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/gpu/cl/kernels/ClGemmMatrixMultiplyReshapedKernel.cpp b/src/gpu/cl/kernels/ClGemmMatrixMultiplyReshapedKernel.cpp
index d72d29e..4fe6bdd 100644
--- a/src/gpu/cl/kernels/ClGemmMatrixMultiplyReshapedKernel.cpp
+++ b/src/gpu/cl/kernels/ClGemmMatrixMultiplyReshapedKernel.cpp
@@ -29,10 +29,11 @@
#include "arm_compute/core/CL/OpenCL.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/TensorInfo.h"
-#include "arm_compute/core/Validate.h"
#include "arm_compute/core/utils/ActivationFunctionUtils.h"
-#include "arm_compute/core/utils/StringUtils.h"
#include "arm_compute/core/utils/misc/ShapeCalculator.h"
+#include "arm_compute/core/utils/StringUtils.h"
+#include "arm_compute/core/Validate.h"
+
#include "src/core/CL/CLUtils.h"
#include "src/core/CL/CLValidate.h"
#include "src/core/helpers/AutoConfiguration.h"
@@ -52,7 +53,13 @@
{
using ElementsProcessed = Steps;
-Status validate_arguments(const ITensorInfo *src0, const ITensorInfo *src1, const ITensorInfo *src2, const ITensorInfo *dst, float alpha, float beta, const GEMMLHSMatrixInfo &lhs_info,
+Status validate_arguments(const ITensorInfo *src0,
+ const ITensorInfo *src1,
+ const ITensorInfo *src2,
+ const ITensorInfo *dst,
+ float alpha,
+ float beta,
+ const GEMMLHSMatrixInfo &lhs_info,
const GEMMRHSMatrixInfo &rhs_info,
const GEMMKernelInfo &gemm_info)
{
@@ -61,42 +68,50 @@
ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(src0);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(src0, 1, DataType::F16, DataType::F32);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src0, src1);
- ARM_COMPUTE_RETURN_ERROR_ON_MSG(src0->num_dimensions() > 4, "The number of dimensions for the LHS matrix must be <= 4");
- ARM_COMPUTE_RETURN_ERROR_ON_MSG(src1->num_dimensions() > 3, "The number of dimensions for the RHS matrix must be <= 3");
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(src0->num_dimensions() > 4,
+ "The number of dimensions for the LHS matrix must be <= 4");
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(src1->num_dimensions() > 3,
+ "The number of dimensions for the RHS matrix must be <= 3");
ARM_COMPUTE_RETURN_ERROR_ON(lhs_info.k0 != rhs_info.k0);
ARM_COMPUTE_RETURN_ERROR_ON(lhs_info.transpose == rhs_info.transpose);
- ARM_COMPUTE_RETURN_ERROR_ON_MSG(((lhs_info.k0 & (lhs_info.k0 - 1)) && lhs_info.k0 != 3), "Only 2,3,4,8,16 are supported for k0");
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(((lhs_info.k0 & (lhs_info.k0 - 1)) && lhs_info.k0 != 3),
+ "Only 2,3,4,8,16 are supported for k0");
ARM_COMPUTE_RETURN_ERROR_ON(lhs_info.k0 > 16);
ARM_COMPUTE_RETURN_ERROR_ON(lhs_info.m0 < 2 || lhs_info.m0 > 8);
- ARM_COMPUTE_RETURN_ERROR_ON_MSG((lhs_info.transpose) && ((lhs_info.m0 & (lhs_info.m0 - 1)) && lhs_info.m0 != 3), "Only 2,3,4,8,16 are supported for m0");
- ARM_COMPUTE_RETURN_ERROR_ON_MSG((rhs_info.transpose) && ((rhs_info.n0 & (rhs_info.n0 - 1)) && rhs_info.n0 != 3), "Only 2,3,4,8,16 are supported for n0");
- ARM_COMPUTE_RETURN_ERROR_ON_MSG((gemm_info.reinterpret_input_as_3d || gemm_info.depth_output_gemm3d != 0) && (src2 != nullptr)
- && (!gemm_info.broadcast_bias),
- "Bias addition only supported with broadcast mode in case the input or dst has to be reinterpreted as 3D");
- ARM_COMPUTE_RETURN_ERROR_ON_MSG(gemm_info.fp_mixed_precision && (src0->data_type() == DataType::F32), "Mixed precision only supported for F16 data type");
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG((lhs_info.transpose) && ((lhs_info.m0 & (lhs_info.m0 - 1)) && lhs_info.m0 != 3),
+ "Only 2,3,4,8,16 are supported for m0");
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG((rhs_info.transpose) && ((rhs_info.n0 & (rhs_info.n0 - 1)) && rhs_info.n0 != 3),
+ "Only 2,3,4,8,16 are supported for n0");
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(
+ (gemm_info.reinterpret_input_as_3d || gemm_info.depth_output_gemm3d != 0) && (src2 != nullptr) &&
+ (!gemm_info.broadcast_bias),
+ "Bias addition only supported with broadcast mode in case the input or dst has to be reinterpreted as 3D");
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(gemm_info.fp_mixed_precision && (src0->data_type() == DataType::F32),
+ "Mixed precision only supported for F16 data type");
ARM_COMPUTE_RETURN_ON_ERROR(gemm::validate_image2d_support_on_rhs(*src1, rhs_info));
