mirror of https://github.com/alibaba/MNN.git
105 lines
3.7 KiB
C++
105 lines
3.7 KiB
C++
//
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// ShapeArgMax.cpp
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// MNN
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//
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// Created by MNN on 2019/01/10.
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// Copyright © 2018, Alibaba Group Holding Limited
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//
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#include "shape/SizeComputer.hpp"
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#include "core/Macro.h"
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#include <vector>
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namespace MNN {
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class ArgMaxComputer : public SizeComputer {
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virtual bool onComputeSize(const MNN::Op *op, const std::vector<Tensor *> &inputs,
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const std::vector<Tensor *> &outputs) const override {
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MNN_ASSERT(1 == inputs.size());
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MNN_ASSERT(1 == outputs.size());
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// copy dims
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auto &input = inputs[0]->buffer();
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auto &output = outputs[0]->buffer();
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output.dimensions = input.dimensions;
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memcpy(output.dim, input.dim, sizeof(halide_dimension_t) * input.dimensions);
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auto argMax = op->main_as_ArgMax();
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const auto inputDimensionFormat = TensorUtils::getDescribe(inputs[0])->dimensionFormat;
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TensorUtils::getDescribe(outputs[0])->dimensionFormat = inputDimensionFormat;
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if (inputDimensionFormat != MNN_DATA_FORMAT_NC4HW4) {
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int axis = argMax->axis();
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if(axis < 0){
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axis = input.dimensions + axis;
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}
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// reduce axis dimension
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output.dimensions = input.dimensions - 1;
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for (int i = 0, j = 0; i < input.dimensions; ++i) {
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if (i == axis) {
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continue;
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}
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output.dim[j].extent = input.dim[i].extent;
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j++;
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}
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output.dim[input.dimensions - 1].extent = 0;
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// set output data type to be INT(according to tensorflow implementation)
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output.type = halide_type_of<int>();
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} else {
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if (argMax->axis() == 0) {
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// Legacy code
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// key extent
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// really legacy
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output.type = halide_type_of<float>();
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int keyExtent = argMax->topK();
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if (argMax->outMaxVal()) {
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keyExtent *= 2;
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}
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if (input.dim[3].extent > 1) {
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output.dim[3].extent = keyExtent;
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} else if (input.dim[2].extent > 1) { // iw = ow = 1
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output.dim[2].extent = keyExtent;
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} else { // iw = ow = 1, ih = oh = 1;
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output.dim[1].extent = keyExtent;
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}
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} else {
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TensorUtils::getDescribe(outputs[0])->dimensionFormat = inputDimensionFormat;
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output.type = halide_type_of<float>();
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int topK = argMax->topK();
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int axis = argMax->axis();
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// in caffe, axis may not exist, we set it to 10000 to indicate this situation
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// see file: tools/converter/source/caffe/ArgMax.cpp
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if (axis != 10000) {
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if (argMax->outMaxVal()) {
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output.dim[axis].extent = topK * 2;
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} else {
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output.dim[axis].extent = topK;
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}
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} else {
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std::vector<int> outputShape(input.dimensions, 1);
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outputShape[0] = input.dim[0].extent;
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outputShape[2] = topK;
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if (argMax->outMaxVal()) {
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outputShape[1] = 2;
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}
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for (int ii = 0; ii < outputShape.size(); ii++) {
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output.dim[ii].extent = outputShape[ii];
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}
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}
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}
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}
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return true;
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}
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};
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REGISTER_SHAPE(ArgMaxComputer, OpType_ArgMax);
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REGISTER_SHAPE(ArgMaxComputer, OpType_ArgMin);
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} // namespace MNN
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