[ GPU/OpenCL ] change reshape_cl to inherit LayerImplCl

- This commit updates reshape_cl.cpp/.h to inherit LayerImplCl.
- This commit implements registerClKernels(), which is called in
context_cl.cpp

Self evaluation:

Build test: [X]Passed [ ]Failed [ ]Skipped
Run test: [X]Passed [ ]Failed [ ]Skipped

Signed-off-by: Eunju Yang <[email protected]>

nntrainer/cl_context.cpp

@@ -32,10 +32,11 @@ std::once_flag global_cl_context_init_flag;
 
 static void add_default_object(ClContext &cc) {
 
-  FullyConnectedLayerCl::registerClKernels();
-  cc.registerFactory(nntrainer::createLayer<FullyConnectedLayerCl>,
-                     FullyConnectedLayerCl::type,
-                     ml::train::LayerType::LAYER_FC);
+  if (FullyConnectedLayerCl::registerClKernels()) {
+    cc.registerFactory(nntrainer::createLayer<FullyConnectedLayerCl>,
+                       FullyConnectedLayerCl::type,
+                       ml::train::LayerType::LAYER_FC);
+  }
 
   // cc.registerFactory(nntrainer::createLayer<AdditionLayerCL>,
   //                    AdditionLayerCL::type,
@@ -45,16 +46,19 @@ static void add_default_object(ClContext &cc) {
   // SwiGLULayerCl::type,
   //  ml::train::LayerType::LAYER_SWIGLU);
 
-  ReshapeLayerCl::registerClKernels();
-  cc.registerFactory(nntrainer::createLayer<ReshapeLayerCl>,
-                     ReshapeLayerCl::type, ml::train::LayerType::LAYER_RESHAPE);
+  if (ReshapeLayerCl::registerClKernels()) {
+    cc.registerFactory(nntrainer::createLayer<ReshapeLayerCl>,
+                       ReshapeLayerCl::type,
+                       ml::train::LayerType::LAYER_RESHAPE);
+  }
 
   // cc.registerFactory(nntrainer::createLayer<RMSNormLayerCl>,
   //  RMSNormLayerCl::type, ml::train::LayerType::LAYER_RMSNORM);
 
-  ConcatLayerCl::registerClKernels();
-  cc.registerFactory(nntrainer::createLayer<ConcatLayerCl>, ConcatLayerCl::type,
-                     ml::train::LayerType::LAYER_CONCAT);
+  if (ConcatLayerCl::registerClKernels()) {
+    cc.registerFactory(nntrainer::createLayer<ConcatLayerCl>,
+                       ConcatLayerCl::type, ml::train::LayerType::LAYER_CONCAT);
+  }
 }
 
 static void registerer(ClContext &cc) noexcept {

nntrainer/layers/cl_layers/reshape_cl.cpp

@@ -49,6 +49,24 @@ namespace nntrainer {
 
 static constexpr size_t SINGLE_INOUT_IDX = 0;
 
+bool ReshapeLayerCl::registerClKernels() {
+
+  ClContext::SharedPtrClKernel kernel_copy_ptr = nullptr;
+
+  kernel_copy_ptr = cl_context_ref.registerClKernel(copy_cl_kernel_, "copy_cl");
+  NNTR_THROW_IF(!kernel_copy_ptr, std::runtime_error)
+    << "OpenCL Error: Fail to register copy_cl kernel";
+  layer_kernel_ptrs.emplace_back(kernel_copy_ptr);
+
+  kernel_copy_ptr =
+    cl_context_ref.registerClKernel(copy_cl_kernel_fp16_, "copy_cl_fp16");
+  NNTR_THROW_IF(!kernel_copy_ptr, std::runtime_error)
+    << "OpenCL Error: Fail to register copy_cl_fp16 kernel";
+  layer_kernel_ptrs.emplace_back(kernel_copy_ptr);
+
+  return true;
+};
+
 void ReshapeLayerCl::finalize(InitLayerContext &context) {
   NNTR_THROW_IF(context.getNumInputs() != 1, std::invalid_argument)
     << "Reshape only supports 1 input for now";
@@ -98,9 +116,6 @@ void ReshapeLayerCl::incremental_forwarding(RunLayerContext &context,
   }
 }
 
-opencl::Kernel ReshapeLayerCl::kernel_copy;
-opencl::Kernel ReshapeLayerCl::kernel_copy_fp16;
-
 void ReshapeLayerCl::ReshapeProcess(Tensor const &input, Tensor &output) {
 
   unsigned int input_batch_size, input_height, input_width, input_channels;
@@ -136,11 +151,7 @@ void ReshapeLayerCl::copy_cl_fp16(const __fp16 *input, __fp16 *res,
   bool result = false;
 
   do {
-    ClContext::SharedPtrClKernel kernel_copy_ptr =
-      cl_context_ref.registerClKernel(copy_cl_kernel_fp16_, "copy_cl_fp16");
-    if (!kernel_copy_ptr) {
-      break;
-    }
+    const auto &kernel_copy_ptr = layer_kernel_ptrs[Kernels::COPY_CL];
 
     size_t dim_size = sizeof(__fp16) * input_batch_size * input_height *
                       input_width * input_channels;
@@ -219,11 +230,7 @@ void ReshapeLayerCl::copy_cl(const float *input, float *res,
   bool result = false;
 
   do {
-    ClContext::SharedPtrClKernel kernel_copy_ptr =
-      cl_context_ref.registerClKernel(copy_cl_kernel_, "copy_cl");
-    if (!kernel_copy_ptr) {
-      break;
-    }
+    const auto &kernel_copy_ptr = layer_kernel_ptrs[Kernels::COPY_CL];
 
     size_t dim_size = sizeof(float) * input_batch_size * input_height *
                       input_width * input_channels;

nntrainer/layers/cl_layers/reshape_cl.h

@@ -18,6 +18,7 @@
 #include <cl_context.h>
 #include <common_properties.h>
 #include <layer_devel.h>
+#include <layer_impl_cl.h>
 #include <opencl_buffer.h>
 #include <opencl_kernel.h>
 
@@ -26,10 +27,7 @@ namespace nntrainer {
  * @class   Reshape Layer
  * @brief   Reshape Layer
  */
-class ReshapeLayerCl : public Layer {
-
-private:
-  inline static ClContext cl_context_ref;
+class ReshapeLayerCl : public LayerImplCl {
 
 public:
   /**
@@ -105,16 +103,18 @@ class ReshapeLayerCl : public Layer {
 
   inline static const std::string type = "reshape";
 
-  static opencl::Kernel kernel_copy;
-  static opencl::Kernel kernel_copy_fp16;
-
   /**
    * @brief Process data and dimensions for reshape operation
    * @param[in] input Tensor
    * @param[in] result Tensor
    */
   void ReshapeProcess(Tensor const &input, Tensor &result);
 
+  /**
+   * @brief registerClKernels
+   */
+  static bool registerClKernels();
+
   /**
    * @brief     copy computation
    * @param[in] input float * for Input Tensor
@@ -145,9 +145,13 @@ class ReshapeLayerCl : public Layer {
                     unsigned int input_height, unsigned int input_width);
 #endif
 
-protected:
+private:
   std::tuple<props::TargetShape>
     reshape_props; /**< reshape properties : target_shape after reshape */
+
+  inline static std::vector<ClContext::SharedPtrClKernel> layer_kernel_ptrs;
+
+  enum Kernels { COPY_CL, COPY_CL_FP16 };
 };
 
 } // namespace nntrainer

test/jni/Android.mk

@@ -443,13 +443,11 @@ LOCAL_SRC_FILES := \
 	 ../unittest/layers/unittest_layers.cpp \
 	 ../unittest/layers/unittest_layers_impl.cpp \
 	 ../unittest/layers/unittest_layers_concat_cl.cpp \
-	 ../unittest/layers/unittest_layers_swiglu_cl.cpp \
 	 ../unittest/layers/unittest_layers_fully_connected_cl.cpp \
 	 ../unittest/layers/unittest_layers_input.cpp \
 	 ../unittest/layers/unittest_layers_loss.cpp \
 	 ../unittest/layers/unittest_layers_reshape_cl.cpp \
 	 ../unittest/layers/unittest_layers_fully_connected.cpp \
-     ../unittest/layers/unittest_layers_rmsnorm_cl.cpp \
 	 ../unittest/layers/unittest_layers_batch_normalization.cpp \
 	 ../unittest/layers/unittest_layers_layer_normalization.cpp \
 	 ../unittest/layers/unittest_layers_convolution2d.cpp \
@@ -458,7 +456,6 @@ LOCAL_SRC_FILES := \
 	 ../unittest/layers/unittest_layers_flatten.cpp \
 	 ../unittest/layers/unittest_layers_activation.cpp \
 	 ../unittest/layers/unittest_layers_addition.cpp \
-	 ../unittest/layers/unittest_layers_addition_cl.cpp \
 	 ../unittest/layers/unittest_layers_multiout.cpp \
 	 ../unittest/layers/unittest_layers_rnn.cpp \
 	 ../unittest/layers/unittest_layers_rnncell.cpp \