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path: root/src/core/CL/kernels/CLInstanceNormalizationLayerKernel.cpp
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Diffstat (limited to 'src/core/CL/kernels/CLInstanceNormalizationLayerKernel.cpp')
-rw-r--r--src/core/CL/kernels/CLInstanceNormalizationLayerKernel.cpp59
1 files changed, 39 insertions, 20 deletions
diff --git a/src/core/CL/kernels/CLInstanceNormalizationLayerKernel.cpp b/src/core/CL/kernels/CLInstanceNormalizationLayerKernel.cpp
index 323579dc3c..b13eb16556 100644
--- a/src/core/CL/kernels/CLInstanceNormalizationLayerKernel.cpp
+++ b/src/core/CL/kernels/CLInstanceNormalizationLayerKernel.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2019-2021 Arm Limited.
+ * Copyright (c) 2019-2021, 2023 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -29,6 +29,8 @@
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/Utils.h"
+#include "arm_compute/core/utils/StringUtils.h"
+
#include "src/core/CL/CLValidate.h"
#include "src/core/helpers/AutoConfiguration.h"
#include "src/core/helpers/WindowHelpers.h"
@@ -38,17 +40,20 @@ namespace arm_compute
{
namespace
{
-Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const InstanceNormalizationLayerKernelInfo &info)
+Status validate_arguments(const ITensorInfo *input,
+ const ITensorInfo *output,
+ const InstanceNormalizationLayerKernelInfo &info)
{
ARM_COMPUTE_RETURN_ERROR_ON_MSG(info.epsilon == 0.f, "Epsilon must be different than 0");
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN(input, DataType::F16, DataType::F32);
- if(output != nullptr && output->total_size() != 0)
+ if (output != nullptr && output->total_size() != 0)
{
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input, output);
- ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->num_channels() != output->num_channels(), "Input and output have different number of channels");
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->num_channels() != output->num_channels(),
+ "Input and output have different number of channels");
}
return Status{};
@@ -58,26 +63,30 @@ Status validate_arguments_meanvar(const ITensorInfo *input, const ITensorInfo *o
{
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN(input, DataType::F16, DataType::F32);
- if(output != nullptr && output->total_size() != 0)
+ if (output != nullptr && output->total_size() != 0)
{
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input, output);
- ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->num_channels() != output->num_channels(), "Input and output have different number of channels");
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->num_channels() != output->num_channels(),
+ "Input and output have different number of channels");
}
return Status{};
}
} // namespace
-CLComputeMeanVariance::CLComputeMeanVariance()
- : _input(nullptr), _output(nullptr)
+CLComputeMeanVariance::CLComputeMeanVariance() : _input(nullptr), _output(nullptr)
{
+ _type = CLKernelType::ELEMENTWISE;
}
-void CLComputeMeanVariance::configure(const CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output, bool use_mixed_precision)
+void CLComputeMeanVariance::configure(const CLCompileContext &compile_context,
+ ICLTensor *input,
+ ICLTensor *output,
+ bool use_mixed_precision)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input);
- auto padding_info = get_padding_info({ input, output });
+ auto padding_info = get_padding_info({input, output});
_input = input;
_output = output == nullptr ? input : output;
@@ -86,7 +95,8 @@ void CLComputeMeanVariance::configure(const CLCompileContext &compile_context, I
const unsigned int num_elems_processed_per_iteration = 16 / input->info()->element_size();
CLBuildOptions build_opts;
- build_opts.add_option("-DINTERNAL_DATA_TYPE=" + (use_mixed_precision ? "float" : get_cl_type_from_data_type(input->info()->data_type())));
+ build_opts.add_option("-DINTERNAL_DATA_TYPE=" +
+ (use_mixed_precision ? "float" : get_cl_type_from_data_type(input->info()->data_type())));
build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()));
build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration));
build_opts.add_option("-DDIM_X=" + support::cpp11::to_string(input->info()->dimension(0)));
