Mathis/CUDANet
1
0
Fork 0
mirror of https://github.com/lordmathis/CUDANet.git synced 2025-11-05 17:34:21 +00:00
Code Issues Packages Projects Releases Wiki Activity

Rename dim2d to shape2d

Browse Source
This commit is contained in:
Matúš Námešný
2024-05-27 21:14:51 +02:00
parent 07d505a0e5
commit df47a31f36
22 changed files with 120 additions and 120 deletions
Download Patch File Download Diff File Expand all files Collapse all files

20
include/layers/avg_pooling.cuh
View File

@@ -9,11 +9,11 @@ namespace CUDANet::Layers {
class AvgPooling2d : public SequentialLayer, public TwoDLayer {
public:
AvgPooling2d(
dim2d inputSize,
shape2d inputSize,
int nChannels,
dim2d poolingSize,
dim2d stride,
dim2d padding,
shape2d poolingSize,
shape2d stride,
shape2d padding,
ActivationType activationType
);
~AvgPooling2d();
@@ -34,16 +34,16 @@ class AvgPooling2d : public SequentialLayer, public TwoDLayer {
*/
int getInputSize();
dim2d getOutputDims();
shape2d getOutputDims();
private:
dim2d inputSize;
shape2d inputSize;
int nChannels;
dim2d poolingSize;
dim2d stride;
dim2d padding;
shape2d poolingSize;
shape2d stride;
shape2d padding;
dim2d outputSize;
shape2d outputSize;
float* d_output;

6
include/layers/batch_norm.cuh
View File

@@ -10,7 +10,7 @@ namespace CUDANet::Layers {
class BatchNorm2d : public WeightedLayer, public TwoDLayer {
public:
BatchNorm2d(dim2d inputSize, int inputChannels, float epsilon, ActivationType activationType);
BatchNorm2d(shape2d inputSize, int inputChannels, float epsilon, ActivationType activationType);
~BatchNorm2d();
@@ -64,11 +64,11 @@ class BatchNorm2d : public WeightedLayer, public TwoDLayer {
*/
int getInputSize();
dim2d getOutputDims();
shape2d getOutputDims();
private:
dim2d inputSize;
shape2d inputSize;
int inputChannels;
int gridSize;

22
include/layers/conv2d.cuh
View File

@@ -28,12 +28,12 @@ class Conv2d : public WeightedLayer, public TwoDLayer {
* 'SOFTMAX' or 'NONE')
*/
Conv2d(
dim2d inputSize,
shape2d inputSize,
int inputChannels,
dim2d kernelSize,
dim2d stride,
shape2d kernelSize,
shape2d stride,
int numFilters,
dim2d paddingSize,
shape2d paddingSize,
ActivationType activationType
);
@@ -98,24 +98,24 @@ class Conv2d : public WeightedLayer, public TwoDLayer {
*
* @return int
*/
dim2d getPaddingSize() {
shape2d getPaddingSize() {
return paddingSize;
}
dim2d getOutputDims();
shape2d getOutputDims();
private:
// Inputs
dim2d inputSize;
shape2d inputSize;
int inputChannels;
// Outputs
dim2d outputSize;
shape2d outputSize;
// Kernel
dim2d kernelSize;
dim2d stride;
dim2d paddingSize;
shape2d kernelSize;
shape2d stride;
shape2d paddingSize;
int numFilters;
// Kernels

4
include/layers/layer.cuh
View File

@@ -7,7 +7,7 @@
#define CUDANET_SAME_PADDING(inputSize, kernelSize, stride) \
((stride - 1) * inputSize - stride + kernelSize) / 2;
typedef std::pair<int, int> dim2d;
typedef std::pair<int, int> shape2d;
namespace CUDANet::Layers {
@@ -15,7 +15,7 @@ namespace CUDANet::Layers {
class TwoDLayer {
public:
virtual dim2d getOutputDims() = 0;
virtual shape2d getOutputDims() = 0;
};

20
include/layers/max_pooling.cuh
View File

@@ -9,11 +9,11 @@ namespace CUDANet::Layers {
class MaxPooling2d : public SequentialLayer, public TwoDLayer {
public:
MaxPooling2d(
dim2d inputSize,
shape2d inputSize,
int nChannels,
dim2d poolingSize,
dim2d stride,
dim2d padding,
shape2d poolingSize,
shape2d stride,
shape2d padding,
ActivationType activationType
);
~MaxPooling2d();
@@ -34,16 +34,16 @@ class MaxPooling2d : public SequentialLayer, public TwoDLayer {
*/
int getInputSize();
dim2d getOutputDims();
shape2d getOutputDims();
private:
dim2d inputSize;
shape2d inputSize;
int nChannels;
dim2d poolingSize;
dim2d stride;
dim2d padding;
shape2d poolingSize;
shape2d stride;
shape2d padding;
dim2d outputSize;
shape2d outputSize;
float* d_output;