mirror of https://github.com/alibaba/MNN.git
42 lines
1.3 KiB
C++
42 lines
1.3 KiB
C++
//
|
|
// ShapeShape.cpp
|
|
// MNN
|
|
//
|
|
// Created by MNN on 2019/01/10.
|
|
// Copyright © 2018, Alibaba Group Holding Limited
|
|
//
|
|
|
|
#include "shape/SizeComputer.hpp"
|
|
#include "core/Macro.h"
|
|
#include "core/TensorUtils.hpp"
|
|
|
|
namespace MNN {
|
|
|
|
class ShapeSizeComputer : public SizeComputer {
|
|
virtual bool onComputeSize(const MNN::Op* op, const std::vector<Tensor*>& inputs,
|
|
const std::vector<Tensor*>& outputs) const override {
|
|
MNN_ASSERT(1 <= inputs.size());
|
|
MNN_ASSERT(1 == outputs.size());
|
|
auto& ib = inputs[0]->buffer();
|
|
auto& ob = outputs[0]->buffer();
|
|
|
|
ob.dimensions = 1;
|
|
outputs[0]->setType(DataType_DT_INT32);
|
|
TensorUtils::getDescribe(outputs[0])->dimensionFormat = op->defaultDimentionFormat();
|
|
auto inputFormat = TensorUtils::getDescribe(inputs[0])->dimensionFormat;
|
|
if (inputFormat == MNN_DATA_FORMAT_NC4HW4 && op->defaultDimentionFormat() == MNN_DATA_FORMAT_NHWC) {
|
|
// For compability
|
|
ob.dim[0].extent = 4;
|
|
} else {
|
|
ob.dim[0].extent = ib.dimensions;
|
|
}
|
|
if (ib.dimensions == 0) {
|
|
return false;
|
|
}
|
|
return true;
|
|
}
|
|
};
|
|
|
|
REGISTER_SHAPE(ShapeSizeComputer, OpType_Shape);
|
|
} // namespace MNN
|