AvgPoolFusionT *>(value);
34248 + auto ptr = reinterpret_cast<mindspore::schema::AvgPoolGradT *>(value);
34253 + auto ptr = reinterpret_cast<mindspore::schema::BatchNormT *>(value);
34258 + auto ptr = reinterpret_cast<mindspore::schema::BatchNormGradT *>(value);
34263 + auto ptr = reinterpret_cast<mindspore::schema::BatchToSpaceT *>(value);
34268 + auto ptr = reinterpret_cast<mindspore::schema::BatchToSpaceNDT *>(value);
34273 + auto ptr = reinterpret_cast<mindspore::schema::BiasAddT *>(value);
34278 + auto ptr = reinterpret_cast<mindspore::schema::BinaryCrossEntropyT *>(value);
34283 + auto ptr = reinterpret_cast<mindspore::schema::BinaryCrossEntropyGradT *>(value);
34288 + auto ptr = reinterpret_cast<mindspore::schema::BiasAddGradT *>(value);
34293 + auto ptr = reinterpret_cast<mindspore::schema::BroadcastToT *>(value);
34298 + auto ptr = reinterpret_cast<mindspore::schema::CastT *>(value);
34303 + auto ptr = reinterpret_cast<mindspore::schema::CeilT *>(value);
34308 + auto ptr = reinterpret_cast<mindspore::schema::ClipT *>(value);
34313 + auto ptr = reinterpret_cast<mindspore::schema::ConcatT *>(value);
34318 + auto ptr = reinterpret_cast<mindspore::schema::AttentionT *>(value);
34323 + auto ptr = reinterpret_cast<mindspore::schema::Conv2DBackpropFilterFusionT *>(value);
34328 + auto ptr = reinterpret_cast<mindspore::schema::Conv2DBackpropInputFusionT *>(value);
34333 + auto ptr = reinterpret_cast<mindspore::schema::Conv2DFusionT *>(value);
34338 + auto ptr = reinterpret_cast<mindspore::schema::Conv2dTransposeFusionT *>(value);
34343 + auto ptr = reinterpret_cast<mindspore::schema::CosT *>(value);
34348 + auto ptr = reinterpret_cast<mindspore::schema::ConstantOfShapeT *>(value);
34353 + auto ptr = reinterpret_cast<mindspore::schema::CropT *>(value);
34358 + auto ptr = reinterpret_cast<mindspore::schema::CustomExtractFeaturesT *>(value);
34363 + auto ptr = reinterpret_cast<mindspore::schema::CustomNormalizeT *>(value);
34368 + auto ptr = reinterpret_cast<mindspore::schema::CustomPredictT *>(value);
34373 + auto ptr = reinterpret_cast<mindspore::schema::DeConv2DGradFilterT *>(value);
34378 + auto ptr = reinterpret_cast<mindspore::schema::DependT *>(value);
34383 + auto ptr = reinterpret_cast<mindspore::schema::DepthToSpaceT *>(value);
34388 + auto ptr = reinterpret_cast<mindspore::schema::DetectionPostProcessT *>(value);
34393 + auto ptr = reinterpret_cast<mindspore::schema::DivFusionT *>(value);
34398 + auto ptr = reinterpret_cast<mindspore::schema::DivGradT *>(value);
34403 + auto ptr = reinterpret_cast<mindspore::schema::DropoutT *>(value);
34408 + auto ptr = reinterpret_cast<mindspore::schema::DropoutGradT *>(value);
34413 + auto ptr = reinterpret_cast<mindspore::schema::EluT *>(value);
34418 + auto ptr = reinterpret_cast<mindspore::schema::EltwiseT *>(value);
34423 + auto ptr = reinterpret_cast<mindspore::schema::EqualT *>(value);
34428 + auto ptr = reinterpret_cast<mindspore::schema::EmbeddingLookupFusionT *>(value);
34433 + auto ptr = reinterpret_cast<mindspore::schema::ExpFusionT *>(value);
34438 + auto ptr = reinterpret_cast<mindspore::schema::ExpandDimsT *>(value);
34443 + auto ptr = reinterpret_cast<mindspore::schema::FakeQuantWithMinMaxVarsT *>(value);
34448 + auto ptr = reinterpret_cast<mindspore::schema::FakeQuantWithMinMaxVarsPerChannelT *>(value);
34453 + auto ptr = reinterpret_cast<mindspore::schema::FftRealT *>(value);
34458 + auto ptr = reinterpret_cast<mindspore::schema::FftImagT *>(value);
34463 + auto ptr = reinterpret_cast<mindspore::schema::FlattenT *>(value);
34468 + auto ptr = reinterpret_cast<mindspore::schema::FlattenGradT *>(value);
34473 + auto ptr = reinterpret_cast<mindspore::schema::FloorT *>(value);
34478 + auto ptr = reinterpret_cast<mindspore::schema::FloorDivT *>(value);
34483 + auto ptr = reinterpret_cast<mindspore::schema::FloorModT *>(value);
34488 + auto ptr = reinterpret_cast<mindspore::schema::FillT *>(value);
34493 + auto ptr = reinterpret_cast<mindspore::schema::FullConnectionT *>(value);
34498 + auto ptr = reinterpret_cast<mindspore::schema::FusedBatchNormT *>(value);
34503 + auto ptr = reinterpret_cast<mindspore::schema::GatherT *>(value);
34508 + auto ptr = reinterpret_cast<mindspore::schema::GatherNdT *>(value);
34513 + auto ptr = reinterpret_cast<mindspore::schema::GreaterT *>(value);
34518 + auto ptr = reinterpret_cast<mindspore::schema::GreaterEqualT *>(value);
34523 + auto ptr = reinterpret_cast<mindspore::schema::HashtableLookupT *>(value);
34528 + auto ptr = reinterpret_cast<mindspore::schema::InstanceNormT *>(value);
34533 + auto ptr = reinterpret_cast<mindspore::schema::LayerNormFusionT *>(value);
34538 + auto ptr = reinterpret_cast<mindspore::schema::LeakyReluT *>(value);
34543 + auto ptr = reinterpret_cast<mindspore::schema::LessT *>(value);
34548 + auto ptr = reinterpret_cast<mindspore::schema::LessEqualT *>(value);
34553 + auto ptr = reinterpret_cast<mindspore::schema::LogT *>(value);
34558 + auto ptr = reinterpret_cast<mindspore::schema::LogGradT *>(value);
34563 + auto ptr = reinterpret_cast<mindspore::schema::LogicalAndT *>(value);
34568 + auto ptr = reinterpret_cast<mindspore::schema::LogicalNotT *>(value);
34573 + auto ptr = reinterpret_cast<mindspore::schema::LogicalOrT *>(value);
34578 + auto ptr = reinterpret_cast<mindspore::schema::LpNormalizationT *>(value);
34583 + auto ptr = reinterpret_cast<mindspore::schema::LRNT *>(value);
34588 + auto ptr = reinterpret_cast<mindspore::schema::LshProjectionT *>(value);
34593 + auto ptr = reinterpret_cast<mindspore::schema::LSTMT *>(value);
34598 + auto ptr = reinterpret_cast<mindspore::schema::L2NormalizeFusionT *>(value);
34603 + auto ptr = reinterpret_cast<mindspore::schema::MatMulFusionT *>(value);
34608 + auto ptr = reinterpret_cast<mindspore::schema::MaximumT *>(value);
34613 + auto ptr = reinterpret_cast<mindspore::schema::MaximumGradT *>(value);
34618 + auto ptr = reinterpret_cast<mindspore::schema::MaxPoolFusionT *>(value);
34623 + auto ptr = reinterpret_cast<mindspore::schema::MaxPoolGradT *>(value);
34628 + auto ptr = reinterpret_cast<mindspore::schema::SwitchLayerT *>(value);
34633 + auto ptr = reinterpret_cast<mindspore::schema::MfccT *>(value);
34638 + auto ptr = reinterpret_cast<mindspore::schema::MinimumT *>(value);
34643 + auto ptr = reinterpret_cast<mindspore::schema::MinimumGradT *>(value);
34648 + auto ptr = reinterpret_cast<mindspore::schema::ModT *>(value);
34653 + auto ptr = reinterpret_cast<mindspore::schema::MulFusionT *>(value);
34658 + auto ptr = reinterpret_cast<mindspore::schema::MulGradT *>(value);
34663 + auto ptr = reinterpret_cast<mindspore::schema::NegT *>(value);
34668 + auto ptr = reinterpret_cast<mindspore::schema::NegGradT *>(value);
34673 + auto ptr = reinterpret_cast<mindspore::schema::NotEqualT *>(value);
34678 + auto ptr = reinterpret_cast<mindspore::schema::NonMaxSuppressionT *>(value);
34683 + auto ptr = reinterpret_cast<mindspore::schema::OneHotT *>(value);
34688 + auto ptr = reinterpret_cast<mindspore::schema::OnesLikeT *>(value);
34693 + auto ptr = reinterpret_cast<mindspore::schema::PadFusionT *>(value);
34698 + auto ptr = reinterpret_cast<mindspore::schema::PartialFusionT *>(value);
34703 + auto ptr = reinterpret_cast<mindspore::schema::PowerGradT *>(value);
34708 + auto ptr = reinterpret_cast<mindspore::schema::PowFusionT *>(value);
34713 + auto ptr = reinterpret_cast<mindspore::schema::PriorBoxT *>(value);
34718 + auto ptr = reinterpret_cast<mindspore::schema::PReLUFusionT *>(value);
34723 + auto ptr = reinterpret_cast<mindspore::schema::QuantDTypeCastT *>(value);
34728 + auto ptr = reinterpret_cast<mindspore::schema::RankT *>(value);
34733 + auto ptr = reinterpret_cast<mindspore::schema::RangeT *>(value);
34738 + auto ptr = reinterpret_cast<mindspore::schema::ReciprocalT *>(value);
34743 + auto ptr = reinterpret_cast<mindspore::schema::RealDivT *>(value);
34748 + auto ptr = reinterpret_cast<mindspore::schema::ReduceFusionT *>(value);
34753 + auto ptr = reinterpret_cast<mindspore::schema::ReshapeT *>(value);
34758 + auto ptr = reinterpret_cast<mindspore::schema::ResizeT *>(value);
