COMPMID-2214: Remove std::vector<std::unique_ptr<>> where possible.
Change-Id: I6569aa64a4976966445ed7646129c36fe4654cd9
Signed-off-by: Georgios Pinitas <georgios.pinitas@arm.com>
Reviewed-on: https://review.mlplatform.org/c/1190
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michalis Spyrou <michalis.spyrou@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
diff --git a/src/runtime/NEON/functions/NEGaussianPyramid.cpp b/src/runtime/NEON/functions/NEGaussianPyramid.cpp
index 0dbcb12..fbf8812 100644
--- a/src/runtime/NEON/functions/NEGaussianPyramid.cpp
+++ b/src/runtime/NEON/functions/NEGaussianPyramid.cpp
@@ -68,6 +68,7 @@
/* Get number of pyramid levels */
const size_t num_levels = pyramid->info()->num_levels();
+ const size_t num_stages = num_levels - 1;
_input = input;
_pyramid = pyramid;
@@ -81,33 +82,29 @@
PyramidInfo pyramid_info(num_levels - 1, SCALE_PYRAMID_HALF, tensor_shape, Format::S16);
_tmp.init(pyramid_info);
- _horizontal_reduction.reserve(num_levels);
- _vertical_reduction.reserve(num_levels);
- _horizontal_border_handler.reserve(num_levels);
- _vertical_border_handler.reserve(num_levels);
+ _horizontal_reduction.clear();
+ _vertical_reduction.clear();
+ _horizontal_border_handler.clear();
+ _vertical_border_handler.clear();
- for(unsigned int i = 0; i < num_levels - 1; ++i)
+ _horizontal_reduction.resize(num_stages);
+ _vertical_reduction.resize(num_stages);
+ _horizontal_border_handler.resize(num_stages);
+ _vertical_border_handler.resize(num_stages);
+
+ for(size_t i = 0; i < num_stages; ++i)
{
/* Configure horizontal kernel */
- auto horizontal_kernel = support::cpp14::make_unique<NEGaussianPyramidHorKernel>();
- horizontal_kernel->configure(_pyramid->get_pyramid_level(i), _tmp.get_pyramid_level(i));
+ _horizontal_reduction[i].configure(_pyramid->get_pyramid_level(i), _tmp.get_pyramid_level(i));
/* Configure vertical kernel */
- auto vertical_kernel = support::cpp14::make_unique<NEGaussianPyramidVertKernel>();
- vertical_kernel->configure(_tmp.get_pyramid_level(i), _pyramid->get_pyramid_level(i + 1));
+ _vertical_reduction[i].configure(_tmp.get_pyramid_level(i), _pyramid->get_pyramid_level(i + 1));
/* Configure border */
- auto horizontal_border_kernel = support::cpp14::make_unique<NEFillBorderKernel>();
- horizontal_border_kernel->configure(_pyramid->get_pyramid_level(i), horizontal_kernel->border_size(), border_mode, PixelValue(constant_border_value));
+ _horizontal_border_handler[i].configure(_pyramid->get_pyramid_level(i), _horizontal_reduction[i].border_size(), border_mode, PixelValue(constant_border_value));
/* Configure border */
- auto vertical_border_kernel = support::cpp14::make_unique<NEFillBorderKernel>();
- vertical_border_kernel->configure(_tmp.get_pyramid_level(i), vertical_kernel->border_size(), border_mode, PixelValue(pixel_value_u16));
-
- _vertical_border_handler.emplace_back(std::move(vertical_border_kernel));
- _horizontal_border_handler.emplace_back(std::move(horizontal_border_kernel));
- _vertical_reduction.emplace_back(std::move(vertical_kernel));
- _horizontal_reduction.emplace_back(std::move(horizontal_kernel));
+ _vertical_border_handler[i].configure(_tmp.get_pyramid_level(i), _vertical_reduction[i].border_size(), border_mode, PixelValue(pixel_value_u16));
}
_tmp.allocate();
@@ -119,17 +116,17 @@
ARM_COMPUTE_ERROR_ON_MSG(_pyramid == nullptr, "Unconfigured function");
/* Get number of pyramid levels */
- const size_t num_levels = _pyramid->info()->num_levels();
+ const unsigned int num_levels = _pyramid->info()->num_levels();
/* The first level of the pyramid has the input image */
_pyramid->get_pyramid_level(0)->copy_from(*_input);
for(unsigned int i = 0; i < num_levels - 1; ++i)
{
- NEScheduler::get().schedule(_horizontal_border_handler[i].get(), Window::DimZ);
- NEScheduler::get().schedule(_horizontal_reduction[i].get(), Window::DimY);
- NEScheduler::get().schedule(_vertical_border_handler[i].get(), Window::DimZ);
- NEScheduler::get().schedule(_vertical_reduction[i].get(), Window::DimY);
+ NEScheduler::get().schedule(&_horizontal_border_handler[i], Window::DimZ);
+ NEScheduler::get().schedule(&_horizontal_reduction[i], Window::DimY);
+ NEScheduler::get().schedule(&_vertical_border_handler[i], Window::DimZ);
+ NEScheduler::get().schedule(&_vertical_reduction[i], Window::DimY);
}
}
@@ -150,26 +147,29 @@
/* Get number of pyramid levels */
const size_t num_levels = pyramid->info()->num_levels();
+ const size_t num_stages = num_levels - 1;
_input = input;
_pyramid = pyramid;
+ _gaus5x5.clear();
+ _scale_nearest.clear();
+
+ _gaus5x5.resize(num_stages);
+ _scale_nearest.resize(num_stages);
+
if(num_levels > 1)
{
PyramidInfo pyramid_info(num_levels - 1, SCALE_PYRAMID_ORB, pyramid->info()->tensor_shape(), Format::U8);
_tmp.init(pyramid_info);
- for(unsigned int i = 0; i < num_levels - 1; ++i)
+ for(size_t i = 0; i < num_levels - 1; ++i)
{
/* Configure gaussian 5x5 */
- auto gaus5x5_kernel = support::cpp14::make_unique<NEGaussian5x5>();
- gaus5x5_kernel->configure(_pyramid->get_pyramid_level(i), _tmp.get_pyramid_level(i), border_mode, constant_border_value);
- _gaus5x5.emplace_back(std::move(gaus5x5_kernel));
+ _gaus5x5[i].configure(_pyramid->get_pyramid_level(i), _tmp.get_pyramid_level(i), border_mode, constant_border_value);
/* Configure scale */
- auto scale_kernel = support::cpp14::make_unique<NEScale>();
- scale_kernel->configure(_tmp.get_pyramid_level(i), _pyramid->get_pyramid_level(i + 1), InterpolationPolicy::NEAREST_NEIGHBOR, BorderMode::UNDEFINED);
- _scale_nearest.emplace_back(std::move(scale_kernel));
+ _scale_nearest[i].configure(_tmp.get_pyramid_level(i), _pyramid->get_pyramid_level(i + 1), InterpolationPolicy::NEAREST_NEIGHBOR, BorderMode::UNDEFINED);
}
_tmp.allocate();
@@ -188,7 +188,7 @@
for(unsigned int i = 0; i < num_levels - 1; ++i)
{
- _gaus5x5[i].get()->run();
- _scale_nearest[i].get()->run();
+ _gaus5x5[i].run();
+ _scale_nearest[i].run();
}
}
diff --git a/src/runtime/NEON/functions/NEHOGMultiDetection.cpp b/src/runtime/NEON/functions/NEHOGMultiDetection.cpp
index 26abc9d..4e61580 100644
--- a/src/runtime/NEON/functions/NEHOGMultiDetection.cpp
+++ b/src/runtime/NEON/functions/NEHOGMultiDetection.cpp
@@ -126,12 +126,18 @@
_num_block_norm_kernel = input_block_norm.size(); // Number of NEHOGBlockNormalizationKernel kernels to compute
_num_hog_detect_kernel = input_hog_detect.size(); // Number of NEHOGDetector functions to compute
- _orient_bin_kernel.reserve(_num_orient_bin_kernel);
- _block_norm_kernel.reserve(_num_block_norm_kernel);
- _hog_detect_kernel.reserve(_num_hog_detect_kernel);
- _hog_space.reserve(_num_orient_bin_kernel);
- _hog_norm_space.reserve(_num_block_norm_kernel);
- _non_maxima_kernel = arm_compute::support::cpp14::make_unique<CPPDetectionWindowNonMaximaSuppressionKernel>();
+ _orient_bin_kernel.clear();
+ _block_norm_kernel.clear();
+ _hog_detect_kernel.clear();
+ _hog_space.clear();
+ _hog_norm_space.clear();
+
+ _orient_bin_kernel.resize(_num_orient_bin_kernel);
+ _block_norm_kernel.resize(_num_block_norm_kernel);
+ _hog_detect_kernel.resize(_num_hog_detect_kernel);
