MNN/source/shape/ShapeStridedSlice.cpp

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2019-04-17 10:49:11 +08:00
//
// ShapeStridedSlice.cpp
// MNN
//
// Created by MNN on 2019/01/10.
// Copyright © 2018, Alibaba Group Holding Limited
//
#include <algorithm>
#include <array>
#include "CPUStridedSlice.hpp"
#include "CommonOptFunction.h"
#include "Macro.h"
#include "SizeComputer.hpp"
#include "TensorUtils.hpp"
namespace MNN {
class StridedSliceComputer : public SizeComputer {
public:
virtual bool onComputeSize(const MNN::Op *op, const std::vector<Tensor *> &inputs,
const std::vector<Tensor *> &outputs) const override {
MNN_ASSERT(4 == inputs.size());
MNN_ASSERT(1 == outputs.size());
const std::string name = op->name()->c_str();
Tensor *input = inputs[0];
const int inputDimension = input->buffer().dimensions;
MNN_ASSERT(inputDimension > 0);
// input haven't realized
auto output = outputs[0];
auto parameter = op->main_as_StridedSliceParam();
Tensor *begin = inputs[1];
Tensor *end = inputs[2];
Tensor *strided = inputs[3];
std::shared_ptr<Tensor> tempBegin;
std::shared_ptr<Tensor> tempEnd;
std::shared_ptr<Tensor> tempStrided;
// copy data from device to host if needed
if (!begin->host<int32_t>() && begin->deviceId()) {
tempBegin.reset(Tensor::createHostTensorFromDevice(begin, true));
begin = tempBegin.get();
}
if (!end->host<int32_t>() && end->deviceId()) {
tempEnd.reset(Tensor::createHostTensorFromDevice(end, true));
end = tempEnd.get();
}
if (!strided->host<int32_t>() && strided->deviceId()) {
tempStrided.reset(Tensor::createHostTensorFromDevice(strided, true));
strided = tempStrided.get();
}
MNN_ASSERT(begin->buffer().dimensions == end->buffer().dimensions &&
begin->buffer().dimensions == strided->buffer().dimensions);
std::vector<int32_t> inputShape(input->buffer().dimensions);
for (int i = 0; i < input->buffer().dimensions; i++) {
inputShape[i] = input->buffer().dim[i].extent;
}
int stridedSliceDimension = begin->buffer().dim[0].extent;
std::vector<int32_t> beginShape(stridedSliceDimension);
std::vector<int32_t> endShape(stridedSliceDimension);
std::vector<int32_t> stridedShape(stridedSliceDimension);
std::vector<int32_t> outputShape;
std::vector<int32_t> outputShapeShrinked;
std::vector<int32_t> beginMask(stridedSliceDimension);
for (int i = 0; i < stridedSliceDimension; i++) {
beginMask[i] = parameter->beginMask() & (1 << i);
}
std::vector<int32_t> endMask(stridedSliceDimension);
for (int i = 0; i < stridedSliceDimension; i++) {
endMask[i] = parameter->endMask() & (1 << i);
}
std::vector<int32_t> shrinkAxisMask(stridedSliceDimension);
for (int i = 0; i < stridedSliceDimension; i++) {
shrinkAxisMask[i] = parameter->shrinkAxisMask() & (1 << i);
}
int ellipsisMaskNonZeroBitPosition = 0;
for (int i = 0; i < stridedSliceDimension; i++) {
int temp = parameter->ellipsisMask() & (1 << i);
if (temp != 0) {
ellipsisMaskNonZeroBitPosition = i; // only one non-zero bit is allowed in ellipsisMask
break;
}
}
std::vector<int32_t> newAxisMask(stridedSliceDimension);
for (int i = 0; i < stridedSliceDimension; i++) {
newAxisMask[i] = parameter->newAxisMask() & (1 << i);
}
if (parameter->ellipsisMask() != 0 || parameter->newAxisMask() != 0) {
MNN_ASSERT(false); // TODO: do not support these two mask now
}
for (int i = 0; i < stridedSliceDimension; i++) {
if (beginMask[i] > 0) {
beginShape[i] = 0;
} else {
beginShape[i] = std::min(inputShape[i], begin->host<int32_t>()[i]);
}
if (beginShape[i] < 0) {
beginShape[i] += input->buffer().dim[i].extent;
}
MNN_ASSERT(beginShape[i] >= 0);
endShape[i] = endMask[i] > 0
? inputShape[i]
: (end->host<int32_t>()[i] > inputShape[i] ? inputShape[i] : end->host<int32_t>()[i]);
if (endShape[i] < 0) {
endShape[i] += input->buffer().dim[i].extent;
}
MNN_ASSERT(endShape[i] >= 0);
stridedShape[i] = shrinkAxisMask[i] > 0 ? 1 : strided->host<int32_t>()[i];
if (endShape[i] < beginShape[i]) {
int t = beginShape[i];
beginShape[i] = endShape[i];
endShape[i] = t;
MNN_ASSERT(stridedShape[i] != 0);
if (stridedShape[i] < 0) {
stridedShape[i] = -stridedShape[i];
} else {
// MNN_ASSERT(false); // TODO: should be the wrong case, but there is one in linfeng's faster
// rcnn face model
beginShape[i] = endShape[i]; // TODO: temp solution
}
}
if (shrinkAxisMask[i] == 0) {
int size = (endShape[i] - beginShape[i] - 1) / stridedShape[i] + 1;
outputShape.push_back(size);
outputShapeShrinked.push_back(size);
} else {
outputShape.push_back(1);
}
}
int outputDimensionsWithoutRemain = (int)outputShape.size();
int dimensionRemained = input->buffer().dimensions - stridedSliceDimension;
for (int i = 0; i < dimensionRemained; i++) {
outputShape.push_back(input->buffer().dim[outputDimensionsWithoutRemain + i].extent);
outputShapeShrinked.push_back(input->buffer().dim[outputDimensionsWithoutRemain + i].extent);
}
output->buffer().dimensions = (int)outputShapeShrinked.size();
output->buffer().type = input->buffer().type;
output->buffer().dim[0].extent = 1;
for (int i = 0; i < outputShapeShrinked.size(); i++) {
output->buffer().dim[i].extent = outputShapeShrinked[i];
output->buffer().dim[i].flags = 0;
}
return true;
}
};
REGISTER_SHAPE(StridedSliceComputer, OpType_StridedSlice);
} // namespace MNN