34763 + auto ptr = reinterpret_cast<mindspore::schema::ReverseSequenceT *>(value);
34768 + auto ptr = reinterpret_cast<mindspore::schema::ReverseV2T *>(value);
34773 + auto ptr = reinterpret_cast<mindspore::schema::RfftT *>(value);
34778 + auto ptr = reinterpret_cast<mindspore::schema::ROIPoolingT *>(value);
34783 + auto ptr = reinterpret_cast<mindspore::schema::RoundT *>(value);
34788 + auto ptr = reinterpret_cast<mindspore::schema::RsqrtT *>(value);
34793 + auto ptr = reinterpret_cast<mindspore::schema::ScaleFusionT *>(value);
34798 + auto ptr = reinterpret_cast<mindspore::schema::ScatterNdT *>(value);
34803 + auto ptr = reinterpret_cast<mindspore::schema::SGDT *>(value);
34808 + auto ptr = reinterpret_cast<mindspore::schema::ShapeT *>(value);
34813 + auto ptr = reinterpret_cast<mindspore::schema::SigmoidCrossEntropyWithLogitsT *>(value);
34818 + auto ptr = reinterpret_cast<mindspore::schema::SigmoidCrossEntropyWithLogitsGradT *>(value);
34823 + auto ptr = reinterpret_cast<mindspore::schema::SinT *>(value);
34828 + auto ptr = reinterpret_cast<mindspore::schema::SkipGramT *>(value);
34833 + auto ptr = reinterpret_cast<mindspore::schema::SliceFusionT *>(value);
34838 + auto ptr = reinterpret_cast<mindspore::schema::SmoothL1LossT *>(value);
34843 + auto ptr = reinterpret_cast<mindspore::schema::SmoothL1LossGradT *>(value);
34848 + auto ptr = reinterpret_cast<mindspore::schema::SoftmaxT *>(value);
34853 + auto ptr = reinterpret_cast<mindspore::schema::SoftmaxCrossEntropyWithLogitsT *>(value);
34858 + auto ptr = reinterpret_cast<mindspore::schema::SpaceToBatchT *>(value);
34863 + auto ptr = reinterpret_cast<mindspore::schema::SpaceToBatchNDT *>(value);
34868 + auto ptr = reinterpret_cast<mindspore::schema::SpaceToDepthT *>(value);
34873 + auto ptr = reinterpret_cast<mindspore::schema::SparseSoftmaxCrossEntropyWithLogitsT *>(value…
34878 + auto ptr = reinterpret_cast<mindspore::schema::SparseToDenseT *>(value);
34883 + auto ptr = reinterpret_cast<mindspore::schema::SplitT *>(value);
34888 + auto ptr = reinterpret_cast<mindspore::schema::SqrtT *>(value);
34893 + auto ptr = reinterpret_cast<mindspore::schema::SqueezeT *>(value);
34898 + auto ptr = reinterpret_cast<mindspore::schema::SquareT *>(value);
34903 + auto ptr = reinterpret_cast<mindspore::schema::SquaredDifferenceT *>(value);
34908 + auto ptr = reinterpret_cast<mindspore::schema::StackT *>(value);
34913 + auto ptr = reinterpret_cast<mindspore::schema::StridedSliceT *>(value);
34918 + auto ptr = reinterpret_cast<mindspore::schema::SubFusionT *>(value);
34923 + auto ptr = reinterpret_cast<mindspore::schema::SubGradT *>(value);
34928 + auto ptr = reinterpret_cast<mindspore::schema::SwitchT *>(value);
34933 + auto ptr = reinterpret_cast<mindspore::schema::TensorListFromTensorT *>(value);
34938 + auto ptr = reinterpret_cast<mindspore::schema::TensorListGetItemT *>(value);
34943 + auto ptr = reinterpret_cast<mindspore::schema::TensorListReserveT *>(value);
34948 + auto ptr = reinterpret_cast<mindspore::schema::TensorListSetItemT *>(value);
34953 + auto ptr = reinterpret_cast<mindspore::schema::TensorListStackT *>(value);
34958 + auto ptr = reinterpret_cast<mindspore::schema::TileFusionT *>(value);
34963 + auto ptr = reinterpret_cast<mindspore::schema::TopKFusionT *>(value);
34968 + auto ptr = reinterpret_cast<mindspore::schema::TransposeT *>(value);
34973 + auto ptr = reinterpret_cast<mindspore::schema::UniqueT *>(value);
34978 + auto ptr = reinterpret_cast<mindspore::schema::UnsortedSegmentSumT *>(value);
34983 + auto ptr = reinterpret_cast<mindspore::schema::UnsqueezeT *>(value);
34988 + auto ptr = reinterpret_cast<mindspore::schema::UnstackT *>(value);
34993 + auto ptr = reinterpret_cast<mindspore::schema::LSTMGradT *>(value);
34998 + auto ptr = reinterpret_cast<mindspore::schema::WhereT *>(value);
35003 + auto ptr = reinterpret_cast<mindspore::schema::ZerosLikeT *>(value);
35008 + auto ptr = reinterpret_cast<mindspore::schema::SelectT *>(value);
35013 + auto ptr = reinterpret_cast<mindspore::schema::ScatterNdUpdateT *>(value);
35018 + auto ptr = reinterpret_cast<mindspore::schema::GRUT *>(value);
35023 + auto ptr = reinterpret_cast<mindspore::schema::NonZeroT *>(value);
35028 + auto ptr = reinterpret_cast<mindspore::schema::InvertPermutationT *>(value);
35033 + auto ptr = reinterpret_cast<mindspore::schema::SizeT *>(value);
35038 + auto ptr = reinterpret_cast<mindspore::schema::RandomStandardNormalT *>(value);
35043 + auto ptr = reinterpret_cast<mindspore::schema::CropAndResizeT *>(value);
35048 + auto ptr = reinterpret_cast<mindspore::schema::ErfT *>(value);
35053 + auto ptr = reinterpret_cast<mindspore::schema::StridedSliceGradT *>(value);
35058 + auto ptr = reinterpret_cast<mindspore::schema::IsFiniteT *>(value);
35063 + auto ptr = reinterpret_cast<mindspore::schema::LinSpaceT *>(value);
35068 + auto ptr = reinterpret_cast<mindspore::schema::UniformRealT *>(value);
35073 + auto ptr = reinterpret_cast<mindspore::schema::AbsGradT *>(value);
35078 + auto ptr = reinterpret_cast<mindspore::schema::RsqrtGradT *>(value);
35083 + auto ptr = reinterpret_cast<mindspore::schema::SqrtGradT *>(value);
35088 + auto ptr = reinterpret_cast<mindspore::schema::LayerNormGradT *>(value);
35093 + auto ptr = reinterpret_cast<mindspore::schema::ResizeGradT *>(value);
35098 + auto ptr = reinterpret_cast<mindspore::schema::SpliceT *>(value);
35103 + auto ptr = reinterpret_cast<mindspore::schema::LogSoftmaxT *>(value);
35108 + auto ptr = reinterpret_cast<mindspore::schema::CallT *>(value);
35113 + auto ptr = reinterpret_cast<mindspore::schema::CustomT *>(value);
35118 + auto ptr = reinterpret_cast<mindspore::schema::CumSumT *>(value);
35123 + auto ptr = reinterpret_cast<mindspore::schema::SplitWithOverlapT *>(value);
35128 + auto ptr = reinterpret_cast<mindspore::schema::GenOPT *>(value);
35133 + auto ptr = reinterpret_cast<mindspore::schema::RaggedRangeT *>(value);
35138 + auto ptr = reinterpret_cast<mindspore::schema::GLUT *>(value);
35143 + auto ptr = reinterpret_cast<mindspore::schema::TensorArrayT *>(value);
35148 + auto ptr = reinterpret_cast<mindspore::schema::TensorArrayReadT *>(value);
35153 + auto ptr = reinterpret_cast<mindspore::schema::TensorArrayWriteT *>(value);
35158 + auto ptr = reinterpret_cast<mindspore::schema::AffineT *>(value);
35163 + auto ptr = reinterpret_cast<mindspore::schema::AllGatherT *>(value);
35168 + auto ptr = reinterpret_cast<mindspore::schema::ReduceScatterT *>(value);
35173 + auto ptr = reinterpret_cast<mindspore::schema::DynamicQuantT *>(value);
35178 + auto ptr = reinterpret_cast<mindspore::schema::LSTMGradDataT *>(value);
35183 + auto ptr = reinterpret_cast<mindspore::schema::LSTMGradWeightT *>(value);
35188 + auto ptr = reinterpret_cast<mindspore::schema::RandomNormalT *>(value);
35193 + auto ptr = reinterpret_cast<mindspore::schema::NLLLossT *>(value);
35198 + auto ptr = reinterpret_cast<mindspore::schema::NLLLossGradT *>(value);
35203 + auto ptr = reinterpret_cast<mindspore::schema::FormatTransposeT *>(value);
35208 + auto ptr = reinterpret_cast<mindspore::schema::GatherDT *>(value);
35213 + auto ptr = reinterpret_cast<mindspore::schema::GroupNormFusionT *>(value);
38614 + const auto end = fbb_.EndTable(start_);
38615 + auto o = flatbuffers::Offset<Vec>(end);
38631 + auto data__ = data ? _fbb.CreateVector<int64_t>(*data) : 0;
38683 + const auto end = fbb_.EndTable(start_);
38684 + auto o = flatbuffers::Offset<Vec2D>(end);
38700 + auto data__ = data ? _fbb.CreateVector<flatbuffers::Offset<mindspore::schema::Vec>>(*data) : 0;
38764 + const auto end = fbb_.EndTable(start_);
38765 + auto o = flatbuffers::Offset<Attribute>(end);
38784 + auto name__ = name ? _fbb.CreateString(name) : 0;
38785 + auto data__ = data ? _fbb.CreateVector<uint8_t>(*data) : 0;
38795 + auto _o = std::unique_ptr<VecT>(new VecT());
38803 + { auto _e = data(); if (_e) { _o->data.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _…
38814 + auto _data = _o->data.size() ? _fbb.CreateVector(_o->data) : 0;
38821 + auto _o = std::unique_ptr<Vec2DT>(new Vec2DT());
38829 + { auto _e = data(); if (_e) { _o->data.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _…
