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Implement inception module B

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This commit is contained in:
Matúš Námešný
2024-05-26 16:48:58 +02:00
parent 1e3b2f7d7b
commit d1fc45d9e0
1 changed files with 114 additions and 37 deletions
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137
examples/inception_v3/inception_v3.cpp
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@@ -44,6 +44,10 @@ class BasicConv2d : public CUDANet::Module {
return batchNorm->forward(d_output); return batchNorm->forward(d_output);
} }
dim2d getOutputDims() {
return batchNorm->getOutputDims();
}
private: private:
CUDANet::Layers::Conv2d *conv; CUDANet::Layers::Conv2d *conv;
CUDANet::Layers::BatchNorm2d *batchNorm; CUDANet::Layers::BatchNorm2d *batchNorm;
@@ -62,13 +66,15 @@ class InceptionA : public CUDANet::Module {
poolFeatures(poolFeatures) { poolFeatures(poolFeatures) {
// Branch 1x1 // Branch 1x1
branch1x1 = new BasicConv2d( branch1x1 = new BasicConv2d(
inputSize, inputChannels, 64, {1, 1}, {1, 1}, {0, 0}, prefix + ".branch1x1" inputSize, inputChannels, 64, {1, 1}, {1, 1}, {0, 0},
prefix + ".branch1x1"
); );
addLayer("", branch1x1); addLayer("", branch1x1);
// Branch 5x5 // Branch 5x5
branch5x5_1 = new BasicConv2d( branch5x5_1 = new BasicConv2d(
inputSize, inputChannels, 48, {1, 1}, {1, 1}, {0, 0}, prefix + ".branch5x5_1" inputSize, inputChannels, 48, {1, 1}, {1, 1}, {0, 0},
prefix + ".branch5x5_1"
); );
addLayer("", branch5x5_1); addLayer("", branch5x5_1);
branch5x5_2 = new BasicConv2d( branch5x5_2 = new BasicConv2d(
@@ -77,18 +83,21 @@ class InceptionA : public CUDANet::Module {
addLayer("", branch5x5_2); addLayer("", branch5x5_2);
// Branch 3x3 // Branch 3x3
branch3x3_1 = new BasicConv2d( branch3x3dbl_1 = new BasicConv2d(
inputSize, inputChannels, 64, {1, 1}, {1, 1}, {0, 0}, prefix + ".branch3x3_1" inputSize, inputChannels, 64, {1, 1}, {1, 1}, {0, 0},
prefix + ".branch3x3dbl_1"
); );
addLayer("", branch3x3_1); addLayer("", branch3x3dbl_1);
branch3x3_2 = new BasicConv2d( branch3x3dbl_2 = new BasicConv2d(
inputSize, 64, 96, {3, 3}, {1, 1}, {1, 1}, prefix + ".branch3x3_2" inputSize, 64, 96, {3, 3}, {1, 1}, {1, 1},
prefix + ".branch3x3dbl_2"
); );
addLayer("", branch3x3_2); addLayer("", branch3x3dbl_2);
branch3x3_3 = new BasicConv2d( branch3x3dbl_3 = new BasicConv2d(
inputSize, 96, 96, {3, 3}, {1, 1}, {1, 1}, prefix + ".branch3x3_3" inputSize, 96, 96, {3, 3}, {1, 1}, {1, 1},
prefix + ".branch3x3dbl_3"
); );
addLayer("", branch3x3_3); addLayer("", branch3x3dbl_3);
// Branch Pool // Branch Pool
branchPool_1 = new CUDANet::Layers::AvgPooling2d( branchPool_1 = new CUDANet::Layers::AvgPooling2d(
@@ -97,8 +106,8 @@ class InceptionA : public CUDANet::Module {
); );
addLayer("", branchPool_1); addLayer("", branchPool_1);
branchPool_2 = new BasicConv2d( branchPool_2 = new BasicConv2d(
branchPool_1->getOutputDims(), inputChannels, poolFeatures, {1, 1}, {1, 1}, {0, 0}, branchPool_1->getOutputDims(), inputChannels, poolFeatures, {1, 1},
prefix + ".branchPool" {1, 1}, {0, 0}, prefix + ".branchPool"
); );
addLayer("", branchPool_2); addLayer("", branchPool_2);
@@ -107,7 +116,7 @@ class InceptionA : public CUDANet::Module {
branch1x1->getOutputSize(), branch5x5_2->getOutputSize() branch1x1->getOutputSize(), branch5x5_2->getOutputSize()
); );
concat_2 = new CUDANet::Layers::Concat( concat_2 = new CUDANet::Layers::Concat(
concat_1->getOutputSize(), branch3x3_3->getOutputSize() concat_1->getOutputSize(), branch3x3dbl_3->getOutputSize()
); );
concat_3 = new CUDANet::Layers::Concat( concat_3 = new CUDANet::Layers::Concat(
concat_2->getOutputSize(), branchPool_2->getOutputSize() concat_2->getOutputSize(), branchPool_2->getOutputSize()
