Fixing the Cuda compilation

Author: Cydral

dlib/cuda/cublas_dlibapi.cpp

@@ -102,10 +102,10 @@ namespace dlib
             bool trans_lhs,
             const tensor& rhs,
             bool trans_rhs,
-            tt::operation_mode mode
+            operation_mode mode
         )
         {
-            if (mode == tt::operation_mode::CHANNEL_WISE)
+            if (mode == operation_mode::CHANNEL_WISE)
             {
                 // Recall that BLAS uses column major order so to deal with that we flip the
                 // order of the lhs and rhs arguments.
@@ -154,7 +154,7 @@ namespace dlib
                     &beta,
                     dest.device(), dest_nc));
             }
-            else if (mode == tt::operation_mode::PLANE_WISE)
+            else if (mode == operation_mode::PLANE_WISE)
             {
                 const auto transa = trans_lhs ? CUBLAS_OP_T : CUBLAS_OP_N;
                 const auto transb = trans_rhs ? CUBLAS_OP_T : CUBLAS_OP_N;

dlib/cuda/cublas_dlibapi.h

@@ -9,9 +9,9 @@
 #include "cuda_errors.h"
 
 namespace dlib
-{
+{    
     namespace cuda 
-    {
+    {        
 
     // -----------------------------------------------------------------------------------
 
@@ -23,7 +23,7 @@ namespace dlib
             bool trans_lhs,
             const tensor& rhs,
             bool trans_rhs,
-            tt::operation_mode mode = tt::operation_mode::CHANNEL_WISE
+            operation_mode mode = operation_mode::CHANNEL_WISE
         );
     /*!
         requires

dlib/cuda/tensor.h

@@ -15,6 +15,17 @@
 namespace dlib
 {
 
+// ----------------------------------------------------------------------------------------
+
+    /*!
+        This enum is used to determine the mode of operation for certain functions
+        (such as gemm and softmax) in Dlib. It specifies whether the calculation
+        should be performed based on the matrix field in nr()xnc() or if the matrix
+        should be considered in num_samples()xk(). This helps in organizing tensor
+        computations more efficiently according to the required dimensions.
+    !*/
+    enum class operation_mode { CHANNEL_WISE = 0, PLANE_WISE = 1 };
+
 // ----------------------------------------------------------------------------------------
 
     class tensor;

dlib/cuda/tensor_tools.cpp

@@ -209,13 +209,13 @@ namespace dlib { namespace tt
         bool trans_lhs,
         const tensor& rhs,
         bool trans_rhs,
-        tt::operation_mode mode
+        operation_mode mode
     )
     {
 #ifdef DLIB_USE_CUDA
         cuda::gemm(beta, dest, alpha, lhs, trans_lhs, rhs, trans_rhs, mode);
 #else
-        if (mode == tt::operation_mode::CHANNEL_WISE)
+        if (mode == operation_mode::CHANNEL_WISE)
         {
             if (beta != 0)
             {
@@ -240,7 +240,7 @@ namespace dlib { namespace tt
                     dest = alpha * mat(lhs) * mat(rhs);
             }
         }
-        else if (mode == tt::operation_mode::PLANE_WISE)
+        else if (mode == operation_mode::PLANE_WISE)
         {
             auto is_matrix = [](const auto& tensor) {
                 return ((tensor.num_samples() * tensor.k() == 1 && tensor.nr() * tensor.nc() > 1) ||

dlib/cuda/tensor_tools.h

@@ -25,17 +25,6 @@ namespace dlib
 namespace dlib { namespace tt
 {
 
-// ----------------------------------------------------------------------------------------
-    
-    /*!
-        This enum is used to determine the mode of operation for certain functions 
-        (such as gemm and softmax) in Dlib. It specifies whether the calculation 
-        should be performed based on the matrix field in nr()xnc() or if the matrix 
-        should be considered in num_samples()xk(). This helps in organizing tensor 
-        computations more efficiently according to the required dimensions.
-    !*/
-    enum class operation_mode { CHANNEL_WISE = 0, PLANE_WISE = 1 };
-
 // ----------------------------------------------------------------------------------------
 
     void inverse_norms (
@@ -177,7 +166,7 @@ namespace dlib { namespace tt
         bool trans_lhs,
         const tensor& rhs,
         bool trans_rhs,
-        tt::operation_mode mode = tt::operation_mode::CHANNEL_WISE
+        operation_mode mode = operation_mode::CHANNEL_WISE
     );
     /*!
         requires

dlib/dnn/layers.h

@@ -2809,7 +2809,7 @@ namespace dlib
             auto& t2 = layer<tag>(sub).get_output();
             output.set_size(t1.num_samples(), t1.k(), t1.nr(), t2.nc());
 
-            tt::gemm(0, output, 1, t1, false, t2, false, tt::operation_mode::PLANE_WISE);
+            tt::gemm(0, output, 1, t1, false, t2, false, operation_mode::PLANE_WISE);
         }
 
         template <typename SUBNET>
@@ -2820,8 +2820,8 @@ namespace dlib
             auto& prev = sub.get_gradient_input();
             auto& prev_tag = layer<tag>(sub).get_gradient_input();            
 
-            tt::gemm(1, prev, 1, gradient_input, false, t2, true, tt::operation_mode::PLANE_WISE);
-            tt::gemm(1, prev_tag, 1, t1, true, gradient_input, false, tt::operation_mode::PLANE_WISE);
+            tt::gemm(1, prev, 1, gradient_input, false, t2, true, operation_mode::PLANE_WISE);
+            tt::gemm(1, prev_tag, 1, t1, true, gradient_input, false, operation_mode::PLANE_WISE);
         }
 
         const tensor& get_layer_params() const { return params; }