38840 + auto _data = _o->data.size() ? _fbb.CreateVector<flatbuffers::Offset<mindspore::schema::Vec>> (_…
38847 + auto _o = std::unique_ptr<AttributeT>(new AttributeT());
38855 + { auto _e = name(); if (_e) _o->name = _e->str(); }
38856 + { auto _e = data(); if (_e) { _o->data.resize(_e->size()); std::copy(_e->begin(), _e->end(), _o-…
38867 + auto _name = _o->name.empty() ? 0 : _fbb.CreateString(_o->name);
38868 + auto _data = _o->data.size() ? _fbb.CreateVector(_o->data) : 0;
39388 + const auto end = fbb_.EndTable(start_);
39389 + auto o = flatbuffers::Offset<QuantParam>(end);
39477 + const auto end = fbb_.EndTable(start_);
39478 + auto o = flatbuffers::Offset<ExternalData>(end);
39503 + auto checkSum__ = checkSum ? _fbb.CreateString(checkSum) : 0;
39504 + auto location__ = location ? _fbb.CreateString(location) : 0;
39644 + const auto end = fbb_.EndTable(start_);
39645 + auto o = flatbuffers::Offset<Tensor>(end);
39697 + auto dims__ = dims ? _fbb.CreateVector<int32_t>(*dims) : 0;
39698 + auto data__ = data ? _fbb.CreateVector<uint8_t>(*data) : 0;
39699 + auto quantParams__ = quantParams ? _fbb.CreateVector<flatbuffers::Offset<mindspore::schema::Quan…
39700 + auto quantClusters__ = quantClusters ? _fbb.CreateVector<float>(*quantClusters) : 0;
39701 + auto name__ = name ? _fbb.CreateString(name) : 0;
39702 + auto externalData__ = externalData ? _fbb.CreateVector<flatbuffers::Offset<mindspore::schema::Ex…
41234 + const auto end = fbb_.EndTable(start_);
41235 + auto o = flatbuffers::Offset<Primitive>(end);
41321 + const auto end = fbb_.EndTable(start_);
41322 + auto o = flatbuffers::Offset<CNode>(end);
41353 + auto name__ = name ? _fbb.CreateString(name) : 0;
41354 + auto inputIndex__ = inputIndex ? _fbb.CreateVector<uint32_t>(*inputIndex) : 0;
41355 + auto outputIndex__ = outputIndex ? _fbb.CreateVector<uint32_t>(*outputIndex) : 0;
41430 + const auto end = fbb_.EndTable(start_);
41431 + auto o = flatbuffers::Offset<SubGraph>(end);
41459 + auto name__ = name ? _fbb.CreateString(name) : 0;
41460 + auto inputIndices__ = inputIndices ? _fbb.CreateVector<uint32_t>(*inputIndices) : 0;
41461 + auto outputIndices__ = outputIndices ? _fbb.CreateVector<uint32_t>(*outputIndices) : 0;
41462 + auto nodeIndices__ = nodeIndices ? _fbb.CreateVector<uint32_t>(*nodeIndices) : 0;
41463 + auto tensorIndices__ = tensorIndices ? _fbb.CreateVector<uint32_t>(*tensorIndices) : 0;
41591 + const auto end = fbb_.EndTable(start_);
41592 + auto o = flatbuffers::Offset<MetaGraph>(end);
41638 + auto name__ = name ? _fbb.CreateString(name) : 0;
41639 + auto version__ = version ? _fbb.CreateString(version) : 0;
41640 + auto inputIndex__ = inputIndex ? _fbb.CreateVector<uint32_t>(*inputIndex) : 0;
41641 + auto outputIndex__ = outputIndex ? _fbb.CreateVector<uint32_t>(*outputIndex) : 0;
41642 + auto nodes__ = nodes ? _fbb.CreateVector<flatbuffers::Offset<mindspore::schema::CNode>>(*nodes) …
41643 + auto allTensors__ = allTensors ? _fbb.CreateVector<flatbuffers::Offset<mindspore::schema::Tensor…
41644 + auto subGraph__ = subGraph ? _fbb.CreateVector<flatbuffers::Offset<mindspore::schema::SubGraph>>…
41645 + auto obfMetaData__ = obfMetaData ? _fbb.CreateVector<uint8_t>(*obfMetaData) : 0;
43888 + const auto end = fbb_.EndTable(start_);
43889 + auto o = flatbuffers::Offset<Abs>(end);
43959 + const auto end = fbb_.EndTable(start_);
43960 + auto o = flatbuffers::Offset<Activation>(end);
44016 + const auto end = fbb_.EndTable(start_);
44017 + auto o = flatbuffers::Offset<ActivationGrad>(end);
44067 + const auto end = fbb_.EndTable(start_);
44068 + auto o = flatbuffers::Offset<Adam>(end);
44110 + const auto end = fbb_.EndTable(start_);
44111 + auto o = flatbuffers::Offset<AddFusion>(end);
44227 + const auto end = fbb_.EndTable(start_);
44228 + auto o = flatbuffers::Offset<AdderFusion>(end);
44271 + auto kernel_size__ = kernel_size ? _fbb.CreateVector<int64_t>(*kernel_size) : 0;
44272 + auto stride__ = stride ? _fbb.CreateVector<int64_t>(*stride) : 0;
44273 + auto dilation__ = dilation ? _fbb.CreateVector<int64_t>(*dilation) : 0;
44274 + auto pad_list__ = pad_list ? _fbb.CreateVector<int64_t>(*pad_list) : 0;
44306 + const auto end = fbb_.EndTable(start_);
44307 + auto o = flatbuffers::Offset<AddGrad>(end);
44335 + const auto end = fbb_.EndTable(start_);
44336 + auto o = flatbuffers::Offset<AddN>(end);
44374 + const auto end = fbb_.EndTable(start_);
44375 + auto o = flatbuffers::Offset<All>(end);
44431 + const auto end = fbb_.EndTable(start_);
44432 + auto o = flatbuffers::Offset<ApplyMomentum>(end);
44500 + const auto end = fbb_.EndTable(start_);
44501 + auto o = flatbuffers::Offset<ArgMaxFusion>(end);
44571 + const auto end = fbb_.EndTable(start_);
44572 + auto o = flatbuffers::Offset<ArgMinFusion>(end);
44618 + const auto end = fbb_.EndTable(start_);
44619 + auto o = flatbuffers::Offset<Assert>(end);
44649 + const auto end = fbb_.EndTable(start_);
44650 + auto o = flatbuffers::Offset<Assign>(end);
44678 + const auto end = fbb_.EndTable(start_);
44679 + auto o = flatbuffers::Offset<AssignAdd>(end);
44733 + const auto end = fbb_.EndTable(start_);
44734 + auto o = flatbuffers::Offset<AudioSpectrogram>(end);
44837 + const auto end = fbb_.EndTable(start_);
44838 + auto o = flatbuffers::Offset<AvgPoolFusion>(end);
44875 + auto kernel_size__ = kernel_size ? _fbb.CreateVector<int64_t>(*kernel_size) : 0;
44876 + auto strides__ = strides ? _fbb.CreateVector<int64_t>(*strides) : 0;
44877 + auto pad__ = pad ? _fbb.CreateVector<int64_t>(*pad) : 0;
44943 + const auto end = fbb_.EndTable(start_);
44944 + auto o = flatbuffers::Offset<AvgPoolGrad>(end);
44969 + auto kernel_size__ = kernel_size ? _fbb.CreateVector<int64_t>(*kernel_size) : 0;
44970 + auto strides__ = strides ? _fbb.CreateVector<int64_t>(*strides) : 0;
45022 + const auto end = fbb_.EndTable(start_);
45023 + auto o = flatbuffers::Offset<BatchNorm>(end);
45075 + const auto end = fbb_.EndTable(start_);
45076 + auto o = flatbuffers::Offset<BatchNormGrad>(end);
45128 + const auto end = fbb_.EndTable(start_);
45129 + auto o = flatbuffers::Offset<BatchToSpace>(end);
45148 + auto block_size__ = block_size ? _fbb.CreateVector<int64_t>(*block_size) : 0;
45192 + const auto end = fbb_.EndTable(start_);
45193 + auto o = flatbuffers::Offset<BatchToSpaceND>(end);
45212 + auto block_shape__ = block_shape ? _fbb.CreateVector<int64_t>(*block_shape) : 0;
45246 + const auto end = fbb_.EndTable(start_);
45247 + auto o = flatbuffers::Offset<BiasAdd>(end);
45287 + const auto end = fbb_.EndTable(start_);
45288 + auto o = flatbuffers::Offset<BinaryCrossEntropy>(end);
45328 + const auto end = fbb_.EndTable(start_);
45329 + auto o = flatbuffers::Offset<BinaryCrossEntropyGrad>(end);
45359 + const auto end = fbb_.EndTable(start_);
45360 + auto o = flatbuffers::Offset<BiasAddGrad>(end);
45399 + const auto end = fbb_.EndTable(start_);
45400 + auto o = flatbuffers::Offset<BroadcastTo>(end);
45416 + auto shape__ = shape ? _fbb.CreateVector<int64_t>(*shape) : 0;
45439 + const auto end = fbb_.EndTable(start_);
45440 + auto o = flatbuffers::Offset<Cast>(end);
45468 + const auto end = fbb_.EndTable(start_);
45469 + auto o = flatbuffers::Offset<Ceil>(end);
45515 + const auto end = fbb_.EndTable(start_);
45516 + auto o = flatbuffers::Offset<Clip>(end);
45558 + const auto end = fbb_.EndTable(start_);
45559 + auto o = flatbuffers::Offset<Concat>(end);
45589 + const auto end = fbb_.EndTable(start_);
45590 + auto o = flatbuffers::Offset<Attention>(end);
45712 + const auto end = fbb_.EndTable(start_);
45713 + auto o = flatbuffers::Offset<Conv2DBackpropFilterFusion>(end);
45759 + auto kernel_size__ = kernel_size ? _fbb.CreateVector<int64_t>(*kernel_size) : 0;
45760 + auto stride__ = stride ? _fbb.CreateVector<int64_t>(*stride) : 0;
45761 + auto dilation__ = dilation ? _fbb.CreateVector<int64_t>(*dilation) : 0;
45762 + auto pad_list__ = pad_list ? _fbb.CreateVector<int64_t>(*pad_list) : 0;
45898 + const auto end = fbb_.EndTable(start_);
45899 + auto o = flatbuffers::Offset<Conv2DBackpropInputFusion>(end);
45948 + auto kernel_size__ = kernel_size ? _fbb.CreateVector<int64_t>(*kernel_size) : 0;
