COMPMID-920: Introduce prepare() stage

Change-Id: I08ddb7f6e061178e7566518b48e4e18f8f078596
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/129825
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>

1 files changed, 11 insertions, 1 deletions

diff --git a/arm_compute/runtime/CL/functions/CLWinogradConvolutionLayer.h b/arm_compute/runtime/CL/functions/CLWinogradConvolutionLayer.h
index a27976959c..594d6028e1 100644
--- a/arm_compute/runtime/CL/functions/CLWinogradConvolutionLayer.h
+++ b/arm_compute/runtime/CL/functions/CLWinogradConvolutionLayer.h
@@ -49,6 +49,14 @@ class CLWinogradConvolutionLayer : public IFunction
 public:
     /** Default constructor */
     CLWinogradConvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
+    /** Prevent instances of this class from being copied (As this class contains pointers) */
+    CLWinogradConvolutionLayer(const CLWinogradConvolutionLayer &) = delete;
+    /** Default move constructor */
+    CLWinogradConvolutionLayer(CLWinogradConvolutionLayer &&) = default;
+    /** Prevent instances of this class from being copied (As this class contains pointers) */
+    CLWinogradConvolutionLayer &operator=(const CLWinogradConvolutionLayer &) = delete;
+    /** Default move assignment operator */
+    CLWinogradConvolutionLayer &operator=(CLWinogradConvolutionLayer &&) = default;
     /** Set the input and output tensors.
      *
      * @note: This function only works with 3x3 and 5x5 kernels along with unit strides
@@ -92,6 +100,7 @@ public:
 
     // Inherited methods overridden:
     void run() override;
+    void prepare() override;
 
 private:
     CLMemoryGroup                   _memory_group;
@@ -103,7 +112,8 @@ private:
     CLTensor                        _input0;
     CLTensor                        _input1;
     CLTensor                        _batched_mm_output;
-    bool                            _is_first_run;
+    const ICLTensor                *_original_weights;
+    bool                            _is_prepared;
     bool                            _is_activationlayer_enabled;
 };
 }