@@ -106,7 +116,7 @@ void CLComputeMeanVariance::configure(const CLCompileContext &compile_context, I
const TensorShape out_shape(input_channel, 2u, input_batches);
// Output auto initialization if not yet initialized
- if(use_mixed_precision)
+ if (use_mixed_precision)
{
auto_init_if_empty(*_output->info(), out_shape, 1, DataType::F32);
}
@@ -132,7 +142,7 @@ void CLComputeMeanVariance::run(const Window &window, cl::CommandQueue &queue)
Window collapsed_window = window.collapse(window, Window::DimZ);
// We will process the planes together
- if(_input->info()->data_layout() == DataLayout::NCHW)
+ if (_input->info()->data_layout() == DataLayout::NCHW)
{
collapsed_window.set(Window::DimX, Window::Dimension(0, 1, 1));
collapsed_window.set(Window::DimY, Window::Dimension(0, 1, 1));
@@ -152,12 +162,17 @@ void CLComputeMeanVariance::run(const Window &window, cl::CommandQueue &queue)
CLInstanceNormalizationLayerKernel::CLInstanceNormalizationLayerKernel()
: _input(nullptr), _output(nullptr), _mean(nullptr), _run_in_place(false)
{
+ _type = CLKernelType::ELEMENTWISE;
}
-void CLInstanceNormalizationLayerKernel::configure(const CLCompileContext &compile_context, ICLTensor *input, ICLTensor *mean_var, ICLTensor *output, const InstanceNormalizationLayerKernelInfo &info)
+void CLInstanceNormalizationLayerKernel::configure(const CLCompileContext &compile_context,
+ ICLTensor *input,
+ ICLTensor *mean_var,
+ ICLTensor *output,
+ const InstanceNormalizationLayerKernelInfo &info)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input);
- auto padding_info = get_padding_info({ input, output });
+ auto padding_info = get_padding_info({input, output});
_input = input;
_output = output == nullptr ? input : output;
@@ -169,7 +184,9 @@ void CLInstanceNormalizationLayerKernel::configure(const CLCompileContext &compi
CLBuildOptions build_opts;
build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()));
- build_opts.add_option("-DINTERNAL_DATA_TYPE=" + (info.use_mixed_precision ? "float" : get_cl_type_from_data_type(input->info()->data_type())));
+ build_opts.add_option("-DINTERNAL_DATA_TYPE=" + (info.use_mixed_precision
+ ? "float"
+ : get_cl_type_from_data_type(input->info()->data_type())));
build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration));
build_opts.add_option("-DDIM_X=" + support::cpp11::to_string(input->info()->dimension(0)));
build_opts.add_option("-DDIM_Y=" + support::cpp11::to_string(input->info()->dimension(1)));
@@ -185,7 +202,7 @@ void CLInstanceNormalizationLayerKernel::configure(const CLCompileContext &compi
// Configure kernel window
Window win = calculate_max_window(*input->info(), Steps(1));
- if(output != nullptr)
+ if (output != nullptr)
{
auto_init_if_empty(*output->info(), input->info()->tensor_shape(), 1, input->info()->data_type());
}
@@ -194,7 +211,9 @@ void CLInstanceNormalizationLayerKernel::configure(const CLCompileContext &compi
ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info));
}
-Status CLInstanceNormalizationLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const InstanceNormalizationLayerKernelInfo &info)
+Status CLInstanceNormalizationLayerKernel::validate(const ITensorInfo *input,
+ const ITensorInfo *output,
+ const InstanceNormalizationLayerKernelInfo &info)
{
ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, info));
return Status{};
@@ -208,7 +227,7 @@ void CLInstanceNormalizationLayerKernel::run(const Window &window, cl::CommandQu
Window collapsed_window = window.collapse(window, Window::DimZ);
// We will process the planes together
- if(_input->info()->data_layout() == DataLayout::NCHW)
+ if (_input->info()->data_layout() == DataLayout::NCHW)
{
collapsed_window.set(Window::DimX, Window::Dimension(0, 1, 1));
collapsed_window.set(Window::DimY, Window::Dimension(0, 1, 1));
@@ -223,7 +242,7 @@ void CLInstanceNormalizationLayerKernel::run(const Window &window, cl::CommandQu
add_4D_tensor_argument(idx, _input, collapsed_window);
add_3D_tensor_argument(idx, _mean, collapsed_window);
- if(!_run_in_place)
+ if (!_run_in_place)
{
add_4D_tensor_argument(idx, _output, collapsed_window);
}
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-04 01:07:49 +0000