Rename dim2d to shape2d

src/kernels/convolution.cu

@@ -9,13 +9,13 @@ __global__ void Kernels::convolution(
     const float* __restrict__ d_kernel,
     const float* __restrict__ d_bias,
     float* __restrict__ d_output,
-    const dim2d inputSize,
+    const shape2d inputSize,
     const int   nChannels,
-    const dim2d paddingSize,
-    const dim2d kernelSize,
-    const dim2d stride,
+    const shape2d paddingSize,
+    const shape2d kernelSize,
+    const shape2d stride,
     const int   nFilters,
-    const dim2d outputSize
+    const shape2d outputSize
 ) {
     int j = blockDim.x * blockIdx.x + threadIdx.x;
     int i = blockDim.y * blockIdx.y + threadIdx.y;

src/kernels/pooling.cu

@@ -7,12 +7,12 @@ using namespace CUDANet;
 __global__ void Kernels::max_pooling(
     const float* __restrict__ d_input,
     float* __restrict__ d_output,
-    const dim2d inputSize,
-    const dim2d outputSize,
+    const shape2d inputSize,
+    const shape2d outputSize,
     const int   nChannels,
-    const dim2d poolingSize,
-    const dim2d stride,
-    const dim2d padding
+    const shape2d poolingSize,
+    const shape2d stride,
+    const shape2d padding
 ) {
     int j = blockDim.x * blockIdx.x + threadIdx.x;
     int i = blockDim.y * blockIdx.y + threadIdx.y;
@@ -48,12 +48,12 @@ __global__ void Kernels::max_pooling(
 __global__ void Kernels::avg_pooling(
     const float* __restrict__ d_input,
     float* __restrict__ d_output,
-    const dim2d inputSize,
-    const dim2d outputSize,
+    const shape2d inputSize,
+    const shape2d outputSize,
     const int   nChannels,
-    const dim2d poolingSize,
-    const dim2d stride,
-    const dim2d padding
+    const shape2d poolingSize,
+    const shape2d stride,
+    const shape2d padding
 ) {
     int j = blockDim.x * blockIdx.x + threadIdx.x;
     int i = blockDim.y * blockIdx.y + threadIdx.y;

src/layers/avg_pooling.cu

@@ -5,11 +5,11 @@
 using namespace CUDANet::Layers;
 
 AvgPooling2d::AvgPooling2d(
-    dim2d          inputSize,
+    shape2d          inputSize,
     int            nChannels,
-    dim2d          poolingSize,
-    dim2d          stride,
-    dim2d          padding,
+    shape2d          poolingSize,
+    shape2d          stride,
+    shape2d          padding,
     ActivationType activationType
 )
     : inputSize(inputSize),
@@ -66,6 +66,6 @@ int AvgPooling2d::getInputSize() {
     return inputSize.first * inputSize.second * nChannels;
 }
 
-dim2d AvgPooling2d::getOutputDims() {
+shape2d AvgPooling2d::getOutputDims() {
     return outputSize;
 }

src/layers/batch_norm.cu

@@ -10,7 +10,7 @@
 using namespace CUDANet::Layers;
 
 BatchNorm2d::BatchNorm2d(
-    dim2d          inputSize,
+    shape2d          inputSize,
     int            inputChannels,
     float          epsilon,
     ActivationType activationType
@@ -128,7 +128,7 @@ int BatchNorm2d::getOutputSize() {
     return inputSize.first * inputSize.second * inputChannels;
 }
 
-dim2d BatchNorm2d::getOutputDims() {
+shape2d BatchNorm2d::getOutputDims() {
     return inputSize;
 }
 

src/layers/conv2d.cu

@@ -12,12 +12,12 @@
 using namespace CUDANet::Layers;
 
 Conv2d::Conv2d(
-    dim2d          inputSize,
+    shape2d          inputSize,
     int            inputChannels,
-    dim2d          kernelSize,
-    dim2d          stride,
+    shape2d          kernelSize,
+    shape2d          stride,
     int            numFilters,
-    dim2d          paddingSize,
+    shape2d          paddingSize,
     ActivationType activationType
 )
     : inputSize(inputSize),
@@ -139,6 +139,6 @@ int Conv2d::getInputSize() {
     return inputSize.first * inputSize.second * inputChannels;
 }
 
-dim2d Conv2d::getOutputDims() {
+shape2d Conv2d::getOutputDims() {
     return outputSize;
 }

src/layers/max_pooling.cu

@@ -5,11 +5,11 @@
 using namespace CUDANet::Layers;
 
 MaxPooling2d::MaxPooling2d(
-    dim2d          inputSize,
+    shape2d          inputSize,
     int            nChannels,
-    dim2d          poolingSize,
-    dim2d          stride,
-    dim2d          padding,
+    shape2d          poolingSize,
+    shape2d          stride,
+    shape2d          padding,
     ActivationType activationType
 )
     : inputSize(inputSize),
@@ -70,6 +70,6 @@ int MaxPooling2d::getInputSize() {
     return inputSize.first * inputSize.second * nChannels;
 }
 
-dim2d MaxPooling2d::getOutputDims() {
+shape2d MaxPooling2d::getOutputDims() {
     return outputSize;
 }

src/model/model.cpp

@@ -11,7 +11,7 @@
 
 using namespace CUDANet;
 
-Model::Model(const dim2d inputSize, const int inputChannels, const int outputSize)
+Model::Model(const shape2d inputSize, const int inputChannels, const int outputSize)
     : inputSize(inputSize),
       inputChannels(inputChannels),
       outputSize(outputSize),