@@ -120,9 +129,9 @@ class InceptionA : public CUDANet::Module {
float *d_branch5x5_out = branch5x5_1->forward(d_input); float *d_branch5x5_out = branch5x5_1->forward(d_input);
d_branch5x5_out = branch5x5_2->forward(d_branch5x5_out); d_branch5x5_out = branch5x5_2->forward(d_branch5x5_out);
float *d_branch3x3_out = branch3x3_1->forward(d_input); float *d_branch3x3_out = branch3x3dbl_1->forward(d_input);
d_branch3x3_out = branch3x3_2->forward(d_branch3x3_out); d_branch3x3_out = branch3x3dbl_2->forward(d_branch3x3_out);
d_branch3x3_out = branch3x3_3->forward(d_branch3x3_out); d_branch3x3_out = branch3x3dbl_3->forward(d_branch3x3_out);
float *d_branchPool_out = branchPool_1->forward(d_input); float *d_branchPool_out = branchPool_1->forward(d_input);
d_branchPool_out = branchPool_2->forward(d_branchPool_out); d_branchPool_out = branchPool_2->forward(d_branchPool_out);
@@ -139,14 +148,17 @@ class InceptionA : public CUDANet::Module {
int inputChannels; int inputChannels;
int poolFeatures; int poolFeatures;
CUDANet::Module *branch1x1; BasicConv2d *branch1x1;
CUDANet::Module *branch5x5_1;
CUDANet::Module *branch5x5_2; BasicConv2d *branch5x5_1;
CUDANet::Module *branch3x3_1; BasicConv2d *branch5x5_2;
CUDANet::Module *branch3x3_2;
CUDANet::Module *branch3x3_3; BasicConv2d *branch3x3dbl_1;
BasicConv2d *branch3x3dbl_2;
BasicConv2d *branch3x3dbl_3;
CUDANet::Layers::AvgPooling2d *branchPool_1; CUDANet::Layers::AvgPooling2d *branchPool_1;
CUDANet::Module *branchPool_2; BasicConv2d *branchPool_2;
CUDANet::Layers::Concat *concat_1; CUDANet::Layers::Concat *concat_1;
CUDANet::Layers::Concat *concat_2; CUDANet::Layers::Concat *concat_2;
@@ -155,12 +167,77 @@ class InceptionA : public CUDANet::Module {
class InceptionB : public CUDANet::Module { class InceptionB : public CUDANet::Module {
public: public:
InceptionB(const int inputSize, const int inputChannels) InceptionB(
const dim2d inputSize,
const int inputChannels,
const std::string &prefix
)
: inputSize(inputSize), inputChannels(inputChannels) { : inputSize(inputSize), inputChannels(inputChannels) {
// Branch 1x1 // Branch 3x3
branch1x1 = new BasicConv2d( branch3x3 = new BasicConv2d(
inputSize, inputChannels, 128, 1, 1, 0, "branch1x1" inputSize, inputChannels, 384, {3, 3}, {2, 2}, {0, 0}, "branch1x1"
);
addLayer("", branch3x3);
// Branch 3x3dbl
branch3x3dbl_1 = new BasicConv2d(
inputSize, inputChannels, 64, {1, 1}, {1, 1}, {0, 0},
"branch3x3dbl_1"
);
addLayer("", branch3x3dbl_1);
branch3x3dbl_2 = new BasicConv2d(
branch3x3dbl_1->getOutputDims(), 96, 96, {3, 3}, {1, 1}, {1, 1},
"branch3x3dbl_2"
);
addLayer("", branch3x3dbl_2);
branch3x3dbl_3 = new BasicConv2d(
branch3x3dbl_2->getOutputDims(), 96, 96, {3, 3}, {2, 2}, {1, 1},
"branch3x3dbl_3"
);
addLayer("", branch3x3dbl_3);
branchPool = new CUDANet::Layers::MaxPooling2d(
inputSize, inputChannels, {3, 3}, {2, 2},
CUDANet::Layers::ActivationType::NONE
);
addLayer(prefix + ".branchPool", branchPool);
concat_1 = new CUDANet::Layers::Concat(
branch3x3->getOutputSize(), branch3x3dbl_3->getOutputSize()
);
concat_2 = new CUDANet::Layers::Concat(
concat_1->getOutputSize(), branchPool->getOutputSize()
); );
addLayer("", branch1x1);
} }
}
float *forward(const float *d_input) {
float *d_branch3x3_out = branch3x3->forward(d_input);
float *d_branch3x3dbl_out = branch3x3dbl_1->forward(d_input);
d_branch3x3dbl_out = branch3x3dbl_2->forward(d_branch3x3dbl_out);
d_branch3x3dbl_out = branch3x3dbl_3->forward(d_branch3x3dbl_out);
float *d_branchPool_out = branchPool->forward(d_input);
float *d_output =
concat_1->forward(d_branch3x3_out, d_branch3x3dbl_out);
d_output = concat_2->forward(d_output, d_branchPool_out);
return d_output;
}
private:
dim2d inputSize;
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;
};