MNN/source/shape/ShapeBinaryOp.cpp

73 lines
2.3 KiB
C++

//
// ShapeBinaryOp.cpp
// MNN
//
// Created by MNN on 2019/01/10.
// Copyright © 2018, Alibaba Group Holding Limited
//
#include "shape/SizeComputer.hpp"
#include "core/Macro.h"
#include <vector>
namespace MNN {
class BinaryOpComputer : public SizeComputer {
public:
static bool outputBool(int operation) {
if (operation == BinaryOpOperation_GREATER_EQUAL) {
return true;
}
if (operation == BinaryOpOperation_GREATER) {
return true;
}
if (operation == BinaryOpOperation_LESS) {
return true;
}
if (operation == BinaryOpOperation_LESS_EQUAL) {
return true;
}
if (operation == BinaryOpOperation_EQUAL) {
return true;
}
if (operation == BinaryOpOperation_NOTEQUAL) {
return true;
}
return false;
}
virtual bool onComputeSize(const Op* op, const std::vector<Tensor*>& inputs,
const std::vector<Tensor*>& outputs) const override {
MNN_ASSERT(2 == inputs.size());
MNN_ASSERT(1 == outputs.size());
// set output type & format
auto input0 = inputs[0], input1 = inputs[1], output = outputs[0];
auto &buffer = output->buffer();
const auto opType = op->main_as_BinaryOp()->opType();
if (outputBool(opType)) {
buffer.type = halide_type_of<int32_t>();
} else {
buffer.type = input0->getType();
}
if (input0->getType().code != input1->getType().code) {
#ifdef DEBUG
MNN_PRINT("Error for binary op: input0's type != input1's type, %d != %d, optype:%d, ", input0->getType().code, input1->getType().code, opType);
if (nullptr != op->name()) {
MNN_PRINT("op name: %s", op->name()->c_str());
}
MNN_PRINT("\n");
#endif
return false;
}
if (input0->dimensions() < input1->dimensions()) {
auto temp = input0;
input0 = input1;
input1 = temp;
}
TensorUtils::getDescribe(output)->dimensionFormat = TensorUtils::getDescribe(input0)->dimensionFormat;
return SizeComputer::computeBroadCastDims(inputs, outputs);
}
};
REGISTER_SHAPE(BinaryOpComputer, OpType_BinaryOp);
} // namespace MNN