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, 44 insertions, 19 deletions

diff --git a/src/runtime/CL/functions/CLArgMinMaxLayer.cpp b/src/runtime/CL/functions/CLArgMinMaxLayer.cpp
index b30d739025..f9bbd31e8a 100644
--- a/src/runtime/CL/functions/CLArgMinMaxLayer.cpp
+++ b/src/runtime/CL/functions/CLArgMinMaxLayer.cpp
@@ -27,31 +27,39 @@
 #include "arm_compute/core/Error.h"
 #include "arm_compute/core/TensorInfo.h"
 #include "arm_compute/core/Types.h"
-#include "arm_compute/core/Validate.h"
 #include "arm_compute/core/utils/misc/ShapeCalculator.h"
+#include "arm_compute/core/Validate.h"
+
+#include "src/common/utils/Log.h"
 #include "src/core/CL/CLValidate.h"
 #include "src/core/CL/kernels/CLArgMinMaxLayerKernel.h"
 #include "src/core/helpers/AutoConfiguration.h"
 #include "src/runtime/Utils.h"
 
-#include "src/common/utils/Log.h"
-
 namespace arm_compute
 {
 CLArgMinMaxLayer::CLArgMinMaxLayer(std::shared_ptr<IMemoryManager> memory_manager)
-    : _memory_group(std::move(memory_manager)), _not_reshaped_output(), _arg_min_max_kernel(), _reshape(), _reduction_axis()
+    : _memory_group(std::move(memory_manager)),
+      _not_reshaped_output(),
+      _arg_min_max_kernel(),
+      _reshape(),
+      _reduction_axis()
 {
 }
 
 CLArgMinMaxLayer::~CLArgMinMaxLayer() = default;
 
-Status CLArgMinMaxLayer::validate(const ITensorInfo *input, int axis, const ITensorInfo *output, const ReductionOperation &op)
+Status
+CLArgMinMaxLayer::validate(const ITensorInfo *input, int axis, const ITensorInfo *output, const ReductionOperation &op)
 {
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input);
-    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::S32, DataType::F16, DataType::F32);
-    ARM_COMPUTE_RETURN_ERROR_ON_MSG(op != ReductionOperation::ARG_IDX_MAX && op != ReductionOperation::ARG_IDX_MIN, "Invalid reduction operation");
-    ARM_COMPUTE_RETURN_ERROR_ON_MSG(axis >= static_cast<int>(TensorShape::num_max_dimensions), "Reduction axis greater than max number of dimensions");
+    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED,
+                                                         DataType::S32, DataType::F16, DataType::F32);
+    ARM_COMPUTE_RETURN_ERROR_ON_MSG(op != ReductionOperation::ARG_IDX_MAX && op != ReductionOperation::ARG_IDX_MIN,
+                                    "Invalid reduction operation");
+    ARM_COMPUTE_RETURN_ERROR_ON_MSG(axis >= static_cast<int>(TensorShape::num_max_dimensions),
+                                    "Reduction axis greater than max number of dimensions");
     ARM_COMPUTE_RETURN_ERROR_ON_MSG(axis > 3, "Unsupported reduction axis");
 
     DataType   output_data_type = DataType::S32;
@@ -59,17 +67,18 @@ Status CLArgMinMaxLayer::validate(const ITensorInfo *input, int axis, const ITen
     const auto input_num_channles = input->num_channels();
     const auto input_qinfo        = input->quantization_info();
 
-    if(output->total_size() != 0)
+    if (output->total_size() != 0)
     {
         output_data_type                       = output->data_type();
-        const TensorInfo expected_output_shape = output->clone()->set_tensor_shape(arm_compute::misc::shape_calculator::compute_reduced_shape(input->tensor_shape(), axis, false));
+        const TensorInfo expected_output_shape = output->clone()->set_tensor_shape(
+            arm_compute::misc::shape_calculator::compute_reduced_shape(input->tensor_shape(), axis, false));
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(&expected_output_shape, output);
     }
 
     auto shape_before_reshape = input->tensor_shape();
     shape_before_reshape.set(axis, 1);
-    auto initialize_tensorinfo = [](TensorInfo & ti, TensorShape shape, DataType data_type, int num_channels, QuantizationInfo qinfo)
-    {
+    auto initialize_tensorinfo = [](TensorInfo &ti, TensorShape shape, DataType data_type, int num_channels,
+                                    QuantizationInfo qinfo) {
         ti.set_data_type(data_type).set_tensor_shape(shape).set_num_channels(num_channels).set_quantization_info(qinfo);
     };
 
@@ -85,20 +94,36 @@ void CLArgMinMaxLayer::configure(const ICLTensor *input, int axis, ICLTensor *ou
     configure(CLKernelLibrary::get().get_compile_context(), input, axis, output, op);
 }
 
-void CLArgMinMaxLayer::configure(const CLCompileContext &compile_context, const ICLTensor *input, int axis, ICLTensor *output, const ReductionOperation &op)
+void CLArgMinMaxLayer::configure(const CLCompileContext   &compile_context,
+                                 const ICLTensor          *input,
+                                 int                       axis,
+                                 ICLTensor                *output,
+                                 const ReductionOperation &op)
 {
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_LOG_PARAMS(input, axis, output, op);
 
     _reduction_axis = axis;
 
-    const TensorShape output_shape     = arm_compute::misc::shape_calculator::compute_reduced_shape(input->info()->tensor_shape(), axis, false);
-    DataType          output_data_type = (output->info()->data_type() == DataType::UNKNOWN) ? DataType::S32 : output->info()->data_type();
-    auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(output_shape).set_data_type(output_data_type).reset_padding().set_is_resizable(true));
-
-    TensorShape not_reshaped_output_shape{ input->info()->tensor_shape() };
+    const TensorShape output_shape =
+        arm_compute::misc::shape_calculator::compute_reduced_shape(input->info()->tensor_shape(), axis, false);
+    DataType output_data_type =
+        (output->info()->data_type() == DataType::UNKNOWN) ? DataType::S32 : output->info()->data_type();
+    auto_init_if_empty(*output->info(), input->info()
+                                            ->clone()
+                                            ->set_tensor_shape(output_shape)
+                                            .set_data_type(output_data_type)
+                                            .reset_padding()
+                                            .set_is_resizable(true));
+
+    TensorShape not_reshaped_output_shape{input->info()->tensor_shape()};
     not_reshaped_output_shape.set(axis, 1);
-    auto_init_if_empty(*_not_reshaped_output.info(), input->info()->clone()->set_tensor_shape(not_reshaped_output_shape).set_data_type(output_data_type).reset_padding().set_is_resizable(true));
+    auto_init_if_empty(*_not_reshaped_output.info(), input->info()
+                                                         ->clone()
+                                                         ->set_tensor_shape(not_reshaped_output_shape)
+                                                         .set_data_type(output_data_type)
+                                                         .reset_padding()
+                                                         .set_is_resizable(true));
 
     _arg_min_max_kernel = std::make_unique<CLArgMinMaxLayerKernel>();
     _arg_min_max_kernel->configure(compile_context, input, &_not_reshaped_output, axis, op);