45949 + auto stride__ = stride ? _fbb.CreateVector<int64_t>(*stride) : 0;
45950 + auto dilation__ = dilation ? _fbb.CreateVector<int64_t>(*dilation) : 0;
45951 + auto pad__ = pad ? _fbb.CreateVector<int64_t>(*pad) : 0;
45952 + auto pad_list__ = pad_list ? _fbb.CreateVector<int64_t>(*pad_list) : 0;
46080 + const auto end = fbb_.EndTable(start_);
46081 + auto o = flatbuffers::Offset<Conv2DFusion>(end);
46127 + auto kernel_size__ = kernel_size ? _fbb.CreateVector<int64_t>(*kernel_size) : 0;
46128 + auto stride__ = stride ? _fbb.CreateVector<int64_t>(*stride) : 0;
46129 + auto dilation__ = dilation ? _fbb.CreateVector<int64_t>(*dilation) : 0;
46130 + auto pad_list__ = pad_list ? _fbb.CreateVector<int64_t>(*pad_list) : 0;
46275 + const auto end = fbb_.EndTable(start_);
46276 + auto o = flatbuffers::Offset<Conv2dTransposeFusion>(end);
46328 + auto kernel_size__ = kernel_size ? _fbb.CreateVector<int64_t>(*kernel_size) : 0;
46329 + auto stride__ = stride ? _fbb.CreateVector<int64_t>(*stride) : 0;
46330 + auto dilation__ = dilation ? _fbb.CreateVector<int64_t>(*dilation) : 0;
46331 + auto pad__ = pad ? _fbb.CreateVector<int64_t>(*pad) : 0;
46332 + auto pad_list__ = pad_list ? _fbb.CreateVector<int64_t>(*pad_list) : 0;
46333 + auto output_paddings__ = output_paddings ? _fbb.CreateVector<int64_t>(*output_paddings) : 0;
46368 + const auto end = fbb_.EndTable(start_);
46369 + auto o = flatbuffers::Offset<Cos>(end);
46416 + const auto end = fbb_.EndTable(start_);
46417 + auto o = flatbuffers::Offset<ConstantOfShape>(end);
46436 + auto value__ = value ? _fbb.CreateVector<float>(*value) : 0;
46479 + const auto end = fbb_.EndTable(start_);
46480 + auto o = flatbuffers::Offset<Crop>(end);
46499 + auto offsets__ = offsets ? _fbb.CreateVector<int64_t>(*offsets) : 0;
46523 + const auto end = fbb_.EndTable(start_);
46524 + auto o = flatbuffers::Offset<CustomExtractFeatures>(end);
46552 + const auto end = fbb_.EndTable(start_);
46553 + auto o = flatbuffers::Offset<CustomNormalize>(end);
46599 + const auto end = fbb_.EndTable(start_);
46600 + auto o = flatbuffers::Offset<CustomPredict>(end);
46718 + const auto end = fbb_.EndTable(start_);
46719 + auto o = flatbuffers::Offset<DeConv2DGradFilter>(end);
46762 + auto kernel_size__ = kernel_size ? _fbb.CreateVector<int64_t>(*kernel_size) : 0;
46763 + auto pad_list__ = pad_list ? _fbb.CreateVector<int64_t>(*pad_list) : 0;
46764 + auto stride__ = stride ? _fbb.CreateVector<int64_t>(*stride) : 0;
46765 + auto dilation__ = dilation ? _fbb.CreateVector<int64_t>(*dilation) : 0;
46797 + const auto end = fbb_.EndTable(start_);
46798 + auto o = flatbuffers::Offset<Depend>(end);
46844 + const auto end = fbb_.EndTable(start_);
46845 + auto o = flatbuffers::Offset<DepthToSpace>(end);
46968 + const auto end = fbb_.EndTable(start_);
46969 + auto o = flatbuffers::Offset<DetectionPostProcess>(end);
47015 + auto scale__ = scale ? _fbb.CreateVector<float>(*scale) : 0;
47058 + const auto end = fbb_.EndTable(start_);
47059 + auto o = flatbuffers::Offset<DivFusion>(end);
47089 + const auto end = fbb_.EndTable(start_);
47090 + auto o = flatbuffers::Offset<DivGrad>(end);
47128 + const auto end = fbb_.EndTable(start_);
47129 + auto o = flatbuffers::Offset<Dropout>(end);
47169 + const auto end = fbb_.EndTable(start_);
47170 + auto o = flatbuffers::Offset<DropoutGrad>(end);
47210 + const auto end = fbb_.EndTable(start_);
47211 + auto o = flatbuffers::Offset<Elu>(end);
47251 + const auto end = fbb_.EndTable(start_);
47252 + auto o = flatbuffers::Offset<Eltwise>(end);
47282 + const auto end = fbb_.EndTable(start_);
47283 + auto o = flatbuffers::Offset<Equal>(end);
47321 + const auto end = fbb_.EndTable(start_);
47322 + auto o = flatbuffers::Offset<EmbeddingLookupFusion>(end);
47378 + const auto end = fbb_.EndTable(start_);
47379 + auto o = flatbuffers::Offset<ExpFusion>(end);
47413 + const auto end = fbb_.EndTable(start_);
47414 + auto o = flatbuffers::Offset<ExpandDims>(end);
47460 + const auto end = fbb_.EndTable(start_);
47461 + auto o = flatbuffers::Offset<FakeQuantWithMinMaxVars>(end);
47511 + const auto end = fbb_.EndTable(start_);
47512 + auto o = flatbuffers::Offset<FakeQuantWithMinMaxVarsPerChannel>(end);
47544 + const auto end = fbb_.EndTable(start_);
47545 + auto o = flatbuffers::Offset<FftReal>(end);
47573 + const auto end = fbb_.EndTable(start_);
47574 + auto o = flatbuffers::Offset<FftImag>(end);
47612 + const auto end = fbb_.EndTable(start_);
47613 + auto o = flatbuffers::Offset<Flatten>(end);
47643 + const auto end = fbb_.EndTable(start_);
47644 + auto o = flatbuffers::Offset<FlattenGrad>(end);
47672 + const auto end = fbb_.EndTable(start_);
47673 + auto o = flatbuffers::Offset<Floor>(end);
47701 + const auto end = fbb_.EndTable(start_);
47702 + auto o = flatbuffers::Offset<FloorDiv>(end);
47730 + const auto end = fbb_.EndTable(start_);
47731 + auto o = flatbuffers::Offset<FloorMod>(end);
47759 + const auto end = fbb_.EndTable(start_);
47760 + auto o = flatbuffers::Offset<Fill>(end);
47822 + const auto end = fbb_.EndTable(start_);
47823 + auto o = flatbuffers::Offset<FullConnection>(end);
47885 + const auto end = fbb_.EndTable(start_);
47886 + auto o = flatbuffers::Offset<FusedBatchNorm>(end);
47920 + const auto end = fbb_.EndTable(start_);
47921 + auto o = flatbuffers::Offset<Gather>(end);
47949 + const auto end = fbb_.EndTable(start_);
47950 + auto o = flatbuffers::Offset<GatherNd>(end);
47978 + const auto end = fbb_.EndTable(start_);
47979 + auto o = flatbuffers::Offset<Greater>(end);
48007 + const auto end = fbb_.EndTable(start_);
48008 + auto o = flatbuffers::Offset<GreaterEqual>(end);
48036 + const auto end = fbb_.EndTable(start_);
48037 + auto o = flatbuffers::Offset<HashtableLookup>(end);
48075 + const auto end = fbb_.EndTable(start_);
48076 + auto o = flatbuffers::Offset<InstanceNorm>(end);
48140 + const auto end = fbb_.EndTable(start_);
48141 + auto o = flatbuffers::Offset<LayerNormFusion>(end);
48187 + const auto end = fbb_.EndTable(start_);
48188 + auto o = flatbuffers::Offset<LeakyRelu>(end);
48218 + const auto end = fbb_.EndTable(start_);
48219 + auto o = flatbuffers::Offset<Less>(end);
48247 + const auto end = fbb_.EndTable(start_);
48248 + auto o = flatbuffers::Offset<LessEqual>(end);
48276 + const auto end = fbb_.EndTable(start_);
48277 + auto o = flatbuffers::Offset<Log>(end);
48305 + const auto end = fbb_.EndTable(start_);
48306 + auto o = flatbuffers::Offset<LogGrad>(end);
48334 + const auto end = fbb_.EndTable(start_);
48335 + auto o = flatbuffers::Offset<LogicalAnd>(end);
48363 + const auto end = fbb_.EndTable(start_);
48364 + auto o = flatbuffers::Offset<LogicalNot>(end);
48392 + const auto end = fbb_.EndTable(start_);
48393 + auto o = flatbuffers::Offset<LogicalOr>(end);
48439 + const auto end = fbb_.EndTable(start_);
48440 + auto o = flatbuffers::Offset<LpNormalization>(end);
48515 + const auto end = fbb_.EndTable(start_);
48516 + auto o = flatbuffers::Offset<LRN>(end);
48544 + auto norm_region__ = norm_region ? _fbb.CreateString(norm_region) : 0;
48581 + const auto end = fbb_.EndTable(start_);
48582 + auto o = flatbuffers::Offset<LshProjection>(end);
48686 + const auto end = fbb_.EndTable(start_);
48687 + auto o = flatbuffers::Offset<LSTM>(end);
48807 + const auto end = fbb_.EndTable(start_);
48808 + auto o = flatbuffers::Offset<LSTMGrad>(end);
48881 + const auto end = fbb_.EndTable(start_);
48882 + auto o = flatbuffers::Offset<L2NormalizeFusion>(end);
48904 + auto axis__ = axis ? _fbb.CreateVector<int64_t>(*axis) : 0;
48955 + const auto end = fbb_.EndTable(start_);
48956 + auto o = flatbuffers::Offset<MatMulFusion>(end);
48990 + const auto end = fbb_.EndTable(start_);
48991 + auto o = flatbuffers::Offset<Maximum>(end);
49037 + const auto end = fbb_.EndTable(start_);
49038 + auto o = flatbuffers::Offset<MaximumGrad>(end);
49139 + const auto end = fbb_.EndTable(start_);
49140 + auto o = flatbuffers::Offset<MaxPoolFusion>(end);
49177 + auto kernel_size__ = kernel_size ? _fbb.CreateVector<int64_t>(*kernel_size) : 0;
49178 + auto strides__ = strides ? _fbb.CreateVector<int64_t>(*strides) : 0;
49179 + auto pad__ = pad ? _fbb.CreateVector<int64_t>(*pad) : 0;
