Apply clang-format on repository

Code is formatted as per a revised clang format configuration
file(not part of this delivery). Version 14.0.6 is used.

Exclusion List:
- files with .cl extension
- files that are not strictly C/C++ (e.g. Android.bp, Sconscript ...)
And the following directories
- compute_kernel_writer/validation/
- tests/
- include/
- src/core/NEON/kernels/convolution/
- src/core/NEON/kernels/arm_gemm/
- src/core/NEON/kernels/arm_conv/
- data/

There will be a follow up for formatting of .cl files and the
files under tests/ and compute_kernel_writer/validation/.

Signed-off-by: Felix Thomasmathibalan <felixjohnny.thomasmathibalan@arm.com>
Change-Id: Ib7eb1fcf4e7537b9feaefcfc15098a804a3fde0a
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10391
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>

1 files changed, 19 insertions, 7 deletions

diff --git a/src/gpu/cl/operators/ClWinogradConv2d.h b/src/gpu/cl/operators/ClWinogradConv2d.h
index eb2f7a72b2..54ec1a1737 100644
--- a/src/gpu/cl/operators/ClWinogradConv2d.h
+++ b/src/gpu/cl/operators/ClWinogradConv2d.h
@@ -25,6 +25,7 @@
 #define ARM_COMPUTE_CL_WINOGRADCONV2D_H
 
 #include "arm_compute/runtime/CL/CLTensor.h"
+
 #include "src/core/CL/kernels/CLFillBorderKernel.h"
 #include "src/gpu/cl/ClCompileContext.h"
 #include "src/gpu/cl/IClOperator.h"
@@ -41,7 +42,7 @@ namespace kernels
 class ClWinogradInputTransformKernel;
 class ClWinogradFilterTransformKernel;
 class ClWinogradOutputTransformKernel;
-} // kernels
+} // namespace kernels
 /** Basic function to execute Winograd-based convolution on OpenCL. This function calls the following OpenCL functions/kernels:
  *
  *  -# @ref kernels::ClWinogradInputTransformKernel
@@ -93,20 +94,31 @@ public:
      * @param[in]  enable_fast_math (Optional) Enable fast math computation. In case this flag were set, the function could dispatch the fastest implementation
      *                              available which may introduce a drop of accuracy as well. Default is false
      */
-    void configure(const ClCompileContext &compile_context, ITensorInfo *src, ITensorInfo *weights, ITensorInfo *biases, ITensorInfo *dst, const PadStrideInfo &conv_info,
-                   const ActivationLayerInfo &act_info = ActivationLayerInfo(), bool enable_fast_math = false);
+    void configure(const ClCompileContext    &compile_context,
+                   ITensorInfo               *src,
+                   ITensorInfo               *weights,
+                   ITensorInfo               *biases,
+                   ITensorInfo               *dst,
+                   const PadStrideInfo       &conv_info,
+                   const ActivationLayerInfo &act_info         = ActivationLayerInfo(),
+                   bool                       enable_fast_math = false);
     /** Static function to check if given info will lead to a valid configuration
      *
      * Similar to ClWinogradConv2d::configure()
      *
      * @return a status
      */
-    static Status validate(const ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *dst, const PadStrideInfo &conv_info,
-                           const ActivationLayerInfo &act_info = ActivationLayerInfo(), bool enable_fast_math = false);
+    static Status validate(const ITensorInfo         *src,
+                           const ITensorInfo         *weights,
+                           const ITensorInfo         *biases,
+                           const ITensorInfo         *dst,
+                           const PadStrideInfo       &conv_info,
+                           const ActivationLayerInfo &act_info         = ActivationLayerInfo(),
+                           bool                       enable_fast_math = false);
 
     // Inherited method overridden
-    void run(ITensorPack &tensors) override;
-    void prepare(ITensorPack &tensors) override;
+    void                             run(ITensorPack &tensors) override;
+    void                             prepare(ITensorPack &tensors) override;
     experimental::MemoryRequirements workspace() const override;
 
 private: