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/compute_kernel_writer/src/cl/CLTensorArgument.cpp b/compute_kernel_writer/src/cl/CLTensorArgument.cpp
index 7d4dc95..e53de28 100644
--- a/compute_kernel_writer/src/cl/CLTensorArgument.cpp
+++ b/compute_kernel_writer/src/cl/CLTensorArgument.cpp
@@ -23,11 +23,13 @@
*/
#include "src/cl/CLTensorArgument.h"
+
#include "ckw/Error.h"
-#include "src/ITensorArgument.h"
-#include "src/ITensorComponent.h"
+
#include "src/cl/CLHelpers.h"
#include "src/cl/CLTensorComponent.h"
+#include "src/ITensorArgument.h"
+#include "src/ITensorComponent.h"
#include "src/types/TensorComponentType.h"
#include <algorithm>
@@ -48,25 +50,23 @@
{
// Return the component if it has already been created.
{
- const auto it = std::find_if(
- _components_used.begin(), _components_used.end(),
- [=](const std::unique_ptr<CLTensorComponent> &item)
- {
- return item->component_type() == x;
- });
+ const auto it =
+ std::find_if(_components_used.begin(), _components_used.end(),
+ [=](const std::unique_ptr<CLTensorComponent> &item) { return item->component_type() == x; });
- if(it != _components_used.end())
+ if (it != _components_used.end())
{
return **it;
}
}
- if(_return_dims_by_value)
+ if (_return_dims_by_value)
{
uint32_t component_type = static_cast<uint32_t>(x);
- const bool is_dimension = (component_type & static_cast<uint32_t>(TensorComponentBitmask::Dimension)) != 0;
- const bool is_folded_dimensions = (component_type & static_cast<uint32_t>(TensorComponentBitmask::FoldedDimensions)) != 0;
+ const bool is_dimension = (component_type & static_cast<uint32_t>(TensorComponentBitmask::Dimension)) != 0;
+ const bool is_folded_dimensions =
+ (component_type & static_cast<uint32_t>(TensorComponentBitmask::FoldedDimensions)) != 0;
constexpr auto bitmask_all = static_cast<uint32_t>(TensorComponentIndexBitmask::All);
constexpr auto bitmask_index_0 = static_cast<uint32_t>(TensorComponentIndexBitmask::Index0);
@@ -83,16 +83,16 @@
CKW_ASSERT(bitmask_index_2 == bitmask_index_3 >> 4);
// If we have a dimension or folded dimensions, we can return the corresponding value if it is not dynamic (not equal to -1)
- if(is_dimension == true || is_folded_dimensions == true)
+ if (is_dimension == true || is_folded_dimensions == true)
{
component_type = component_type & bitmask_all;
int32_t idx = 1;
- for(int32_t i = 0; i < tensor_component_index_max_count; ++i)
+ for (int32_t i = 0; i < tensor_component_index_max_count; ++i)
{
uint32_t dim_idx = component_type & bitmask_index_0;
- if(dim_idx == 0)
+ if (dim_idx == 0)
{
// Stop at the first nibble containing 0
break;
@@ -104,7 +104,7 @@
// Get the dimension value
const int32_t dim_val = _info.shape()[dim_idx];
- if(dim_val == kDynamicTensorDimensionValue)
+ if (dim_val == kDynamicTensorDimensionValue)
{
// We cannot return the dimension by value if it is dynamic.
// Therefore, force the idx variable to kDynamicTensorDimensionValue and break the loop.
@@ -118,7 +118,7 @@
component_type >>= 4;
}
- if(idx != kDynamicTensorDimensionValue)
+ if (idx != kDynamicTensorDimensionValue)
{
_components_used.emplace_back(std::make_unique<CLTensorComponent>(*this, x, idx));
@@ -141,14 +141,10 @@
{
// Return the storage if it has already been created.
{
- const auto it = std::find_if(
- _storages_used.begin(), _storages_used.end(),
- [=](const TensorStorageVariable &item)
- {
- return item.type == x;
- });
+ const auto it = std::find_if(_storages_used.begin(), _storages_used.end(),
+ [=](const TensorStorageVariable &item) { return item.type == x; });
- if(it != _storages_used.end())
+ if (it != _storages_used.end())
{
return *it;
}
@@ -167,7 +163,7 @@
{
std::string var_name = _basename;
- switch(x)
+ switch (x)
{
case TensorStorageType::BufferUint8Ptr:
var_name += "_ptr";
@@ -198,9 +194,9 @@
{
std::vector<const ITensorComponent *> components;
- for(const auto &component : _components_used)
+ for (const auto &component : _components_used)
{
- if(component->is_assignable())
+ if (component->is_assignable())
{
components.push_back(component.get());
}