+ _hog_space.resize(_num_orient_bin_kernel);
+ _hog_norm_space.resize(_num_block_norm_kernel);
+ _non_maxima_kernel = CPPDetectionWindowNonMaximaSuppressionKernel();
// Allocate tensors for magnitude and phase
TensorInfo info_mag(shape_img, Format::S16);
@@ -167,17 +173,13 @@
// Allocate HOG space
TensorInfo info_space(shape_hog_space, num_bins, DataType::F32);
- auto hog_space_tensor = support::cpp14::make_unique<Tensor>();
- hog_space_tensor->allocator()->init(info_space);
+ _hog_space[i].allocator()->init(info_space);
// Manage intermediate buffers
- _memory_group.manage(hog_space_tensor.get());
+ _memory_group.manage(&_hog_space[i]);
// Initialise orientation binning kernel
- auto orient_bin_kernel = support::cpp14::make_unique<NEHOGOrientationBinningKernel>();
- orient_bin_kernel->configure(&_mag, &_phase, hog_space_tensor.get(), multi_hog->model(idx_multi_hog)->info());
- _orient_bin_kernel.emplace_back(std::move(orient_bin_kernel));
- _hog_space.emplace_back(std::move(hog_space_tensor));
+ _orient_bin_kernel[i].configure(&_mag, &_phase, &_hog_space[i], multi_hog->model(idx_multi_hog)->info());
}
// Allocate intermediate tensors
@@ -192,23 +194,19 @@
// Allocate normalized HOG space
TensorInfo tensor_info(*(multi_hog->model(idx_multi_hog)->info()), width, height);
- auto hog_norm_space_tensor = support::cpp14::make_unique<Tensor>();
- hog_norm_space_tensor->allocator()->init(tensor_info);
+ _hog_norm_space[i].allocator()->init(tensor_info);
// Manage intermediate buffers
- _memory_group.manage(hog_norm_space_tensor.get());
+ _memory_group.manage(&_hog_norm_space[i]);
// Initialize block normalization kernel
- auto block_norm_kernel = support::cpp14::make_unique<NEHOGBlockNormalizationKernel>();
- block_norm_kernel->configure(_hog_space[idx_orient_bin].get(), hog_norm_space_tensor.get(), multi_hog->model(idx_multi_hog)->info());
- _block_norm_kernel.emplace_back(std::move(block_norm_kernel));
- _hog_norm_space.emplace_back(std::move(hog_norm_space_tensor));
+ _block_norm_kernel[i].configure(&_hog_space[idx_orient_bin], &_hog_norm_space[i], multi_hog->model(idx_multi_hog)->info());
}
// Allocate intermediate tensors
for(size_t i = 0; i < _num_orient_bin_kernel; ++i)
{
- _hog_space[i].get()->allocator()->allocate();
+ _hog_space[i].allocator()->allocate();
}
// Configure HOG detector kernel
@@ -216,18 +214,16 @@
{
const size_t idx_block_norm = input_hog_detect[i];
- auto hog_detect_kernel = support::cpp14::make_unique<NEHOGDetector>();
- hog_detect_kernel->configure(_hog_norm_space[idx_block_norm].get(), multi_hog->model(i), detection_windows, detection_window_strides->at(i), threshold, i);
- _hog_detect_kernel.emplace_back(std::move(hog_detect_kernel));
+ _hog_detect_kernel[i].configure(&_hog_norm_space[idx_block_norm], multi_hog->model(i), detection_windows, detection_window_strides->at(i), threshold, i);
}
// Configure non maxima suppression kernel
- _non_maxima_kernel->configure(_detection_windows, min_distance);
+ _non_maxima_kernel.configure(_detection_windows, min_distance);
// Allocate intermediate tensors
for(size_t i = 0; i < _num_block_norm_kernel; ++i)
{
- _hog_norm_space[i]->allocator()->allocate();
+ _hog_norm_space[i].allocator()->allocate();
}
}
@@ -246,24 +242,24 @@
// Run orientation binning kernel
for(auto &kernel : _orient_bin_kernel)
{
- NEScheduler::get().schedule(kernel.get(), Window::DimY);
+ NEScheduler::get().schedule(&kernel, Window::DimY);
}
// Run block normalization kernel
for(auto &kernel : _block_norm_kernel)
{
- NEScheduler::get().schedule(kernel.get(), Window::DimY);
