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/helpers/MemoryHelpers.h b/src/core/helpers/MemoryHelpers.h
index a410526..dd094b4 100644
--- a/src/core/helpers/MemoryHelpers.h
+++ b/src/core/helpers/MemoryHelpers.h
@@ -24,9 +24,9 @@
#ifndef SRC_COMMON_MEMORY_HELPERS_H
#define SRC_COMMON_MEMORY_HELPERS_H
+#include "arm_compute/core/experimental/Types.h"
#include "arm_compute/core/ITensorPack.h"
#include "arm_compute/core/TensorInfo.h"
-#include "arm_compute/core/experimental/Types.h"
#include "arm_compute/runtime/MemoryGroup.h"
#include <memory>
@@ -43,18 +43,17 @@
template <typename TensorType>
struct WorkspaceDataElement
{
- int slot{ -1 };
- experimental::MemoryLifetime lifetime{ experimental::MemoryLifetime::Temporary };
- std::unique_ptr<TensorType> tensor{ nullptr };
+ int slot{-1};
+ experimental::MemoryLifetime lifetime{experimental::MemoryLifetime::Temporary};
+ std::unique_ptr<TensorType> tensor{nullptr};
};
template <typename TensorType>
using WorkspaceData = std::vector<WorkspaceDataElement<TensorType>>;
template <typename TensorType>
-WorkspaceData<TensorType> manage_workspace(const experimental::MemoryRequirements &mem_reqs,
- MemoryGroup &mgroup,
- ITensorPack &run_pack)
+WorkspaceData<TensorType>
+manage_workspace(const experimental::MemoryRequirements &mem_reqs, MemoryGroup &mgroup, ITensorPack &run_pack)
{
ITensorPack dummy_pack = ITensorPack();
return manage_workspace<TensorType>(mem_reqs, mgroup, run_pack, dummy_pack);
@@ -63,24 +62,26 @@
template <typename TensorType>
WorkspaceData<TensorType> manage_workspace(const experimental::MemoryRequirements &mem_reqs,
MemoryGroup &mgroup,
- ITensorPack &run_pack, ITensorPack &prep_pack)
+ ITensorPack &run_pack,
+ ITensorPack &prep_pack)
{
WorkspaceData<TensorType> workspace_memory;
- for(const auto &req : mem_reqs)
+ for (const auto &req : mem_reqs)
{
- if(req.size == 0)
+ if (req.size == 0)
{
continue;
}
- const auto aux_info = TensorInfo{ TensorShape(req.size), 1, DataType::U8 };
- workspace_memory.emplace_back(WorkspaceDataElement<TensorType> { req.slot, req.lifetime, std::make_unique<TensorType>() });
+ const auto aux_info = TensorInfo{TensorShape(req.size), 1, DataType::U8};
+ workspace_memory.emplace_back(
+ WorkspaceDataElement<TensorType>{req.slot, req.lifetime, std::make_unique<TensorType>()});
auto aux_tensor = workspace_memory.back().tensor.get();
ARM_COMPUTE_ERROR_ON_NULLPTR(aux_tensor);
aux_tensor->allocator()->init(aux_info, req.alignment);
- if(req.lifetime == experimental::MemoryLifetime::Temporary)
+ if (req.lifetime == experimental::MemoryLifetime::Temporary)
{
mgroup.manage(aux_tensor);
}
@@ -91,7 +92,7 @@
run_pack.add_tensor(req.slot, aux_tensor);
}
- for(auto &mem : workspace_memory)
+ for (auto &mem : workspace_memory)
{
auto tensor = mem.tensor.get();
tensor->allocator()->allocate();
@@ -103,31 +104,29 @@
template <typename TensorType>
void release_prepare_tensors(WorkspaceData<TensorType> &workspace, ITensorPack &prep_pack)
{
- workspace.erase(std::remove_if(workspace.begin(),
- workspace.end(),
- [&prep_pack](auto & wk)
- {
- const bool to_erase = wk.lifetime == experimental::MemoryLifetime::Prepare;
- if(to_erase)
- {
- prep_pack.remove_tensor(wk.slot);
- }
- return to_erase;
- }),
- workspace.end());
+ workspace.erase(std::remove_if(workspace.begin(), workspace.end(),
+ [&prep_pack](auto &wk)
+ {
+ const bool to_erase = wk.lifetime == experimental::MemoryLifetime::Prepare;
+ if (to_erase)
+ {
+ prep_pack.remove_tensor(wk.slot);
+ }
+ return to_erase;
+ }),
+ workspace.end());
}
/** Utility function to release tensors with lifetime marked as Prepare */
template <typename TensorType>
-void release_temporaries(const experimental::MemoryRequirements &mem_reqs,
- WorkspaceData<TensorType> &workspace)
+void release_temporaries(const experimental::MemoryRequirements &mem_reqs, WorkspaceData<TensorType> &workspace)
{
- for(auto &ws : workspace)
+ for (auto &ws : workspace)
{
const int slot = ws.slot;
- for(auto &m : mem_reqs)
+ for (auto &m : mem_reqs)
{
- if(m.slot == slot && m.lifetime == experimental::MemoryLifetime::Prepare)
+ if (m.slot == slot && m.lifetime == experimental::MemoryLifetime::Prepare)
{
auto tensor = ws.tensor.get();
tensor->allocator()->free();