49245 + const auto end = fbb_.EndTable(start_);
49246 + auto o = flatbuffers::Offset<MaxPoolGrad>(end);
49271 + auto kernel_size__ = kernel_size ? _fbb.CreateVector<int64_t>(*kernel_size) : 0;
49272 + auto strides__ = strides ? _fbb.CreateVector<int64_t>(*strides) : 0;
49298 + const auto end = fbb_.EndTable(start_);
49299 + auto o = flatbuffers::Offset<SwitchLayer>(end);
49361 + const auto end = fbb_.EndTable(start_);
49362 + auto o = flatbuffers::Offset<Mfcc>(end);
49398 + const auto end = fbb_.EndTable(start_);
49399 + auto o = flatbuffers::Offset<Minimum>(end);
49445 + const auto end = fbb_.EndTable(start_);
49446 + auto o = flatbuffers::Offset<MinimumGrad>(end);
49478 + const auto end = fbb_.EndTable(start_);
49479 + auto o = flatbuffers::Offset<Mod>(end);
49517 + const auto end = fbb_.EndTable(start_);
49518 + auto o = flatbuffers::Offset<MulFusion>(end);
49548 + const auto end = fbb_.EndTable(start_);
49549 + auto o = flatbuffers::Offset<MulGrad>(end);
49577 + const auto end = fbb_.EndTable(start_);
49578 + auto o = flatbuffers::Offset<Neg>(end);
49606 + const auto end = fbb_.EndTable(start_);
49607 + auto o = flatbuffers::Offset<NegGrad>(end);
49635 + const auto end = fbb_.EndTable(start_);
49636 + auto o = flatbuffers::Offset<NotEqual>(end);
49674 + const auto end = fbb_.EndTable(start_);
49675 + auto o = flatbuffers::Offset<NonMaxSuppression>(end);
49715 + const auto end = fbb_.EndTable(start_);
49716 + auto o = flatbuffers::Offset<OneHot>(end);
49746 + const auto end = fbb_.EndTable(start_);
49747 + auto o = flatbuffers::Offset<OnesLike>(end);
49802 + const auto end = fbb_.EndTable(start_);
49803 + auto o = flatbuffers::Offset<PadFusion>(end);
49847 + const auto end = fbb_.EndTable(start_);
49848 + auto o = flatbuffers::Offset<PartialFusion>(end);
49904 + const auto end = fbb_.EndTable(start_);
49905 + auto o = flatbuffers::Offset<PowerGrad>(end);
49957 + const auto end = fbb_.EndTable(start_);
49958 + auto o = flatbuffers::Offset<PowFusion>(end);
50084 + const auto end = fbb_.EndTable(start_);
50085 + auto o = flatbuffers::Offset<PriorBox>(end);
50131 + auto min_sizes__ = min_sizes ? _fbb.CreateVector<int64_t>(*min_sizes) : 0;
50132 + auto max_sizes__ = max_sizes ? _fbb.CreateVector<int64_t>(*max_sizes) : 0;
50133 + auto aspect_ratios__ = aspect_ratios ? _fbb.CreateVector<float>(*aspect_ratios) : 0;
50134 + auto variances__ = variances ? _fbb.CreateVector<float>(*variances) : 0;
50177 + const auto end = fbb_.EndTable(start_);
50178 + auto o = flatbuffers::Offset<PReLUFusion>(end);
50208 + const auto end = fbb_.EndTable(start_);
50209 + auto o = flatbuffers::Offset<Rank>(end);
50271 + const auto end = fbb_.EndTable(start_);
50272 + auto o = flatbuffers::Offset<Range>(end);
50308 + const auto end = fbb_.EndTable(start_);
50309 + auto o = flatbuffers::Offset<Reciprocal>(end);
50337 + const auto end = fbb_.EndTable(start_);
50338 + auto o = flatbuffers::Offset<RealDiv>(end);
50400 + const auto end = fbb_.EndTable(start_);
50401 + auto o = flatbuffers::Offset<ReduceFusion>(end);
50437 + const auto end = fbb_.EndTable(start_);
50438 + auto o = flatbuffers::Offset<Reshape>(end);
50548 + const auto end = fbb_.EndTable(start_);
50549 + auto o = flatbuffers::Offset<Resize>(end);
50615 + const auto end = fbb_.EndTable(start_);
50616 + auto o = flatbuffers::Offset<ReverseSequence>(end);
50659 + const auto end = fbb_.EndTable(start_);
50660 + auto o = flatbuffers::Offset<ReverseV2>(end);
50676 + auto axis__ = axis ? _fbb.CreateVector<int64_t>(*axis) : 0;
50709 + const auto end = fbb_.EndTable(start_);
50710 + auto o = flatbuffers::Offset<Rfft>(end);
50766 + const auto end = fbb_.EndTable(start_);
50767 + auto o = flatbuffers::Offset<ROIPooling>(end);
50801 + const auto end = fbb_.EndTable(start_);
50802 + auto o = flatbuffers::Offset<Round>(end);
50830 + const auto end = fbb_.EndTable(start_);
50831 + auto o = flatbuffers::Offset<Rsqrt>(end);
50877 + const auto end = fbb_.EndTable(start_);
50878 + auto o = flatbuffers::Offset<QuantDTypeCast>(end);
50928 + const auto end = fbb_.EndTable(start_);
50929 + auto o = flatbuffers::Offset<ScaleFusion>(end);
50961 + const auto end = fbb_.EndTable(start_);
50962 + auto o = flatbuffers::Offset<ScatterNd>(end);
51016 + const auto end = fbb_.EndTable(start_);
51017 + auto o = flatbuffers::Offset<SGD>(end);
51051 + const auto end = fbb_.EndTable(start_);
51052 + auto o = flatbuffers::Offset<Shape>(end);
51080 + const auto end = fbb_.EndTable(start_);
51081 + auto o = flatbuffers::Offset<SigmoidCrossEntropyWithLogits>(end);
51109 + const auto end = fbb_.EndTable(start_);
51110 + auto o = flatbuffers::Offset<SigmoidCrossEntropyWithLogitsGrad>(end);
51138 + const auto end = fbb_.EndTable(start_);
51139 + auto o = flatbuffers::Offset<Sin>(end);
51193 + const auto end = fbb_.EndTable(start_);
51194 + auto o = flatbuffers::Offset<SkipGram>(end);
51239 + const auto end = fbb_.EndTable(start_);
51240 + auto o = flatbuffers::Offset<SliceFusion>(end);
51256 + auto axes__ = axes ? _fbb.CreateVector<int64_t>(*axes) : 0;
51289 + const auto end = fbb_.EndTable(start_);
51290 + auto o = flatbuffers::Offset<SmoothL1Loss>(end);
51330 + const auto end = fbb_.EndTable(start_);
51331 + auto o = flatbuffers::Offset<SmoothL1LossGrad>(end);
51372 + const auto end = fbb_.EndTable(start_);
51373 + auto o = flatbuffers::Offset<Softmax>(end);
51389 + auto axis__ = axis ? _fbb.CreateVector<int64_t>(*axis) : 0;
51412 + const auto end = fbb_.EndTable(start_);
51413 + auto o = flatbuffers::Offset<SoftmaxCrossEntropyWithLogits>(end);
51461 + const auto end = fbb_.EndTable(start_);
51462 + auto o = flatbuffers::Offset<SpaceToBatch>(end);
51481 + auto block_size__ = block_size ? _fbb.CreateVector<int64_t>(*block_size) : 0;
51525 + const auto end = fbb_.EndTable(start_);
51526 + auto o = flatbuffers::Offset<SpaceToBatchND>(end);
51545 + auto block_shape__ = block_shape ? _fbb.CreateVector<int64_t>(*block_shape) : 0;
51587 + const auto end = fbb_.EndTable(start_);
51588 + auto o = flatbuffers::Offset<SpaceToDepth>(end);
51630 + const auto end = fbb_.EndTable(start_);
51631 + auto o = flatbuffers::Offset<SparseSoftmaxCrossEntropyWithLogits>(end);
51661 + const auto end = fbb_.EndTable(start_);
51662 + auto o = flatbuffers::Offset<SparseToDense>(end);
51717 + const auto end = fbb_.EndTable(start_);
51718 + auto o = flatbuffers::Offset<Split>(end);
51740 + auto size_splits__ = size_splits ? _fbb.CreateVector<int64_t>(*size_splits) : 0;
51765 + const auto end = fbb_.EndTable(start_);
51766 + auto o = flatbuffers::Offset<Sqrt>(end);
51805 + const auto end = fbb_.EndTable(start_);
51806 + auto o = flatbuffers::Offset<Squeeze>(end);
51822 + auto axis__ = axis ? _fbb.CreateVector<int64_t>(*axis) : 0;
51845 + const auto end = fbb_.EndTable(start_);
51846 + auto o = flatbuffers::Offset<Square>(end);
51874 + const auto end = fbb_.EndTable(start_);
51875 + auto o = flatbuffers::Offset<SquaredDifference>(end);
51913 + const auto end = fbb_.EndTable(start_);
51914 + auto o = flatbuffers::Offset<Stack>(end);
51986 + const auto end = fbb_.EndTable(start_);
51987 + auto o = flatbuffers::Offset<StridedSlice>(end);
52035 + const auto end = fbb_.EndTable(start_);
52036 + auto o = flatbuffers::Offset<SubFusion>(end);
52066 + const auto end = fbb_.EndTable(start_);
52067 + auto o = flatbuffers::Offset<SubGrad>(end);
52095 + const auto end = fbb_.EndTable(start_);
52096 + auto o = flatbuffers::Offset<Switch>(end);
52142 + const auto end = fbb_.EndTable(start_);
52143 + auto o = flatbuffers::Offset<TensorListFromTensor>(end);
52185 + const auto end = fbb_.EndTable(start_);
52186 + auto o = flatbuffers::Offset<TensorListGetItem>(end);
52234 + const auto end = fbb_.EndTable(start_);
52235 + auto o = flatbuffers::Offset<TensorListReserve>(end);
52277 + const auto end = fbb_.EndTable(start_);
52278 + auto o = flatbuffers::Offset<TensorListSetItem>(end);
52326 + const auto end = fbb_.EndTable(start_);
52327 + auto o = flatbuffers::Offset<TensorListStack>(end);
52370 + const auto end = fbb_.EndTable(start_);
52371 + auto o = flatbuffers::Offset<TileFusion>(end);
