mirror of https://github.com/alibaba/MNN.git
31 lines
921 B
C++
31 lines
921 B
C++
|
//
|
||
|
|
// ShapeHistogram.cpp
|
||
|
|
// MNN
|
||
|
|
//
|
||
|
|
// Created by MNN on 2022/07/26.
|
||
|
|
// Copyright © 2018, Alibaba Group Holding Limited
|
||
|
|
//
|
||
|
|
|
||
|
|
#include "shape/SizeComputer.hpp"
|
||
|
|
#include "core/Macro.h"
|
||
|
|
#include "math.h"
|
||
|
|
|
||
|
|
namespace MNN {
|
||
|
|
|
||
|
|
class ShapeHistogram : public SizeComputer {
|
||
|
|
virtual bool onComputeSize(const MNN::Op* op, const std::vector<Tensor*>& inputs,
|
||
|
|
const std::vector<Tensor*>& outputs) const override {
|
||
|
|
MNN_ASSERT(inputs.size() == 1 && outputs.size() == 1);
|
||
|
|
|
||
|
|
auto output = outputs[0];
|
||
|
|
output->buffer().dimensions = 1;
|
||
|
|
output->setLength(0, op->main_as_ArgMax()->outMaxVal());
|
||
|
|
output->buffer().type = halide_type_of<float>();
|
||
|
|
TensorUtils::getDescribe(output)->dimensionFormat = TensorUtils::getDescribe(inputs[0])->dimensionFormat;
|
||
|
|
return true;
|
||
|
|
}
|
||
|
|
};
|
||
|
|
|
||
|
|
REGISTER_SHAPE(ShapeHistogram, OpType_Histogram);
|
||
|
|
} // namespace MNN
|