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Split inception v3 source file

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Matúš Námešný
2024-05-30 18:41:33 +02:00
parent 8168f02f58
commit 229929a464
5 changed files with 1027 additions and 941 deletions
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244
examples/inception_v3/inception_v3.hpp Normal file
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#ifndef INCEPTION_V3_HPP
#define INCEPTION_V3_HPP
#include <cudanet.cuh>
class BasicConv2d : public CUDANet::Module {
public:
BasicConv2d(
const shape2d inputShape,
const int inputChannels,
const int outputChannels,
const shape2d kernelSize,
const shape2d stride,
const shape2d padding,
const std::string &prefix
);
~BasicConv2d();
float *forward(const float *d_input);
shape2d getOutputDims();
int getOutputChannels();
private:
int outputChannels;
CUDANet::Layers::Conv2d *conv;
CUDANet::Layers::BatchNorm2d *batchNorm;
};
class InceptionA : public CUDANet::Module {
public:
InceptionA(
const shape2d inputShape,
const int inputChannels,
const int poolFeatures,
const std::string &prefix
);
~InceptionA();
float *forward(const float *d_input);
shape2d getOutputDims();
int getOutputChannels();
private:
shape2d inputShape;
int inputChannels;
int poolFeatures;
BasicConv2d *branch1x1;
BasicConv2d *branch5x5_1;
BasicConv2d *branch5x5_2;
BasicConv2d *branch3x3dbl_1;
BasicConv2d *branch3x3dbl_2;
BasicConv2d *branch3x3dbl_3;
CUDANet::Layers::AvgPooling2d *branchPool_1;
BasicConv2d *branchPool_2;
CUDANet::Layers::Concat *concat_1;
CUDANet::Layers::Concat *concat_2;
CUDANet::Layers::Concat *concat_3;
};
class InceptionB : public CUDANet::Module {
public:
InceptionB(
const shape2d inputShape,
const int inputChannels,
const std::string &prefix
);
~InceptionB();
float *forward(const float *d_input);
shape2d getOutputDims();
int getOutputChannels();
private:
shape2d inputShape;
int inputChannels;
BasicConv2d *branch3x3;
BasicConv2d *branch3x3dbl_1;
BasicConv2d *branch3x3dbl_2;
BasicConv2d *branch3x3dbl_3;
CUDANet::Layers::MaxPooling2d *branchPool;
CUDANet::Layers::Concat *concat_1;
CUDANet::Layers::Concat *concat_2;
};
class InceptionC : public CUDANet::Module {
public:
InceptionC(
const shape2d inputShape,
const int inputChannels,
const int nChannels_7x7,
const std::string &prefix
);
~InceptionC();
float *forward(const float *d_input);
shape2d getOutputDims();
int getOutputChannels();
private:
shape2d inputShape;
int inputChannels;
BasicConv2d *branch1x1;
BasicConv2d *branch7x7_1;
BasicConv2d *branch7x7_2;
BasicConv2d *branch7x7_3;
BasicConv2d *branch7x7dbl_1;
BasicConv2d *branch7x7dbl_2;
BasicConv2d *branch7x7dbl_3;
BasicConv2d *branch7x7dbl_4;
BasicConv2d *branch7x7dbl_5;
CUDANet::Layers::AvgPooling2d *branchPool_1;
BasicConv2d *branchPool_2;
CUDANet::Layers::Concat *concat_1;
CUDANet::Layers::Concat *concat_2;
CUDANet::Layers::Concat *concat_3;
};
class InceptionD : public CUDANet::Module {
public:
InceptionD(
const shape2d inputShape,
const int inputChannels,
const std::string &prefix
);
~InceptionD();
float *forward(const float *d_input);
shape2d getOutputDims();
int getOutputChannels();
private:
shape2d inputShape;
int inputChannels;
BasicConv2d *branch3x3_1;
BasicConv2d *branch3x3_2;
BasicConv2d *branch7x7x3_1;
BasicConv2d *branch7x7x3_2;
BasicConv2d *branch7x7x3_3;
BasicConv2d *branch7x7x3_4;
CUDANet::Layers::MaxPooling2d *branchPool;
CUDANet::Layers::Concat *concat_1;
CUDANet::Layers::Concat *concat_2;
};
class InceptionE : public CUDANet::Module {
public:
InceptionE(
const shape2d inputShape,
const int inputChannels,
const std::string &prefix
);
~InceptionE();
float *forward(const float *d_input);
shape2d getOutputDims();
int getOutputChannels();
private:
shape2d inputShape;
int inputChannels;
BasicConv2d *branch1x1;
BasicConv2d *branch3x3_1;
BasicConv2d *branch3x3_2a;
BasicConv2d *branch3x3_2b;
CUDANet::Layers::Concat *branch_3x3_2_concat;
BasicConv2d *branch3x3dbl_1;
BasicConv2d *branch3x3dbl_2;
BasicConv2d *branch3x3dbl_3a;
BasicConv2d *branch3x3dbl_3b;
CUDANet::Layers::Concat *branch_3x3dbl_3_concat;
CUDANet::Layers::AvgPooling2d *branchPool_1;
BasicConv2d *branchPool_2;
CUDANet::Layers::Concat *concat_1;
CUDANet::Layers::Concat *concat_2;
CUDANet::Layers::Concat *concat_3;
};
class InceptionV3 : public CUDANet::Model {
public:
InceptionV3(
const shape2d inputShape,
const int inputChannels,
const int outputSize
);
~InceptionV3();
float *predict(const float *input);
private:
BasicConv2d *conv2d_1a_3x3;
BasicConv2d *conv2d_2a_3x3;
BasicConv2d *conv2d_2b_3x3;
CUDANet::Layers::MaxPooling2d *maxpool1;
BasicConv2d *conv2d_3b_1x1;
BasicConv2d *conv2d_4a_3x3;
CUDANet::Layers::MaxPooling2d *maxpool2;
InceptionA *Mixed_5b;
InceptionA *Mixed_5c;
InceptionA *Mixed_5d;
InceptionB *Mixed_6a;
InceptionC *Mixed_6b;
InceptionC *Mixed_6c;
InceptionC *Mixed_6d;
InceptionC *Mixed_6e;
InceptionD *Mixed_7a;
InceptionE *Mixed_7b;
InceptionE *Mixed_7c;
CUDANet::Layers::AdaptiveAvgPooling2d *avgpool;
CUDANet::Layers::Dense *fc;
};
#endif