mirror of https://github.com/alibaba/MNN.git
71 lines
2.6 KiB
C++
71 lines
2.6 KiB
C++
//
|
|
// ShapePool3D.cpp
|
|
// MNN
|
|
//
|
|
// Created by MNN on 2019/01/10.
|
|
// Copyright © 2018, Alibaba Group Holding Limited
|
|
//
|
|
|
|
#include <math.h>
|
|
|
|
#include "core/Macro.h"
|
|
#include "core/SizeComputer.hpp"
|
|
|
|
namespace MNN {
|
|
class Pool3DSizeComputer : public SizeComputer {
|
|
public:
|
|
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 input = inputs[0];
|
|
auto output = outputs[0];
|
|
|
|
for (unsigned int i = 0; i < input->buffer().dimensions; ++i) {
|
|
MNN_ASSERT(input->buffer().dim[i].extent > 0);
|
|
}
|
|
output->buffer().dimensions = input->buffer().dimensions;
|
|
output->buffer().dim[0] = input->buffer().dim[0];
|
|
output->buffer().dim[1] = input->buffer().dim[1];
|
|
|
|
auto layer = op->main_as_Pool3D();
|
|
for (unsigned int i = 0; i < input->dimensions() - 2; ++i) {
|
|
int inputLength = input->buffer().dim[i + 2].extent, outputLength = 0;
|
|
const int kernel = (*layer->kernels())[i], stride = (*layer->strides())[i];
|
|
|
|
if (layer->padType() == PoolPadType_CAFFE) {
|
|
int pad = (*layer->pads())[i];
|
|
outputLength = (inputLength + 2 * pad - kernel) / stride + 1;
|
|
} else if (layer->padType() == PoolPadType_SAME) {
|
|
outputLength = UP_DIV(inputLength, stride);
|
|
} else if (layer->padType() == PoolPadType_VALID) {
|
|
outputLength = (inputLength - kernel) / stride + 1;
|
|
} else {
|
|
MNN_ERROR("PoolPadType %d not support\n", layer->padType());
|
|
}
|
|
if (outputLength <= 0) {
|
|
return false;
|
|
}
|
|
output->buffer().dim[i + 2].extent = outputLength;
|
|
}
|
|
TensorUtils::getDescribe(outputs[0])->dimensionFormat = TensorUtils::getDescribe(inputs[0])->dimensionFormat;
|
|
output->buffer().type = input->buffer().type;
|
|
return true;
|
|
}
|
|
|
|
virtual float onComputeFlops(const MNN::Op* op, const std::vector<Tensor*>& inputs,
|
|
const std::vector<Tensor*>& outputs) const override {
|
|
auto size = (float)outputs[0]->elementSize() / 1024.0f / 1024.0f;
|
|
auto layer = op->main_as_Pool3D();
|
|
float flopsPerElement = 1;
|
|
for (auto kernel: *layer->kernels()) {
|
|
flopsPerElement *= kernel;
|
|
}
|
|
return size * flopsPerElement;
|
|
}
|
|
};
|
|
|
|
REGISTER_SHAPE(Pool3DSizeComputer, OpType_Pooling3D);
|
|
} // namespace MNN
|