mirror of https://github.com/alibaba/MNN.git
54 lines
1.6 KiB
C++
54 lines
1.6 KiB
C++
//
|
|
// ShapeUnpack.cpp
|
|
// MNN
|
|
//
|
|
// Created by MNN on 2019/01/10.
|
|
// Copyright © 2018, Alibaba Group Holding Limited
|
|
//
|
|
|
|
#include "core/Macro.h"
|
|
#include "core/SizeComputer.hpp"
|
|
|
|
namespace MNN {
|
|
|
|
class UnpackComputer : public SizeComputer {
|
|
virtual bool onComputeSize(const MNN::Op *op, const std::vector<Tensor *> &inputs,
|
|
const std::vector<Tensor *> &outputs) const override {
|
|
if (nullptr == op || inputs.empty()) {
|
|
// Avoid crash for special model
|
|
return false;
|
|
}
|
|
auto unpack = op->main_as_Axis();
|
|
const int axis = unpack->axis();
|
|
|
|
auto &input = inputs[0]->buffer();
|
|
|
|
const int inputDimensions = input.dimensions;
|
|
MNN_ASSERT(1 <= inputDimensions);
|
|
|
|
std::vector<int> outDims;
|
|
for (int i = 0; i < inputDimensions; i++) {
|
|
if (axis == i) {
|
|
continue;
|
|
}
|
|
outDims.push_back(input.dim[i].extent);
|
|
}
|
|
const int outputDimensions = inputDimensions - 1;
|
|
MNN_ASSERT(outDims.size() == outputDimensions);
|
|
for (int i = 0; i < outputs.size(); i++) {
|
|
auto &output = outputs[i]->buffer();
|
|
output.dimensions = outputDimensions;
|
|
output.type = input.type;
|
|
for (int j = 0; j < outputDimensions; j++) {
|
|
output.dim[j].extent = outDims[j];
|
|
}
|
|
TensorUtils::getDescribe(outputs[i])->dimensionFormat = TensorUtils::getDescribe(inputs[0])->dimensionFormat;
|
|
}
|
|
|
|
return true;
|
|
}
|
|
};
|
|
|
|
REGISTER_SHAPE(UnpackComputer, OpType_Unpack);
|
|
} // namespace MNN
|