wehub-resource-sync
98 lines
3.4 KiB
C++
98 lines
3.4 KiB
C++
//
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// ReductionTf.cpp
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// MNNConverter
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//
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// Created by MNN on 2019/01/31.
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// Copyright © 2018, Alibaba Group Holding Limited
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//
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#include <string.h>
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#include "TfUtils.hpp"
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#include "tfOpConverter.hpp"
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#include "graph.pb.h"
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DECLARE_OP_CONVERTER(ReductionTf);
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MNN::OpType ReductionTf::opType() {
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return MNN::OpType_Reduction;
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}
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MNN::OpParameter ReductionTf::type() {
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return MNN::OpParameter_ReductionParam;
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}
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void ReductionTf::run(MNN::OpT *dstOp, TmpNode *srcNode) {
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auto reductionParam = new MNN::ReductionParamT;
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// reduction parameter
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tensorflow::AttrValue value;
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reductionParam->dType = MNN::DataType_DT_FLOAT;
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if (find_attr_value(srcNode->tfNode, "T", value)) {
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reductionParam->dType = (MNN::DataType)value.type();
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}
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reductionParam->keepDims = false;
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if (find_attr_value(srcNode->tfNode, "keep_dims", value)) {
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reductionParam->keepDims = value.b();
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}
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#ifdef TF_CONVERT_ORIGIN
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TmpNode *constNode = tempGraph->_getTmpNode(srcNode->inEdges[1]);
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if (constNode->opType == "Const") {
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if (find_attr_value(constNode->tfNode, "value", value)) {
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const tensorflow::TensorProto &reductionIndices = value.tensor();
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const tensorflow::TensorShapeProto &reductionIndicesShape = reductionIndices.tensor_shape();
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int dimSize = 1;
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if (reductionIndicesShape.dim_size() > 0) {
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dimSize = reductionIndicesShape.dim(0).size();
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}
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reductionParam->dim.resize(dimSize);
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if (reductionIndices.int_val_size() > 0) {
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for (int i = 0; i < dimSize; ++i) {
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reductionParam->dim[i] = reductionIndices.int_val(i);
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}
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} else {
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DCHECK((MNN::DataType)reductionIndices.dtype() == MNN::DataType_DT_INT32);
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DCHECK(reductionIndices.tensor_content().size() > 0);
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const int *dimData = (int *)reductionIndices.tensor_content().c_str();
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for (int i = 0; i < dimSize; i++) {
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reductionParam->dim[i] = dimData[i];
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}
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}
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}
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}
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#endif
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// reduction operation
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if (srcNode->opType == "Mean") {
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reductionParam->operation = MNN::ReductionType_MEAN;
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} else if (srcNode->opType == "Max") {
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reductionParam->operation = MNN::ReductionType_MAXIMUM;
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} else if (srcNode->opType == "Min") {
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reductionParam->operation = MNN::ReductionType_MINIMUM;
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} else if (srcNode->opType == "Sum") {
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reductionParam->operation = MNN::ReductionType_SUM;
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} else if (srcNode->opType == "Any") {
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reductionParam->operation = MNN::ReductionType_ANY;
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} else if (srcNode->opType == "All") {
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reductionParam->operation = MNN::ReductionType_ALL;
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} else if (srcNode->opType == "Prod") {
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reductionParam->operation = MNN::ReductionType_PROD;
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} else {
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DLOG(ERROR) << "MNN Converter Not "
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"Supported!!! ===> "
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<< srcNode->opType;
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}
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reductionParam->coeff = 0.0f; // defalut
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dstOp->main.value = reductionParam;
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}
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REGISTER_CONVERTER(ReductionTf, Mean);
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REGISTER_CONVERTER(ReductionTf, Max);
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REGISTER_CONVERTER(ReductionTf, Min);
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REGISTER_CONVERTER(ReductionTf, Any);
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REGISTER_CONVERTER(ReductionTf, All);
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REGISTER_CONVERTER(ReductionTf, Sum);
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REGISTER_CONVERTER(ReductionTf, Prod);
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