COMPMID-3391: Implement Async interfaces

Change-Id: I8168cea5056ff48a0253ebb8c88ea549a3ea69a2
Signed-off-by: Michalis Spyrou <michalis.spyrou@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/3335
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>

1 files changed, 12 insertions, 15 deletions

diff --git a/src/runtime/NEON/functions/NESoftmaxLayer.cpp b/src/runtime/NEON/functions/NESoftmaxLayer.cpp
index 5509edec87..5cd6a550af 100644
--- a/src/runtime/NEON/functions/NESoftmaxLayer.cpp
+++ b/src/runtime/NEON/functions/NESoftmaxLayer.cpp
@@ -32,8 +32,8 @@ namespace arm_compute
 {
 template <bool IS_LOG>
 NESoftmaxLayerGeneric<IS_LOG>::NESoftmaxLayerGeneric(std::shared_ptr<IMemoryManager> memory_manager)
-    : _memory_group(std::move(memory_manager)), _max_kernel(), _softmax_kernel(), _flat_or_reshape_kernel_ptr(nullptr), _fill_border_kernel(), _reshape_kernel(), _max(), _tmp(), _input_flattened(),
-      _output_flattened(), _needs_flattening(false)
+    : _memory_group(std::move(memory_manager)), _max_kernel(), _softmax_kernel(), _flat_or_reshape_ptr(nullptr), _fill_border_kernel(), _reshape(), _max(), _tmp(), _input_flattened(), _output_flattened(),
+      _needs_flattening(false)
 {
 }
 
@@ -46,23 +46,20 @@ void NESoftmaxLayerGeneric<IS_LOG>::configure_reshape_input_kernel(const ITensor
     // Initialize the flat input
     _input_flattened.allocator()->init(input->info()->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(shape_flatten));
 
-    // If we need to flatten the input, we can use NEFlattenKernel or NEReshapeKernel
-    // If the number of reduced axes is 3 (max dimension), which means collapsing all axes except the batch axis, we use NEFlattenKernel.
-    // In all other cases we have to use NEReshapeKernel
     // Note that the "other cases" include both:
     //   1. first_n_reduce_axes < 3: Reduce the first 1 (no need to reduce) or 2 dimensions (inclusive)
     //   2. first_n_reduce_axes == 4: Reduce all 4 dimensions. This can only be handled by NEReshapeKernel instead of NEFlattenKernel.
     if(first_n_reduce_axes == 3)
     {
-        auto flatten_kernel_ptr = support::cpp14::make_unique<NEFlattenLayerKernel>();
+        auto flatten_kernel_ptr = support::cpp14::make_unique<NEFlattenLayer>();
         flatten_kernel_ptr->configure(input, &_input_flattened);
-        _flat_or_reshape_kernel_ptr = std::move(flatten_kernel_ptr);
+        _flat_or_reshape_ptr = std::move(flatten_kernel_ptr);
     }
     else
     {
-        auto reshape_kernel_ptr = support::cpp14::make_unique<NEReshapeLayerKernel>();
+        auto reshape_kernel_ptr = support::cpp14::make_unique<NEReshapeLayer>();
         reshape_kernel_ptr->configure(input, &_input_flattened);
-        _flat_or_reshape_kernel_ptr = std::move(reshape_kernel_ptr);
+        _flat_or_reshape_ptr = std::move(reshape_kernel_ptr);
     }
 
     // We need to init the output tensor here. Indeed, the reshape kernel expects
@@ -127,7 +124,7 @@ void NESoftmaxLayerGeneric<IS_LOG>::configure(ITensor *input, ITensor *output, f
         _input_flattened.allocator()->allocate();
 
         // Reshape the flat output into the requested (4D) output
-        _reshape_kernel.configure(&_output_flattened, output);
+        _reshape.configure(&_output_flattened, output);
 
         // Allocate the intermediate flat tensors
         _output_flattened.allocator()->allocate();
@@ -174,11 +171,11 @@ Status NESoftmaxLayerGeneric<IS_LOG>::validate(const ITensorInfo *input, const I
 
         if(first_n_reduce_axes == 3)
         {
-            ARM_COMPUTE_RETURN_ON_ERROR(NEFlattenLayerKernel::validate(input, &tensor_info_flat));
+            ARM_COMPUTE_RETURN_ON_ERROR(NEFlattenLayer::validate(input, &tensor_info_flat));
         }
         else
         {
-            ARM_COMPUTE_RETURN_ON_ERROR(NEReshapeLayerKernel::validate(input, &tensor_info_flat));
+            ARM_COMPUTE_RETURN_ON_ERROR(NEReshapeLayer::validate(input, &tensor_info_flat));
         }
     }
 
@@ -195,7 +192,7 @@ void           NESoftmaxLayerGeneric<IS_LOG>::run()
 
     if(_needs_flattening)
     {
-        NEScheduler::get().schedule(_flat_or_reshape_kernel_ptr.get(), Window::DimY);
+        _flat_or_reshape_ptr->run();
     }
 
     NEScheduler::get().schedule(&_fill_border_kernel, Window::DimY);
@@ -204,11 +201,11 @@ void           NESoftmaxLayerGeneric<IS_LOG>::run()
 
     if(_needs_flattening)
     {
-        NEScheduler::get().schedule(&_reshape_kernel, Window::DimY);
+        _reshape.run();
     }
 }
 
 template class NESoftmaxLayerGeneric<false>;
 template class NESoftmaxLayerGeneric<true>;
 
-} // namespace arm_compute
\ No newline at end of file
+} // namespace arm_compute