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, 21 insertions, 17 deletions

diff --git a/src/core/CL/kernels/CLRangeKernel.cpp b/src/core/CL/kernels/CLRangeKernel.cpp
index a06c2eed75..622f6210b9 100644
--- a/src/core/CL/kernels/CLRangeKernel.cpp
+++ b/src/core/CL/kernels/CLRangeKernel.cpp
@@ -28,6 +28,7 @@
 #include "arm_compute/core/Utils.h"
 #include "arm_compute/core/utils/helpers/AdjustVecSize.h"
 #include "arm_compute/core/utils/StringUtils.h"
+
 #include "src/core/CL/CLValidate.h"
 #include "src/core/helpers/AutoConfiguration.h"
 #include "src/core/helpers/WindowHelpers.h"
@@ -42,11 +43,8 @@ constexpr unsigned int vector_size_byte_opencl = 16;
 Status validate_arguments(const ITensorInfo *output, const float start, const float end, const float step)
 {
     ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output);
-    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output,
-                                                         1,
-                                                         DataType::U8, DataType::S8, DataType::QASYMM8,
-                                                         DataType::U16, DataType::S16,
-                                                         DataType::U32, DataType::S32,
+    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8, DataType::S8, DataType::QASYMM8,
+                                                         DataType::U16, DataType::S16, DataType::U32, DataType::S32,
                                                          DataType::F16, DataType::F32);
     ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(output);
 
@@ -56,19 +54,22 @@ Status validate_arguments(const ITensorInfo *output, const float start, const fl
 
     ARM_COMPUTE_RETURN_ERROR_ON_MSG((start == end), "start of the requested sequence must not be equal to the end");
 
-    ARM_COMPUTE_RETURN_ERROR_ON_MSG(!check_value_range(start, output->data_type(), output->quantization_info()), "start value is outside the range of the data type");
-    ARM_COMPUTE_RETURN_ERROR_ON_MSG(!check_value_range(end, output->data_type(), output->quantization_info()), "end value is outside the range of the data type");
-    ARM_COMPUTE_RETURN_ERROR_ON_MSG(!check_value_range(step, output->data_type(), output->quantization_info()), "step value is outside the range of the data type");
+    ARM_COMPUTE_RETURN_ERROR_ON_MSG(!check_value_range(start, output->data_type(), output->quantization_info()),
+                                    "start value is outside the range of the data type");
+    ARM_COMPUTE_RETURN_ERROR_ON_MSG(!check_value_range(end, output->data_type(), output->quantization_info()),
+                                    "end value is outside the range of the data type");
+    ARM_COMPUTE_RETURN_ERROR_ON_MSG(!check_value_range(step, output->data_type(), output->quantization_info()),
+                                    "step value is outside the range of the data type");
 
     ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->num_dimensions() != 1, "Output has to be a 1-D tensor");
-    ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->tensor_shape().total_size() < num_of_elements_in_range(start, end, step), "Output tensor size is incorrect");
+    ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->tensor_shape().total_size() < num_of_elements_in_range(start, end, step),
+                                    "Output tensor size is incorrect");
 
     return Status{};
 }
 } // namespace
 
-CLRangeKernel::CLRangeKernel()
-    : _start(0), _end(1), _step(1), _output(nullptr)
+CLRangeKernel::CLRangeKernel() : _start(0), _end(1), _step(1), _output(nullptr)
 {
     _type = CLKernelType::ELEMENTWISE;
 }
@@ -78,16 +79,18 @@ void CLRangeKernel::configure(ICLTensor *output, const float start, const float
     configure(CLKernelLibrary::get().get_compile_context(), output, start, end, step);
 }
 
-void CLRangeKernel::configure(const CLCompileContext &compile_context, ICLTensor *output, const float start, const float end, const float step)
+void CLRangeKernel::configure(
+    const CLCompileContext &compile_context, ICLTensor *output, const float start, const float end, const float step)
 {
     ARM_COMPUTE_ERROR_ON_NULLPTR(output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(output->info(), start, end, step));
 
     // Configure kernel window
-    unsigned int num_elems_processed_per_iteration = adjust_vec_size(vector_size_byte_opencl / output->info()->element_size(), output->info()->dimension(0));
-    Window       win                               = calculate_max_window(*output->info(), Steps(num_elems_processed_per_iteration));
+    unsigned int num_elems_processed_per_iteration =
+        adjust_vec_size(vector_size_byte_opencl / output->info()->element_size(), output->info()->dimension(0));
+    Window win = calculate_max_window(*output->info(), Steps(num_elems_processed_per_iteration));
 
-    auto padding_info = get_padding_info({ output });
+    auto padding_info = get_padding_info({output});
 
     _start  = start;
     _end    = end;
@@ -100,10 +103,11 @@ void CLRangeKernel::configure(const CLCompileContext &compile_context, ICLTensor
     CLBuildOptions build_opts;
     build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(output->info()->data_type()));
     build_opts.add_option("-DVECTOR_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration));
-    build_opts.add_option("-DVEC_SIZE_LEFTOVER=" + support::cpp11::to_string(output->info()->dimension(0) % num_elems_processed_per_iteration));
+    build_opts.add_option("-DVEC_SIZE_LEFTOVER=" +
+                          support::cpp11::to_string(output->info()->dimension(0) % num_elems_processed_per_iteration));
     build_opts.add_option("-DSTART=" + support::cpp11::to_string(start));
     build_opts.add_option("-DSTEP=" + support::cpp11::to_string(step));
-    if(is_data_type_quantized_asymmetric(output->info()->data_type()))
+    if (is_data_type_quantized_asymmetric(output->info()->data_type()))
     {
         const UniformQuantizationInfo qinfo = output->info()->quantization_info().uniform();
         build_opts.add_option("-DOFFSET_OUT=" + support::cpp11::to_string(qinfo.offset));