COMPMID-1330: Add support for NormalizePlanarYUV operator in CL
Change-Id: Id0754b9e2bc3ef7ff2c4c21c3b89709588c41bd3
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/146637
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Reviewed-by: Giorgio Arena <giorgio.arena@arm.com>
diff --git a/src/core/GLES_COMPUTE/kernels/GCNormalizePlanarYUVLayerKernel.cpp b/src/core/GLES_COMPUTE/kernels/GCNormalizePlanarYUVLayerKernel.cpp
index fac2902..03463b2 100644
--- a/src/core/GLES_COMPUTE/kernels/GCNormalizePlanarYUVLayerKernel.cpp
+++ b/src/core/GLES_COMPUTE/kernels/GCNormalizePlanarYUVLayerKernel.cpp
@@ -36,26 +36,75 @@
using namespace arm_compute;
+namespace
+{
+Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const ITensorInfo *mean, const ITensorInfo *std)
+{
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16);
+ ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output);
+ ARM_COMPUTE_RETURN_ERROR_ON(input->data_layout() != DataLayout::NCHW);
+
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, mean, std);
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(mean, std);
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(mean->num_dimensions() > 1, "mean and std must be vectors");
+
+ const unsigned int channel_idx = get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::CHANNEL);
+ ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(channel_idx) != mean->dimension(0));
+
+ // Checks performed when output is configured
+ if(output->total_size() != 0)
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output);
+ }
+
+ return Status{};
+}
+
+std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output, ITensorInfo *mean, ITensorInfo *std)
+{
+ // Output tensor auto initialization if not yet initialized
+ auto_init_if_empty(*output, *input->clone());
+
+ const unsigned int num_elems_processed_per_iteration = 4;
+
+ // Configure kernel window
+ Window win = calculate_max_window(*input, Steps(num_elems_processed_per_iteration));
+
+ AccessWindowHorizontal input_access(input, 0, num_elems_processed_per_iteration);
+ AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration);
+ const int mean_padding = ceil_to_multiple(mean->dimension(0), num_elems_processed_per_iteration) - mean->dimension(0);
+ const int std_padding = ceil_to_multiple(std->dimension(0), num_elems_processed_per_iteration) - std->dimension(0);
+ AccessWindowStatic mean_access(mean, 0, 0, mean->dimension(0) + mean_padding, mean->dimension(1));
+ AccessWindowStatic std_access(std, 0, 0, std->dimension(0) + std_padding, std->dimension(1));
+
+ const bool window_changed = update_window_and_padding(win, input_access, output_access, mean_access, std_access);
+ output_access.set_valid_region(win, input->valid_region());
+
+ Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
+ return std::make_pair(err, win);
+}
+} // namespace
+
GCNormalizePlanarYUVLayerKernel::GCNormalizePlanarYUVLayerKernel()
- : _input(nullptr), _output(nullptr), _mean(nullptr), _sd(nullptr)
+ : _input(nullptr), _output(nullptr), _mean(nullptr), _std(nullptr)
{
}
-void GCNormalizePlanarYUVLayerKernel::configure(const IGCTensor *input, IGCTensor *output, const IGCTensor *mean, const IGCTensor *sd)
+void GCNormalizePlanarYUVLayerKernel::configure(const IGCTensor *input, IGCTensor *output, const IGCTensor *mean, const IGCTensor *std)
{
- ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16);
- ARM_COMPUTE_ERROR_ON_NULLPTR(output);
- ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output, mean, sd);
- ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(input, output);
- ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(mean, sd);
- ARM_COMPUTE_ERROR_ON(input->info()->dimension(2) != mean->info()->dimension(0));
+ ARM_COMPUTE_ERROR_ON_NULLPTR(input, output, mean, std);
+
+ // Output tensor auto initialization if not yet initialized
+ auto_init_if_empty(*output->info(), *input->info()->clone());
+
+ // Perform validation step
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), mean->info(), std->info()));
_input = input;
_output = output;
_mean = mean;
- _sd = sd;
-
- const unsigned int num_elems_processed_per_iteration = 4;
+ _std = std;
// Set build options
std::set<std::string> build_opts;
@@ -67,19 +116,17 @@
_kernel = static_cast<GCKernel>(GCKernelLibrary::get().create_kernel("normalize_planar_yuv_layer", build_opts));
// Configure kernel window
- Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration));
+ auto win_config = validate_and_configure_window(input->info(), output->info(), mean->info(), std->info());
+ ARM_COMPUTE_ERROR_THROW_ON(std::get<0>(win_config));
- AccessWindowHorizontal input_access(input->info(), 0, num_elems_processed_per_iteration);
- AccessWindowHorizontal output_access(output->info(), 0, num_elems_processed_per_iteration);
- const int mean_padding = ceil_to_multiple(mean->info()->dimension(0), num_elems_processed_per_iteration) - mean->info()->dimension(0);
- const int sd_padding = ceil_to_multiple(sd->info()->dimension(0), num_elems_processed_per_iteration) - sd->info()->dimension(0);
- AccessWindowStatic mean_access(mean->info(), 0, 0, mean->info()->dimension(0) + mean_padding, mean->info()->dimension(1));
- AccessWindowStatic sd_access(sd->info(), 0, 0, sd->info()->dimension(0) + sd_padding, sd->info()->dimension(1));
+ IGCKernel::configure(std::get<1>(win_config));
+}
- update_window_and_padding(win, input_access, output_access, mean_access, sd_access);
- output_access.set_valid_region(win, input->info()->valid_region());
-
- IGCKernel::configure(win);
+Status GCNormalizePlanarYUVLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const ITensorInfo *mean, const ITensorInfo *std)
+{
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, mean, std));
+ ARM_COMPUTE_RETURN_ON_ERROR(std::get<0>(validate_and_configure_window(input->clone().get(), output->clone().get(), mean->clone().get(), std->clone().get())));
+ return Status{};
}
void GCNormalizePlanarYUVLayerKernel::run(const Window &window)
@@ -100,7 +147,7 @@
unsigned int idx = 2 * num_arguments_per_3D_tensor();
add_1D_tensor_argument(idx, _mean, 3, slice_in);
- add_1D_tensor_argument(idx, _sd, 4, slice_in);
+ add_1D_tensor_argument(idx, _std, 4, slice_in);
slice_in = window.first_slice_window_3D();