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/runtime/NEON/functions/NEFullyConnectedLayer.cpp b/src/runtime/NEON/functions/NEFullyConnectedLayer.cpp
index 891487e..2656d0f 100644
--- a/src/runtime/NEON/functions/NEFullyConnectedLayer.cpp
+++ b/src/runtime/NEON/functions/NEFullyConnectedLayer.cpp
@@ -27,6 +27,7 @@
#include "arm_compute/core/Validate.h"
#include "arm_compute/runtime/MemoryGroup.h"
#include "arm_compute/runtime/NEON/functions/NEConvertFullyConnectedWeights.h"
+
#include "src/common/utils/Log.h"
#include "src/core/helpers/MemoryHelpers.h"
#include "src/cpu/operators/CpuFullyConnected.h"
@@ -38,80 +39,90 @@
struct NEFullyConnectedLayer::Impl
{
MemoryGroup memory_group{};
- IWeightsManager *weights_manager{ nullptr };
+ IWeightsManager *weights_manager{nullptr};
- std::unique_ptr<cpu::CpuFullyConnected> op{ nullptr };
+ std::unique_ptr<cpu::CpuFullyConnected> op{nullptr};
- const ITensor *original_weights{ nullptr };
+ const ITensor *original_weights{nullptr};
ITensorPack run_pack{};
WorkspaceData<Tensor> workspace{};
experimental::MemoryRequirements aux_mem_req{};
- bool is_prepared{ false };
- bool dynamic_weights{ false };
+ bool is_prepared{false};
+ bool dynamic_weights{false};
};
NEFullyConnectedLayer::~NEFullyConnectedLayer() = default;
-NEFullyConnectedLayer::NEFullyConnectedLayer(std::shared_ptr<IMemoryManager> memory_manager, IWeightsManager *weights_manager)
+NEFullyConnectedLayer::NEFullyConnectedLayer(std::shared_ptr<IMemoryManager> memory_manager,
+ IWeightsManager *weights_manager)
: _impl(std::make_unique<Impl>())
{
_impl->memory_group = MemoryGroup(std::move(memory_manager));
_impl->weights_manager = weights_manager;
}
-void NEFullyConnectedLayer::configure(const ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output,
- FullyConnectedLayerInfo fc_info, const WeightsInfo &weights_info)
+void NEFullyConnectedLayer::configure(const ITensor *input,
+ const ITensor *weights,
+ const ITensor *biases,
+ ITensor *output,
+ FullyConnectedLayerInfo fc_info,
+ const WeightsInfo &weights_info)
{
// Perform validate step
ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output);
- ARM_COMPUTE_ERROR_THROW_ON(NEFullyConnectedLayer::validate(input->info(),
- weights->info(),
+ ARM_COMPUTE_ERROR_THROW_ON(NEFullyConnectedLayer::validate(input->info(), weights->info(),
biases != nullptr ? biases->info() : nullptr,
- output->info(),
- fc_info,
- weights_info));
+ output->info(), fc_info, weights_info));
ARM_COMPUTE_LOG_PARAMS(input, weights, biases, output, fc_info);
_impl->op = std::make_unique<cpu::CpuFullyConnected>();
_impl->original_weights = weights;
_impl->is_prepared = false;
- _impl->op->configure(input->info(), weights->info(), (biases != nullptr) ? biases->info() : nullptr, output->info(), fc_info, weights_info);
+ _impl->op->configure(input->info(), weights->info(), (biases != nullptr) ? biases->info() : nullptr, output->info(),
+ fc_info, weights_info);
- if(_impl->weights_manager != nullptr)
+ if (_impl->weights_manager != nullptr)
{
_impl->weights_manager->manage(_impl->original_weights);
}
_impl->aux_mem_req = _impl->op->workspace();
- _impl->run_pack = { { ACL_SRC_0, input }, { ACL_SRC_1, weights }, { ACL_SRC_2, biases }, { ACL_DST, output } };
- _impl->workspace = manage_workspace<Tensor>(_impl->aux_mem_req, _impl->memory_group, _impl->run_pack, _impl->run_pack);
+ _impl->run_pack = {{ACL_SRC_0, input}, {ACL_SRC_1, weights}, {ACL_SRC_2, biases}, {ACL_DST, output}};
+ _impl->workspace =
+ manage_workspace<Tensor>(_impl->aux_mem_req, _impl->memory_group, _impl->run_pack, _impl->run_pack);
- _impl->dynamic_weights =
- !weights->info()->are_values_constant() &&
- fc_info.transpose_weights &&
- !fc_info.are_weights_reshaped &&
- !fc_info.retain_internal_weights;
+ _impl->dynamic_weights = !weights->info()->are_values_constant() && fc_info.transpose_weights &&
+ !fc_info.are_weights_reshaped && !fc_info.retain_internal_weights;
}
-Status NEFullyConnectedLayer::has_opt_impl(arm_compute::WeightFormat &expected_weight_format, const ITensorInfo *input, const ITensorInfo *weights,
- const ITensorInfo *biases, const ITensorInfo *output, const FullyConnectedLayerInfo &fc_info,
- const WeightsInfo &weights_info)
+Status NEFullyConnectedLayer::has_opt_impl(arm_compute::WeightFormat &expected_weight_format,
+ const ITensorInfo *input,
+ const ITensorInfo *weights,
+ const ITensorInfo *biases,
+ const ITensorInfo *output,
+ const FullyConnectedLayerInfo &fc_info,
+ const WeightsInfo &weights_info)
{
- return cpu::CpuFullyConnected::has_opt_impl(expected_weight_format, input, weights, biases, output, fc_info, weights_info);
+ return cpu::CpuFullyConnected::has_opt_impl(expected_weight_format, input, weights, biases, output, fc_info,
+ weights_info);
}
-Status NEFullyConnectedLayer::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output,
- FullyConnectedLayerInfo fc_info, const WeightsInfo &weights_info)
+Status NEFullyConnectedLayer::validate(const ITensorInfo *input,
+ const ITensorInfo *weights,
+ const ITensorInfo *biases,
+ const ITensorInfo *output,
+ FullyConnectedLayerInfo fc_info,
+ const WeightsInfo &weights_info)
{
return cpu::CpuFullyConnected::validate(input, weights, biases, output, fc_info, weights_info);
}
void NEFullyConnectedLayer::run()
{
- if(!_impl->dynamic_weights)
+ if (!_impl->dynamic_weights)
{
prepare();
}
@@ -122,7 +133,7 @@
void NEFullyConnectedLayer::prepare()
{
- if(!_impl->is_prepared)
+ if (!_impl->is_prepared)
{
_impl->op->prepare(_impl->run_pack);
@@ -131,13 +142,13 @@
_impl->is_prepared = true;
// Handle weights managed infrastructure
- if(_impl->weights_manager != nullptr && _impl->weights_manager->are_weights_managed(_impl->original_weights))
+ if (_impl->weights_manager != nullptr && _impl->weights_manager->are_weights_managed(_impl->original_weights))
{
// Ensure that b gets marked as unused (memory released) only after the last function which uses b also finishes its prepare
// This is for cases where multiple functions share the same b (weights)
// Therefore when a function marks original b as unused, we pre-mark it in weights manager, and mark it back to used so that it doesn't get released before its last reference
const ITensor *original_b = _impl->original_weights;
- if(!original_b->is_used())
+ if (!original_b->is_used())
{
_impl->weights_manager->pre_mark_as_unused(original_b);
}