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>
diff --git a/src/core/CL/kernels/CLROIPoolingLayerKernel.cpp b/src/core/CL/kernels/CLROIPoolingLayerKernel.cpp
index f6933c6..1b2c414 100644
--- a/src/core/CL/kernels/CLROIPoolingLayerKernel.cpp
+++ b/src/core/CL/kernels/CLROIPoolingLayerKernel.cpp
@@ -31,6 +31,7 @@
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/Utils.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"
@@ -48,7 +49,10 @@
_type = CLKernelType::ELEMENTWISE;
}
-Status CLROIPoolingLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *rois, const ITensorInfo *output, const ROIPoolingLayerInfo &pool_info)
+Status CLROIPoolingLayerKernel::validate(const ITensorInfo *input,
+ const ITensorInfo *rois,
+ const ITensorInfo *output,
+ const ROIPoolingLayerInfo &pool_info)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, rois, output);
@@ -61,10 +65,11 @@
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32, DataType::F16, DataType::QASYMM8);
ARM_COMPUTE_RETURN_ERROR_ON((pool_info.pooled_width() == 0) || (pool_info.pooled_height() == 0));
- if(output->total_size() != 0)
+ if (output->total_size() != 0)
{
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
- ARM_COMPUTE_RETURN_ERROR_ON((output->dimension(0) != pool_info.pooled_width()) || (output->dimension(1) != pool_info.pooled_height()));
+ ARM_COMPUTE_RETURN_ERROR_ON((output->dimension(0) != pool_info.pooled_width()) ||
+ (output->dimension(1) != pool_info.pooled_height()));
ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(2) != output->dimension(2));
ARM_COMPUTE_RETURN_ERROR_ON(rois->dimension(1) != output->dimension(3));
}
@@ -72,20 +77,30 @@
return Status{};
}
-void CLROIPoolingLayerKernel::configure(const ICLTensor *input, const ICLTensor *rois, ICLTensor *output, const ROIPoolingLayerInfo &pool_info)
+void CLROIPoolingLayerKernel::configure(const ICLTensor *input,
+ const ICLTensor *rois,
+ ICLTensor *output,
+ const ROIPoolingLayerInfo &pool_info)
{
configure(CLKernelLibrary::get().get_compile_context(), input, rois, output, pool_info);
}
-void CLROIPoolingLayerKernel::configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *rois, const ICLTensor *output, const ROIPoolingLayerInfo &pool_info)
+void CLROIPoolingLayerKernel::configure(const CLCompileContext &compile_context,
+ const ICLTensor *input,
+ const ICLTensor *rois,
+ const ICLTensor *output,
+ const ROIPoolingLayerInfo &pool_info)
{
- ARM_COMPUTE_ERROR_THROW_ON(CLROIPoolingLayerKernel::validate(input->info(), rois->info(), output->info(), pool_info));
+ ARM_COMPUTE_ERROR_THROW_ON(
+ CLROIPoolingLayerKernel::validate(input->info(), rois->info(), output->info(), pool_info));
- auto padding_info = get_padding_info({ input, rois, output });
+ auto padding_info = get_padding_info({input, rois, output});
// Output auto initialization if not yet initialized
- TensorShape output_shape(pool_info.pooled_width(), pool_info.pooled_height(), input->info()->dimension(2), rois->info()->dimension(1));
- auto_init_if_empty(*(output->info()), output_shape, 1, input->info()->data_type(), output->info()->quantization_info());
+ TensorShape output_shape(pool_info.pooled_width(), pool_info.pooled_height(), input->info()->dimension(2),
+ rois->info()->dimension(1));
+ auto_init_if_empty(*(output->info()), output_shape, 1, input->info()->data_type(),
+ output->info()->quantization_info());
// Set instance variables
_input = input;
@@ -107,11 +122,12 @@
build_opts.add_option("-DPOOLED_DIM_Y=" + support::cpp11::to_string(pool_info.pooled_height()));
build_opts.add_option("-DSPATIAL_SCALE=" + support::cpp11::to_string(pool_info.spatial_scale()));
- if(is_qasymm)
+ if (is_qasymm)
{
// Determine quantization info scale, offset
UniformQuantizationInfo uqinfo = UniformQuantizationInfo();
- uqinfo = compute_requantization_scale_offset(_input->info()->quantization_info().uniform(), _output->info()->quantization_info().uniform());
+ uqinfo = compute_requantization_scale_offset(_input->info()->quantization_info().uniform(),
+ _output->info()->quantization_info().uniform());
build_opts.add_option("-DOFFSET_OUT=" + float_to_string_with_full_precision(uqinfo.offset));
build_opts.add_option("-DSCALE_OUT=" + float_to_string_with_full_precision(uqinfo.scale));