+ NEScheduler::get().schedule(&kernel, Window::DimY);
}
// Run HOG detector kernel
for(auto &kernel : _hog_detect_kernel)
{
- kernel->run();
+ kernel.run();
}
// Run non-maxima suppression kernel if enabled
if(_non_maxima_suppression)
{
- NEScheduler::get().schedule(_non_maxima_kernel.get(), Window::DimY);
+ NEScheduler::get().schedule(&_non_maxima_kernel, Window::DimY);
}
}
diff --git a/src/runtime/NEON/functions/NEOpticalFlow.cpp b/src/runtime/NEON/functions/NEOpticalFlow.cpp
index 0df01c6..27dc3e0 100644
--- a/src/runtime/NEON/functions/NEOpticalFlow.cpp
+++ b/src/runtime/NEON/functions/NEOpticalFlow.cpp
@@ -74,10 +74,15 @@
const float pyr_scale = old_pyramid->info()->scale();
- _func_scharr.reserve(_num_levels);
- _kernel_tracker.reserve(_num_levels);
- _scharr_gx.reserve(_num_levels);
- _scharr_gy.reserve(_num_levels);
+ _func_scharr.clear();
+ _kernel_tracker.clear();
+ _scharr_gx.clear();
+ _scharr_gy.clear();
+
+ _func_scharr.resize(_num_levels);
+ _kernel_tracker.resize(_num_levels);
+ _scharr_gx.resize(_num_levels);
+ _scharr_gy.resize(_num_levels);
_old_points_internal = LKInternalKeypointArray(old_points->num_values());
_new_points_internal = LKInternalKeypointArray(old_points->num_values());
@@ -95,34 +100,25 @@
TensorInfo tensor_info(TensorShape(width_ith, height_ith), Format::S16);
- auto scharr_gx = support::cpp14::make_unique<Tensor>();
- auto scharr_gy = support::cpp14::make_unique<Tensor>();
- scharr_gx->allocator()->init(tensor_info);
- scharr_gy->allocator()->init(tensor_info);
+ _scharr_gx[i].allocator()->init(tensor_info);
+ _scharr_gy[i].allocator()->init(tensor_info);
// Manage intermediate buffers
- _memory_group.manage(scharr_gx.get());
- _memory_group.manage(scharr_gy.get());
+ _memory_group.manage(&_scharr_gx[i]);
+ _memory_group.manage(&_scharr_gy[i]);
// Init Scharr kernel
- auto func_scharr = support::cpp14::make_unique<NEScharr3x3>();
- func_scharr->configure(old_ith_input, scharr_gx.get(), scharr_gy.get(), border_mode, constant_border_value);
+ _func_scharr[i].configure(old_ith_input, &_scharr_gx[i], &_scharr_gy[i], border_mode, constant_border_value);
// Init Lucas-Kanade kernel
- auto kernel_tracker = support::cpp14::make_unique<NELKTrackerKernel>();
- kernel_tracker->configure(old_ith_input, new_ith_input, scharr_gx.get(), scharr_gy.get(),
- old_points, new_points_estimates, new_points,
- &_old_points_internal, &_new_points_internal,
- termination, use_initial_estimate, epsilon, num_iterations, window_dimension,
- i, _num_levels, pyr_scale);
+ _kernel_tracker[i].configure(old_ith_input, new_ith_input, &_scharr_gx[i], &_scharr_gy[i],
+ old_points, new_points_estimates, new_points,
+ &_old_points_internal, &_new_points_internal,
+ termination, use_initial_estimate, epsilon, num_iterations, window_dimension,
+ i, _num_levels, pyr_scale);
- scharr_gx->allocator()->allocate();
- scharr_gy->allocator()->allocate();
-
- _func_scharr.emplace_back(std::move(func_scharr));
- _kernel_tracker.emplace_back(std::move(kernel_tracker));
- _scharr_gx.emplace_back(std::move(scharr_gx));
- _scharr_gy.emplace_back(std::move(scharr_gy));
+ _scharr_gx[i].allocator()->allocate();
+ _scharr_gy[i].allocator()->allocate();
}
}
@@ -135,9 +131,9 @@
for(unsigned int level = _num_levels; level > 0; --level)
{
// Run Scharr kernel
- _func_scharr[level - 1].get()->run();
+ _func_scharr[level - 1].run();
// Run Lucas-Kanade kernel
- NEScheduler::get().schedule(_kernel_tracker[level - 1].get(), Window::DimX);
+ NEScheduler::get().schedule(&_kernel_tracker[level - 1], Window::DimX);
}
}