52387 + auto dims__ = dims ? _fbb.CreateVector<int64_t>(*dims) : 0;
52436 + const auto end = fbb_.EndTable(start_);
52437 + auto o = flatbuffers::Offset<TopKFusion>(end);
52471 + const auto end = fbb_.EndTable(start_);
52472 + auto o = flatbuffers::Offset<Transpose>(end);
52500 + const auto end = fbb_.EndTable(start_);
52501 + auto o = flatbuffers::Offset<Unique>(end);
52529 + const auto end = fbb_.EndTable(start_);
52530 + auto o = flatbuffers::Offset<UnsortedSegmentSum>(end);
52569 + const auto end = fbb_.EndTable(start_);
52570 + auto o = flatbuffers::Offset<Unsqueeze>(end);
52586 + auto axis__ = axis ? _fbb.CreateVector<int64_t>(*axis) : 0;
52619 + const auto end = fbb_.EndTable(start_);
52620 + auto o = flatbuffers::Offset<Unstack>(end);
52650 + const auto end = fbb_.EndTable(start_);
52651 + auto o = flatbuffers::Offset<Where>(end);
52679 + const auto end = fbb_.EndTable(start_);
52680 + auto o = flatbuffers::Offset<ZerosLike>(end);
52708 + const auto end = fbb_.EndTable(start_);
52709 + auto o = flatbuffers::Offset<Select>(end);
52747 + const auto end = fbb_.EndTable(start_);
52748 + auto o = flatbuffers::Offset<GRU>(end);
52778 + const auto end = fbb_.EndTable(start_);
52779 + auto o = flatbuffers::Offset<NonZero>(end);
52807 + const auto end = fbb_.EndTable(start_);
52808 + auto o = flatbuffers::Offset<InvertPermutation>(end);
52836 + const auto end = fbb_.EndTable(start_);
52837 + auto o = flatbuffers::Offset<Size>(end);
52883 + const auto end = fbb_.EndTable(start_);
52884 + auto o = flatbuffers::Offset<RandomStandardNormal>(end);
52934 + const auto end = fbb_.EndTable(start_);
52935 + auto o = flatbuffers::Offset<CropAndResize>(end);
52967 + const auto end = fbb_.EndTable(start_);
52968 + auto o = flatbuffers::Offset<Erf>(end);
53038 + const auto end = fbb_.EndTable(start_);
53039 + auto o = flatbuffers::Offset<StridedSliceGrad>(end);
53077 + const auto end = fbb_.EndTable(start_);
53078 + auto o = flatbuffers::Offset<IsFinite>(end);
53106 + const auto end = fbb_.EndTable(start_);
53107 + auto o = flatbuffers::Offset<LinSpace>(end);
53153 + const auto end = fbb_.EndTable(start_);
53154 + auto o = flatbuffers::Offset<UniformReal>(end);
53186 + const auto end = fbb_.EndTable(start_);
53187 + auto o = flatbuffers::Offset<AbsGrad>(end);
53215 + const auto end = fbb_.EndTable(start_);
53216 + auto o = flatbuffers::Offset<RsqrtGrad>(end);
53244 + const auto end = fbb_.EndTable(start_);
53245 + auto o = flatbuffers::Offset<SqrtGrad>(end);
53291 + const auto end = fbb_.EndTable(start_);
53292 + auto o = flatbuffers::Offset<LayerNormGrad>(end);
53342 + const auto end = fbb_.EndTable(start_);
53343 + auto o = flatbuffers::Offset<ResizeGrad>(end);
53403 + const auto end = fbb_.EndTable(start_);
53404 + auto o = flatbuffers::Offset<Splice>(end);
53426 + auto context__ = context ? _fbb.CreateVector<int64_t>(*context) : 0;
53427 + auto forward_indexes__ = forward_indexes ? _fbb.CreateVector<int64_t>(*forward_indexes) : 0;
53462 + const auto end = fbb_.EndTable(start_);
53463 + auto o = flatbuffers::Offset<LogSoftmax>(end);
53503 + const auto end = fbb_.EndTable(start_);
53504 + auto o = flatbuffers::Offset<Call>(end);
53552 + const auto end = fbb_.EndTable(start_);
53553 + auto o = flatbuffers::Offset<CumSum>(end);
53606 + const auto end = fbb_.EndTable(start_);
53607 + auto o = flatbuffers::Offset<Custom>(end);
53626 + auto type__ = type ? _fbb.CreateString(type) : 0;
53627 + auto attr__ = attr ? _fbb.CreateVector<flatbuffers::Offset<mindspore::schema::Attribute>>(*attr)…
53696 + const auto end = fbb_.EndTable(start_);
53697 + auto o = flatbuffers::Offset<SplitWithOverlap>(end);
53725 + auto ratio__ = ratio ? _fbb.CreateVector<int64_t>(*ratio) : 0;
53726 + auto extend_top__ = extend_top ? _fbb.CreateVector<int64_t>(*extend_top) : 0;
53727 + auto extend_bottom__ = extend_bottom ? _fbb.CreateVector<int64_t>(*extend_bottom) : 0;
54018 + const auto end = fbb_.EndTable(start_);
54019 + auto o = flatbuffers::Offset<GenOP>(end);
54128 + auto kernel_size__ = kernel_size ? _fbb.CreateVector<int64_t>(*kernel_size) : 0;
54129 + auto stride__ = stride ? _fbb.CreateVector<int64_t>(*stride) : 0;
54130 + auto dilation__ = dilation ? _fbb.CreateVector<int64_t>(*dilation) : 0;
54131 + auto pad_list__ = pad_list ? _fbb.CreateVector<int64_t>(*pad_list) : 0;
54132 + auto pad__ = pad ? _fbb.CreateVector<int64_t>(*pad) : 0;
54133 + auto axes__ = axes ? _fbb.CreateVector<int64_t>(*axes) : 0;
54187 + const auto end = fbb_.EndTable(start_);
54188 + auto o = flatbuffers::Offset<RaggedRange>(end);
54226 + const auto end = fbb_.EndTable(start_);
54227 + auto o = flatbuffers::Offset<GLU>(end);
54292 + const auto end = fbb_.EndTable(start_);
54293 + auto o = flatbuffers::Offset<TensorArray>(end);
54318 + auto element_shape__ = element_shape ? _fbb.CreateVector<int32_t>(*element_shape) : 0;
54344 + const auto end = fbb_.EndTable(start_);
54345 + auto o = flatbuffers::Offset<TensorArrayRead>(end);
54373 + const auto end = fbb_.EndTable(start_);
54374 + auto o = flatbuffers::Offset<TensorArrayWrite>(end);
54445 + const auto end = fbb_.EndTable(start_);
54446 + auto o = flatbuffers::Offset<Affine>(end);
54474 + auto context__ = context ? _fbb.CreateVector<int64_t>(*context) : 0;
54501 + const auto end = fbb_.EndTable(start_);
54502 + auto o = flatbuffers::Offset<ScatterNdUpdate>(end);
54549 + const auto end = fbb_.EndTable(start_);
54550 + auto o = flatbuffers::Offset<AllGather>(end);
54569 + auto group__ = group ? _fbb.CreateString(group) : 0;
54620 + const auto end = fbb_.EndTable(start_);
54621 + auto o = flatbuffers::Offset<ReduceScatter>(end);
54643 + auto group__ = group ? _fbb.CreateString(group) : 0;
54686 + const auto end = fbb_.EndTable(start_);
54687 + auto o = flatbuffers::Offset<DynamicQuant>(end);
54793 + const auto end = fbb_.EndTable(start_);
54794 + auto o = flatbuffers::Offset<LSTMGradData>(end);
54914 + const auto end = fbb_.EndTable(start_);
54915 + auto o = flatbuffers::Offset<LSTMGradWeight>(end);
54987 + const auto end = fbb_.EndTable(start_);
54988 + auto o = flatbuffers::Offset<RandomNormal>(end);
55032 + const auto end = fbb_.EndTable(start_);
55033 + auto o = flatbuffers::Offset<NLLLoss>(end);
55073 + const auto end = fbb_.EndTable(start_);
55074 + auto o = flatbuffers::Offset<NLLLossGrad>(end);
55122 + const auto end = fbb_.EndTable(start_);
55123 + auto o = flatbuffers::Offset<FormatTranspose>(end);
55155 + const auto end = fbb_.EndTable(start_);
55156 + auto o = flatbuffers::Offset<GatherD>(end);
55210 + const auto end = fbb_.EndTable(start_);
55211 + auto o = flatbuffers::Offset<GroupNormFusion>(end);
55234 + auto ptr = reinterpret_cast<const mindspore::schema::Abs *>(obj);
55238 + auto ptr = reinterpret_cast<const mindspore::schema::Activation *>(obj);
55242 + auto ptr = reinterpret_cast<const mindspore::schema::ActivationGrad *>(obj);
55246 + auto ptr = reinterpret_cast<const mindspore::schema::Adam *>(obj);
55250 + auto ptr = reinterpret_cast<const mindspore::schema::AddFusion *>(obj);
55254 + auto ptr = reinterpret_cast<const mindspore::schema::AdderFusion *>(obj);
55258 + auto ptr = reinterpret_cast<const mindspore::schema::AddGrad *>(obj);
55262 + auto ptr = reinterpret_cast<const mindspore::schema::AddN *>(obj);
55266 + auto ptr = reinterpret_cast<const mindspore::schema::All *>(obj);
55270 + auto ptr = reinterpret_cast<const mindspore::schema::ApplyMomentum *>(obj);
55274 + auto ptr = reinterpret_cast<const mindspore::schema::ArgMaxFusion *>(obj);
55278 + auto ptr = reinterpret_cast<const mindspore::schema::ArgMinFusion *>(obj);
55282 + auto ptr = reinterpret_cast<const mindspore::schema::Assert *>(obj);
55286 + auto ptr = reinterpret_cast<const mindspore::schema::Assign *>(obj);
55290 + auto ptr = reinterpret_cast<const mindspore::schema::AssignAdd *>(obj);
55294 + auto ptr = reinterpret_cast<const mindspore::schema::AudioSpectrogram *>(obj);
55298 + auto ptr = reinterpret_cast<const mindspore::schema::AvgPoolFusion *>(obj);
55302 + auto ptr = reinterpret_cast<const mindspore::schema::AvgPoolGrad *>(obj);
55306 + auto ptr = reinterpret_cast<const mindspore::schema::BatchNorm *>(obj);
