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, 26 insertions, 19 deletions

diff --git a/src/core/CL/kernels/CLL2NormalizeLayerKernel.cpp b/src/core/CL/kernels/CLL2NormalizeLayerKernel.cpp
index 542d380e4a..9ed9d7c5b0 100644
--- a/src/core/CL/kernels/CLL2NormalizeLayerKernel.cpp
+++ b/src/core/CL/kernels/CLL2NormalizeLayerKernel.cpp
@@ -31,10 +31,10 @@
 #include "arm_compute/core/Utils.h"
 #include "arm_compute/core/utils/helpers/AdjustVecSize.h"
 #include "arm_compute/core/Validate.h"
+
 #include "src/core/CL/CLValidate.h"
 #include "src/core/helpers/AutoConfiguration.h"
 #include "src/core/helpers/WindowHelpers.h"
-
 #include "support/StringSupport.h"
 
 namespace arm_compute
@@ -43,7 +43,8 @@ namespace
 {
 constexpr int max_input_tensor_dim = 3;
 
-Status validate_arguments(const ITensorInfo *input, const ITensorInfo *sum, const ITensorInfo *output, int axis, float epsilon)
+Status
+validate_arguments(const ITensorInfo *input, const ITensorInfo *sum, const ITensorInfo *output, int axis, float epsilon)
 {
     ARM_COMPUTE_UNUSED(epsilon);
 
@@ -53,14 +54,15 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *sum, cons
     ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input);
     ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32);
     ARM_COMPUTE_RETURN_ERROR_ON_MSG(actual_axis > 2, "Actual axis greater than 2 is not supported");
-    ARM_COMPUTE_RETURN_ERROR_ON_MSG(actual_axis >= TensorShape::num_max_dimensions, "Actual normalization axis greater than max number of dimensions");
+    ARM_COMPUTE_RETURN_ERROR_ON_MSG(actual_axis >= TensorShape::num_max_dimensions,
+                                    "Actual normalization axis greater than max number of dimensions");
 
     // Reduce shape on axis
     TensorShape sum_shape = input->tensor_shape();
     sum_shape.set(actual_axis, 1);
     ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(sum->tensor_shape(), sum_shape);
 
-    if(output->total_size() != 0)
+    if (output->total_size() != 0)
     {
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output);
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input, output);
@@ -78,16 +80,22 @@ CLL2NormalizeLayerKernel::CLL2NormalizeLayerKernel()
     _type = CLKernelType::ELEMENTWISE;
 }
 
-void CLL2NormalizeLayerKernel::configure(const ICLTensor *input, const ICLTensor *sum, ICLTensor *output, int axis, float epsilon)
+void CLL2NormalizeLayerKernel::configure(
+    const ICLTensor *input, const ICLTensor *sum, ICLTensor *output, int axis, float epsilon)
 {
     configure(CLKernelLibrary::get().get_compile_context(), input, sum, output, axis, epsilon);
 }
 
-void CLL2NormalizeLayerKernel::configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *sum, ICLTensor *output, int axis, float epsilon)
+void CLL2NormalizeLayerKernel::configure(const CLCompileContext &compile_context,
+                                         const ICLTensor        *input,
+                                         const ICLTensor        *sum,
+                                         ICLTensor              *output,
+                                         int                     axis,
+                                         float                   epsilon)
 {
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, sum, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), sum->info(), output->info(), axis, epsilon));
-    auto padding_info = get_padding_info({ input, sum, output });
+    auto padding_info = get_padding_info({input, sum, output});
 
     _input       = input;
     _sum         = sum;
@@ -95,8 +103,9 @@ void CLL2NormalizeLayerKernel::configure(const CLCompileContext &compile_context
     _actual_axis = wrap_around(axis, max_input_tensor_dim);
     _epsilon     = epsilon;
 
-    const unsigned int vec_size_x           = adjust_vec_size(max_cl_vector_width / input->info()->element_size(), input->info()->dimension(0));
-    const int          vec_size_x_leftovers = input->info()->dimension(0) % vec_size_x;
+    const unsigned int vec_size_x =
+        adjust_vec_size(max_cl_vector_width / input->info()->element_size(), input->info()->dimension(0));
+    const int vec_size_x_leftovers = input->info()->dimension(0) % vec_size_x;
 
     // Set build options
     CLBuildOptions build_opts;
@@ -107,7 +116,7 @@ void CLL2NormalizeLayerKernel::configure(const CLCompileContext &compile_context
     // Create kernel
     std::string  kernel_name;
     unsigned int idx = 0;
-    switch(_actual_axis)
+    switch (_actual_axis)
     {
         case 0:
             kernel_name = "l2_normalize_x";
@@ -127,7 +136,7 @@ void CLL2NormalizeLayerKernel::configure(const CLCompileContext &compile_context
     _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
 
     // Set epsilon argument
-    if(input->info()->data_type() == DataType::F32)
+    if (input->info()->data_type() == DataType::F32)
     {
         _kernel.setArg<cl_float>(idx, _epsilon);
     }
@@ -146,7 +155,8 @@ void CLL2NormalizeLayerKernel::configure(const CLCompileContext &compile_context
     ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info));
 }
 
-Status CLL2NormalizeLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *sum, const ITensorInfo *output, int axis, float epsilon)
+Status CLL2NormalizeLayerKernel::validate(
+    const ITensorInfo *input, const ITensorInfo *sum, const ITensorInfo *output, int axis, float epsilon)
 {
     ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, sum, output, axis, epsilon));
     return Status{};
@@ -159,7 +169,7 @@ void CLL2NormalizeLayerKernel::run(const Window &window, cl::CommandQueue &queue
 
     Window window_sum(window);
 
-    switch(_actual_axis)
+    switch (_actual_axis)
     {
         case 0:
         {
@@ -173,8 +183,7 @@ void CLL2NormalizeLayerKernel::run(const Window &window, cl::CommandQueue &queue
                 add_2D_tensor_argument(idx, _sum, sum_slice);
                 add_2D_tensor_argument(idx, _output, in_slice);
                 enqueue(queue, *this, in_slice, lws_hint());
-            }
-            while(window.slide_window_slice_2D(in_slice) && window.slide_window_slice_2D(sum_slice));
+            } while (window.slide_window_slice_2D(in_slice) && window.slide_window_slice_2D(sum_slice));
         }
         break;
         case 1:
@@ -189,8 +198,7 @@ void CLL2NormalizeLayerKernel::run(const Window &window, cl::CommandQueue &queue
                 add_2D_tensor_argument(idx, _sum, sum_slice);
                 add_2D_tensor_argument(idx, _output, in_slice);
                 enqueue(queue, *this, in_slice, lws_hint());
-            }
-            while(window.slide_window_slice_2D(in_slice) && window.slide_window_slice_2D(sum_slice));
+            } while (window.slide_window_slice_2D(in_slice) && window.slide_window_slice_2D(sum_slice));
         }
         break;
         case 2:
@@ -205,8 +213,7 @@ void CLL2NormalizeLayerKernel::run(const Window &window, cl::CommandQueue &queue
                 add_3D_tensor_argument(idx, _sum, sum_slice);
                 add_3D_tensor_argument(idx, _output, in_slice);
                 enqueue(queue, *this, in_slice, lws_hint());
-            }
-            while(window.slide_window_slice_3D(in_slice) && window.slide_window_slice_3D(sum_slice));
+            } while (window.slide_window_slice_3D(in_slice) && window.slide_window_slice_3D(sum_slice));
         }
         break;
         default: