Add toplevel CUDANet namespace

include/layers/conv2d.cuh

@@ -8,7 +8,7 @@
 #include "convolution.cuh"
 #include "ilayer.cuh"
 
-namespace Layers {
+namespace CUDANet::Layers {
 
 /**
  * @brief 2D convolutional layer
@@ -125,6 +125,6 @@ class Conv2d : public ILayer {
     void toCuda();
 };
 
-}  // namespace Layers
+}  // namespace CUDANet::Layers
 
 #endif  // CUDANET_CONV_LAYER_H

include/layers/dense.cuh

@@ -7,7 +7,7 @@
 
 #include "ilayer.cuh"
 
-namespace Layers {
+namespace CUDANet::Layers {
 
 /**
  * @brief Dense (fully connected) layer
@@ -53,8 +53,8 @@ class Dense : public ILayer {
     void setBiases(const float* biases);
 
   private:
-    int inputSize;
-    int outputSize;
+    unsigned int inputSize;
+    unsigned int outputSize;
 
     float* d_output;
 
@@ -67,8 +67,8 @@ class Dense : public ILayer {
     Layers::Activation activation;
 
     // Precompute kernel launch parameters
-    int forwardGridSize;
-    int biasGridSize;
+    unsigned int forwardGridSize;
+    unsigned int biasGridSize;
 
     /**
      * @brief Initialize the weights to zeros
@@ -89,6 +89,6 @@ class Dense : public ILayer {
     void toCuda();
 };
 
-}  // namespace Layers
+}  // namespace CUDANet::Layers
 
 #endif  // CUDANET_DENSE_LAYER_H

include/layers/ilayer.cuh

@@ -4,7 +4,7 @@
 
 #include <vector>
 
-namespace Layers {
+namespace CUDANet::Layers {
 
 /**
  * @brief Activation functions
@@ -88,6 +88,6 @@ class ILayer {
     Layers::Activation activation;
 };
 
-}  // namespace Layers
+}  // namespace CUDANet::Layers
 
 #endif  // CUDANET_I_LAYERH

include/layers/input.cuh

@@ -3,7 +3,7 @@
 
 #include <ilayer.cuh>
 
-namespace Layers {
+namespace CUDANet::Layers {
 
 /**
  * @brief Input layer, just copies the input to the device
@@ -45,6 +45,6 @@ class Input : public ILayer {
     float* d_output;
 };
 
-}  // namespace Layers
+}  // namespace CUDANet::Layers
 
 #endif  // CUDANET_INPUT_LAYER_H