55310 + auto ptr = reinterpret_cast<const mindspore::schema::BatchNormGrad *>(obj);
55314 + auto ptr = reinterpret_cast<const mindspore::schema::BatchToSpace *>(obj);
55318 + auto ptr = reinterpret_cast<const mindspore::schema::BatchToSpaceND *>(obj);
55322 + auto ptr = reinterpret_cast<const mindspore::schema::BiasAdd *>(obj);
55326 + auto ptr = reinterpret_cast<const mindspore::schema::BinaryCrossEntropy *>(obj);
55330 + auto ptr = reinterpret_cast<const mindspore::schema::BinaryCrossEntropyGrad *>(obj);
55334 + auto ptr = reinterpret_cast<const mindspore::schema::BiasAddGrad *>(obj);
55338 + auto ptr = reinterpret_cast<const mindspore::schema::BroadcastTo *>(obj);
55342 + auto ptr = reinterpret_cast<const mindspore::schema::Cast *>(obj);
55346 + auto ptr = reinterpret_cast<const mindspore::schema::Ceil *>(obj);
55350 + auto ptr = reinterpret_cast<const mindspore::schema::Clip *>(obj);
55354 + auto ptr = reinterpret_cast<const mindspore::schema::Concat *>(obj);
55358 + auto ptr = reinterpret_cast<const mindspore::schema::Attention *>(obj);
55362 + auto ptr = reinterpret_cast<const mindspore::schema::Conv2DBackpropFilterFusion *>(obj);
55366 + auto ptr = reinterpret_cast<const mindspore::schema::Conv2DBackpropInputFusion *>(obj);
55370 + auto ptr = reinterpret_cast<const mindspore::schema::Conv2DFusion *>(obj);
55374 + auto ptr = reinterpret_cast<const mindspore::schema::Conv2dTransposeFusion *>(obj);
55378 + auto ptr = reinterpret_cast<const mindspore::schema::Cos *>(obj);
55382 + auto ptr = reinterpret_cast<const mindspore::schema::ConstantOfShape *>(obj);
55386 + auto ptr = reinterpret_cast<const mindspore::schema::Crop *>(obj);
55390 + auto ptr = reinterpret_cast<const mindspore::schema::CustomExtractFeatures *>(obj);
55394 + auto ptr = reinterpret_cast<const mindspore::schema::CustomNormalize *>(obj);
55398 + auto ptr = reinterpret_cast<const mindspore::schema::CustomPredict *>(obj);
55402 + auto ptr = reinterpret_cast<const mindspore::schema::DeConv2DGradFilter *>(obj);
55406 + auto ptr = reinterpret_cast<const mindspore::schema::Depend *>(obj);
55410 + auto ptr = reinterpret_cast<const mindspore::schema::DepthToSpace *>(obj);
55414 + auto ptr = reinterpret_cast<const mindspore::schema::DetectionPostProcess *>(obj);
55418 + auto ptr = reinterpret_cast<const mindspore::schema::DivFusion *>(obj);
55422 + auto ptr = reinterpret_cast<const mindspore::schema::DivGrad *>(obj);
55426 + auto ptr = reinterpret_cast<const mindspore::schema::Dropout *>(obj);
55430 + auto ptr = reinterpret_cast<const mindspore::schema::DropoutGrad *>(obj);
55434 + auto ptr = reinterpret_cast<const mindspore::schema::Elu *>(obj);
55438 + auto ptr = reinterpret_cast<const mindspore::schema::Eltwise *>(obj);
55442 + auto ptr = reinterpret_cast<const mindspore::schema::Equal *>(obj);
55446 + auto ptr = reinterpret_cast<const mindspore::schema::EmbeddingLookupFusion *>(obj);
55450 + auto ptr = reinterpret_cast<const mindspore::schema::ExpFusion *>(obj);
55454 + auto ptr = reinterpret_cast<const mindspore::schema::ExpandDims *>(obj);
55458 + auto ptr = reinterpret_cast<const mindspore::schema::FakeQuantWithMinMaxVars *>(obj);
55462 + auto ptr = reinterpret_cast<const mindspore::schema::FakeQuantWithMinMaxVarsPerChannel *>(ob…
55466 + auto ptr = reinterpret_cast<const mindspore::schema::FftReal *>(obj);
55470 + auto ptr = reinterpret_cast<const mindspore::schema::FftImag *>(obj);
55474 + auto ptr = reinterpret_cast<const mindspore::schema::Flatten *>(obj);
55478 + auto ptr = reinterpret_cast<const mindspore::schema::FlattenGrad *>(obj);
55482 + auto ptr = reinterpret_cast<const mindspore::schema::Floor *>(obj);
55486 + auto ptr = reinterpret_cast<const mindspore::schema::FloorDiv *>(obj);
55490 + auto ptr = reinterpret_cast<const mindspore::schema::FloorMod *>(obj);
55494 + auto ptr = reinterpret_cast<const mindspore::schema::Fill *>(obj);
55498 + auto ptr = reinterpret_cast<const mindspore::schema::FullConnection *>(obj);
55502 + auto ptr = reinterpret_cast<const mindspore::schema::FusedBatchNorm *>(obj);
55506 + auto ptr = reinterpret_cast<const mindspore::schema::Gather *>(obj);
55510 + auto ptr = reinterpret_cast<const mindspore::schema::GatherNd *>(obj);
55514 + auto ptr = reinterpret_cast<const mindspore::schema::Greater *>(obj);
55518 + auto ptr = reinterpret_cast<const mindspore::schema::GreaterEqual *>(obj);
55522 + auto ptr = reinterpret_cast<const mindspore::schema::HashtableLookup *>(obj);
55526 + auto ptr = reinterpret_cast<const mindspore::schema::InstanceNorm *>(obj);
55530 + auto ptr = reinterpret_cast<const mindspore::schema::LayerNormFusion *>(obj);
55534 + auto ptr = reinterpret_cast<const mindspore::schema::LeakyRelu *>(obj);
55538 + auto ptr = reinterpret_cast<const mindspore::schema::Less *>(obj);
55542 + auto ptr = reinterpret_cast<const mindspore::schema::LessEqual *>(obj);
55546 + auto ptr = reinterpret_cast<const mindspore::schema::Log *>(obj);
55550 + auto ptr = reinterpret_cast<const mindspore::schema::LogGrad *>(obj);
55554 + auto ptr = reinterpret_cast<const mindspore::schema::LogicalAnd *>(obj);
55558 + auto ptr = reinterpret_cast<const mindspore::schema::LogicalNot *>(obj);
55562 + auto ptr = reinterpret_cast<const mindspore::schema::LogicalOr *>(obj);
55566 + auto ptr = reinterpret_cast<const mindspore::schema::LpNormalization *>(obj);
55570 + auto ptr = reinterpret_cast<const mindspore::schema::LRN *>(obj);
55574 + auto ptr = reinterpret_cast<const mindspore::schema::LshProjection *>(obj);
55578 + auto ptr = reinterpret_cast<const mindspore::schema::LSTM *>(obj);
55582 + auto ptr = reinterpret_cast<const mindspore::schema::L2NormalizeFusion *>(obj);
55586 + auto ptr = reinterpret_cast<const mindspore::schema::MatMulFusion *>(obj);
55590 + auto ptr = reinterpret_cast<const mindspore::schema::Maximum *>(obj);
55594 + auto ptr = reinterpret_cast<const mindspore::schema::MaximumGrad *>(obj);
55598 + auto ptr = reinterpret_cast<const mindspore::schema::MaxPoolFusion *>(obj);
55602 + auto ptr = reinterpret_cast<const mindspore::schema::MaxPoolGrad *>(obj);
55606 + auto ptr = reinterpret_cast<const mindspore::schema::SwitchLayer *>(obj);
55610 + auto ptr = reinterpret_cast<const mindspore::schema::Mfcc *>(obj);
55614 + auto ptr = reinterpret_cast<const mindspore::schema::Minimum *>(obj);
55618 + auto ptr = reinterpret_cast<const mindspore::schema::MinimumGrad *>(obj);
55622 + auto ptr = reinterpret_cast<const mindspore::schema::Mod *>(obj);
55626 + auto ptr = reinterpret_cast<const mindspore::schema::MulFusion *>(obj);
55630 + auto ptr = reinterpret_cast<const mindspore::schema::MulGrad *>(obj);
55634 + auto ptr = reinterpret_cast<const mindspore::schema::Neg *>(obj);
55638 + auto ptr = reinterpret_cast<const mindspore::schema::NegGrad *>(obj);
55642 + auto ptr = reinterpret_cast<const mindspore::schema::NotEqual *>(obj);
55646 + auto ptr = reinterpret_cast<const mindspore::schema::NonMaxSuppression *>(obj);
55650 + auto ptr = reinterpret_cast<const mindspore::schema::OneHot *>(obj);
55654 + auto ptr = reinterpret_cast<const mindspore::schema::OnesLike *>(obj);
55658 + auto ptr = reinterpret_cast<const mindspore::schema::PadFusion *>(obj);
55662 + auto ptr = reinterpret_cast<const mindspore::schema::PartialFusion *>(obj);
55666 + auto ptr = reinterpret_cast<const mindspore::schema::PowerGrad *>(obj);
55670 + auto ptr = reinterpret_cast<const mindspore::schema::PowFusion *>(obj);
55674 + auto ptr = reinterpret_cast<const mindspore::schema::PriorBox *>(obj);
55678 + auto ptr = reinterpret_cast<const mindspore::schema::PReLUFusion *>(obj);
55682 + auto ptr = reinterpret_cast<const mindspore::schema::QuantDTypeCast *>(obj);
55686 + auto ptr = reinterpret_cast<const mindspore::schema::Rank *>(obj);
55690 + auto ptr = reinterpret_cast<const mindspore::schema::Range *>(obj);
55694 + auto ptr = reinterpret_cast<const mindspore::schema::Reciprocal *>(obj);
55698 + auto ptr = reinterpret_cast<const mindspore::schema::RealDiv *>(obj);
55702 + auto ptr = reinterpret_cast<const mindspore::schema::ReduceFusion *>(obj);
55706 + auto ptr = reinterpret_cast<const mindspore::schema::Reshape *>(obj);
55710 + auto ptr = reinterpret_cast<const mindspore::schema::Resize *>(obj);
55714 + auto ptr = reinterpret_cast<const mindspore::schema::ReverseSequence *>(obj);
55718 + auto ptr = reinterpret_cast<const mindspore::schema::ReverseV2 *>(obj);
55722 + auto ptr = reinterpret_cast<const mindspore::schema::Rfft *>(obj);
55726 + auto ptr = reinterpret_cast<const mindspore::schema::ROIPooling *>(obj);
55730 + auto ptr = reinterpret_cast<const mindspore::schema::Round *>(obj);
55734 + auto ptr = reinterpret_cast<const mindspore::schema::Rsqrt *>(obj);
55738 + auto ptr = reinterpret_cast<const mindspore::schema::ScaleFusion *>(obj);
55742 + auto ptr = reinterpret_cast<const mindspore::schema::ScatterNd *>(obj);
55746 + auto ptr = reinterpret_cast<const mindspore::schema::SGD *>(obj);
55750 + auto ptr = reinterpret_cast<const mindspore::schema::Shape *>(obj);
55754 + auto ptr = reinterpret_cast<const mindspore::schema::SigmoidCrossEntropyWithLogits *>(obj);
55758 + auto ptr = reinterpret_cast<const mindspore::schema::SigmoidCrossEntropyWithLogitsGrad *>(ob…
55762 + auto ptr = reinterpret_cast<const mindspore::schema::Sin *>(obj);
55766 + auto ptr = reinterpret_cast<const mindspore::schema::SkipGram *>(obj);
55770 + auto ptr = reinterpret_cast<const mindspore::schema::SliceFusion *>(obj);
55774 + auto ptr = reinterpret_cast<const mindspore::schema::SmoothL1Loss *>(obj);
55778 + auto ptr = reinterpret_cast<const mindspore::schema::SmoothL1LossGrad *>(obj);
55782 + auto ptr = reinterpret_cast<const mindspore::schema::Softmax *>(obj);
55786 + auto ptr = reinterpret_cast<const mindspore::schema::SoftmaxCrossEntropyWithLogits *>(obj);
55790 + auto ptr = reinterpret_cast<const mindspore::schema::SpaceToBatch *>(obj);
55794 + auto ptr = reinterpret_cast<const mindspore::schema::SpaceToBatchND *>(obj);
55798 + auto ptr = reinterpret_cast<const mindspore::schema::SpaceToDepth *>(obj);
55802 + auto ptr = reinterpret_cast<const mindspore::schema::SparseSoftmaxCrossEntropyWithLogits *>(…
55806 + auto ptr = reinterpret_cast<const mindspore::schema::SparseToDense *>(obj);
55810 + auto ptr = reinterpret_cast<const mindspore::schema::Split *>(obj);
55814 + auto ptr = reinterpret_cast<const mindspore::schema::Sqrt *>(obj);
55818 + auto ptr = reinterpret_cast<const mindspore::schema::Squeeze *>(obj);
55822 + auto ptr = reinterpret_cast<const mindspore::schema::Square *>(obj);
55826 + auto ptr = reinterpret_cast<const mindspore::schema::SquaredDifference *>(obj);
55830 + auto ptr = reinterpret_cast<const mindspore::schema::Stack *>(obj);
55834 + auto ptr = reinterpret_cast<const mindspore::schema::StridedSlice *>(obj);
55838 + auto ptr = reinterpret_cast<const mindspore::schema::SubFusion *>(obj);
55842 + auto ptr = reinterpret_cast<const mindspore::schema::SubGrad *>(obj);
55846 + auto ptr = reinterpret_cast<const mindspore::schema::Switch *>(obj);
55850 + auto ptr = reinterpret_cast<const mindspore::schema::TensorListFromTensor *>(obj);
55854 + auto ptr = reinterpret_cast<const mindspore::schema::TensorListGetItem *>(obj);
55858 + auto ptr = reinterpret_cast<const mindspore::schema::TensorListReserve *>(obj);
55862 + auto ptr = reinterpret_cast<const mindspore::schema::TensorListSetItem *>(obj);
55866 + auto ptr = reinterpret_cast<const mindspore::schema::TensorListStack *>(obj);
55870 + auto ptr = reinterpret_cast<const mindspore::schema::TileFusion *>(obj);
55874 + auto ptr = reinterpret_cast<const mindspore::schema::TopKFusion *>(obj);
55878 + auto ptr = reinterpret_cast<const mindspore::schema::Transpose *>(obj);
55882 + auto ptr = reinterpret_cast<const mindspore::schema::Unique *>(obj);
55886 + auto ptr = reinterpret_cast<const mindspore::schema::UnsortedSegmentSum *>(obj);
55890 + auto ptr = reinterpret_cast<const mindspore::schema::Unsqueeze *>(obj);
55894 + auto ptr = reinterpret_cast<const mindspore::schema::Unstack *>(obj);
55898 + auto ptr = reinterpret_cast<const mindspore::schema::LSTMGrad *>(obj);
55902 + auto ptr = reinterpret_cast<const mindspore::schema::Where *>(obj);
55906 + auto ptr = reinterpret_cast<const mindspore::schema::ZerosLike *>(obj);
55910 + auto ptr = reinterpret_cast<const mindspore::schema::Select *>(obj);
55914 + auto ptr = reinterpret_cast<const mindspore::schema::ScatterNdUpdate *>(obj);
55918 + auto ptr = reinterpret_cast<const mindspore::schema::GRU *>(obj);
55922 + auto ptr = reinterpret_cast<const mindspore::schema::NonZero *>(obj);
55926 + auto ptr = reinterpret_cast<const mindspore::schema::InvertPermutation *>(obj);
55930 + auto ptr = reinterpret_cast<const mindspore::schema::Size *>(obj);
55934 + auto ptr = reinterpret_cast<const mindspore::schema::RandomStandardNormal *>(obj);
55938 + auto ptr = reinterpret_cast<const mindspore::schema::CropAndResize *>(obj);
55942 + auto ptr = reinterpret_cast<const mindspore::schema::Erf *>(obj);
55946 + auto ptr = reinterpret_cast<const mindspore::schema::StridedSliceGrad *>(obj);
55950 + auto ptr = reinterpret_cast<const mindspore::schema::IsFinite *>(obj);
55954 + auto ptr = reinterpret_cast<const mindspore::schema::LinSpace *>(obj);
55958 + auto ptr = reinterpret_cast<const mindspore::schema::UniformReal *>(obj);
55962 + auto ptr = reinterpret_cast<const mindspore::schema::AbsGrad *>(obj);
55966 + auto ptr = reinterpret_cast<const mindspore::schema::RsqrtGrad *>(obj);
55970 + auto ptr = reinterpret_cast<const mindspore::schema::SqrtGrad *>(obj);
55974 + auto ptr = reinterpret_cast<const mindspore::schema::LayerNormGrad *>(obj);
55978 + auto ptr = reinterpret_cast<const mindspore::schema::ResizeGrad *>(obj);
55982 + auto ptr = reinterpret_cast<const mindspore::schema::Splice *>(obj);
55986 + auto ptr = reinterpret_cast<const mindspore::schema::LogSoftmax *>(obj);
55990 + auto ptr = reinterpret_cast<const mindspore::schema::Call *>(obj);
55994 + auto ptr = reinterpret_cast<const mindspore::schema::Custom *>(obj);
55998 + auto ptr = reinterpret_cast<const mindspore::schema::CumSum *>(obj);
56002 + auto ptr = reinterpret_cast<const mindspore::schema::SplitWithOverlap *>(obj);
56006 + auto ptr = reinterpret_cast<const mindspore::schema::GenOP *>(obj);
56010 + auto ptr = reinterpret_cast<const mindspore::schema::RaggedRange *>(obj);
56014 + auto ptr = reinterpret_cast<const mindspore::schema::GLU *>(obj);
56018 + auto ptr = reinterpret_cast<const mindspore::schema::TensorArray *>(obj);
56022 + auto ptr = reinterpret_cast<const mindspore::schema::TensorArrayRead *>(obj);
56026 + auto ptr = reinterpret_cast<const mindspore::schema::TensorArrayWrite *>(obj);
56030 + auto ptr = reinterpret_cast<const mindspore::schema::Affine *>(obj);
56034 + auto ptr = reinterpret_cast<const mindspore::schema::AllGather *>(obj);
56038 + auto ptr = reinterpret_cast<const mindspore::schema::ReduceScatter *>(obj);
56042 + auto ptr = reinterpret_cast<const mindspore::schema::DynamicQuant *>(obj);
56046 + auto ptr = reinterpret_cast<const mindspore::schema::LSTMGradData *>(obj);
56050 + auto ptr = reinterpret_cast<const mindspore::schema::LSTMGradWeight *>(obj);
56054 + auto ptr = reinterpret_cast<const mindspore::schema::RandomNormal *>(obj);
56058 + auto ptr = reinterpret_cast<const mindspore::schema::NLLLoss *>(obj);
56062 + auto ptr = reinterpret_cast<const mindspore::schema::NLLLossGrad *>(obj);
56066 + auto ptr = reinterpret_cast<const mindspore::schema::FormatTranspose *>(obj);
56070 + auto ptr = reinterpret_cast<const mindspore::schema::GatherD *>(obj);
56074 + auto ptr = reinterpret_cast<const mindspore::schema::GroupNormFusion *>(obj);
56706 + const auto end = fbb_.EndTable(start_);
56707 + auto o = flatbuffers::Offset<Vec>(end);
56723 + auto data__ = data ? _fbb.CreateVector<int64_t>(*data) : 0;
56758 + const auto end = fbb_.EndTable(start_);
56759 + auto o = flatbuffers::Offset<Vec2D>(end);
56775 + auto data__ = data ? _fbb.CreateVector<flatbuffers::Offset<mindspore::schema::Vec>>(*data) : 0;
56818 + const auto end = fbb_.EndTable(start_);
56819 + auto o = flatbuffers::Offset<Attribute>(end);
56838 + auto name__ = name ? _fbb.CreateString(name) : 0;
56839 + auto data__ = data ? _fbb.CreateVector<uint8_t>(*data) : 0;