const unsigned int m = gemm_info.m;
const unsigned int n = gemm_info.n;
const unsigned int k = gemm_info.k;
- TensorShape tensor_shape0{ src0->tensor_shape() };
+ TensorShape tensor_shape0{src0->tensor_shape()};
tensor_shape0.set(0, k);
tensor_shape0.set(1, m);
- TensorShape tensor_shape1{ src1->tensor_shape() };
+ TensorShape tensor_shape1{src1->tensor_shape()};
tensor_shape1.set(0, n);
tensor_shape1.set(1, k);
- if(src2 != nullptr && !(helpers::float_ops::is_zero(beta)))
+ if (src2 != nullptr && !(helpers::float_ops::is_zero(beta)))
{
const unsigned int src2_dim0 = src2->dimension(0);
const unsigned int src2_dim1 = src2->dimension(1);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src2, src1);
- if(gemm_info.broadcast_bias)
+ if (gemm_info.broadcast_bias)
{
- ARM_COMPUTE_RETURN_ERROR_ON_MSG((src2_dim1 != 1 || src2_dim0 != n), "Incorrect dimension of bias matrix which is to be broadcasted");
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG((src2_dim1 != 1 || src2_dim0 != n),
+ "Incorrect dimension of bias matrix which is to be broadcasted");
}
else
{
@@ -107,15 +122,18 @@
const TensorInfo tensor_info0 = src0->clone()->set_tensor_shape(tensor_shape0);
const TensorInfo tensor_info1 = src1->clone()->set_tensor_shape(tensor_shape1);
- const TensorInfo tensor_info_reshaped0 = src0->clone()->set_tensor_shape(misc::shape_calculator::compute_lhs_reshaped_shape(tensor_info0, lhs_info));
- const TensorInfo tensor_info_reshaped1 = src1->clone()->set_tensor_shape(misc::shape_calculator::compute_rhs_reshaped_shape(tensor_info1, rhs_info));
+ const TensorInfo tensor_info_reshaped0 =
+ src0->clone()->set_tensor_shape(misc::shape_calculator::compute_lhs_reshaped_shape(tensor_info0, lhs_info));
+ const TensorInfo tensor_info_reshaped1 =
+ src1->clone()->set_tensor_shape(misc::shape_calculator::compute_rhs_reshaped_shape(tensor_info1, rhs_info));
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(src0, &tensor_info_reshaped0);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(src1, &tensor_info_reshaped1);
- if(dst->total_size() != 0)
+ if (dst->total_size() != 0)
{
- const TensorInfo tensor_info_dst = dst->clone()->set_tensor_shape(misc::shape_calculator::compute_mm_shape(*src0, *src1, gemm_info));
+ const TensorInfo tensor_info_dst =
+ dst->clone()->set_tensor_shape(misc::shape_calculator::compute_mm_shape(*src0, *src1, gemm_info));
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(dst, &tensor_info_dst);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src0, dst);
}
@@ -123,9 +141,14 @@
return Status{};
}
-std::pair<Status, Window> validate_and_configure_window(ITensorInfo *src0, ITensorInfo *src1, ITensorInfo *src2, ITensorInfo *dst, const GEMMLHSMatrixInfo &lhs_info,
+std::pair<Status, Window> validate_and_configure_window(ITensorInfo *src0,
+ ITensorInfo *src1,
+ ITensorInfo *src2,
+ ITensorInfo *dst,
+ const GEMMLHSMatrixInfo &lhs_info,
const GEMMRHSMatrixInfo &rhs_info,
- const GEMMKernelInfo &gemm_info, ElementsProcessed &num_elements_processed)
+ const GEMMKernelInfo &gemm_info,
+ ElementsProcessed &num_elements_processed)
{
ARM_COMPUTE_UNUSED(src0, src1, src2);
unsigned int &num_elems_processed_per_iteration_x = num_elements_processed[0];
@@ -134,7 +157,7 @@
TensorInfo tmp_info(*dst);
- if(reinterpret_output_as_3d)
+ if (reinterpret_output_as_3d)
{
// Since the dst tensor has to be reinterpreted as 3D and the execute window is based on a 2D GEMM,
// the window needs to be constructed on the 2D collapsed version of the tensor
@@ -147,7 +170,8 @@
num_elems_processed_per_iteration_x = rhs_info.n0;
num_elems_processed_per_iteration_y = lhs_info.m0;
- Window win = calculate_max_window(tmp_info, Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y));
+ Window win =
+ calculate_max_window(tmp_info, Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y));
// Collapse along the Z direction
// This collapse needs to be here in order to tune the Z dimension of LWS
@@ -164,18 +188,26 @@
_type = CLKernelType::GEMM;
}
-void ClGemmMatrixMultiplyReshapedKernel::configure(const CLCompileContext &compile_context,
- const ITensorInfo *src0, const ITensorInfo *src1, const ITensorInfo *src2, ITensorInfo *dst, float alpha, float beta,
- const GEMMLHSMatrixInfo &lhs_info, const GEMMRHSMatrixInfo &rhs_info, const GEMMKernelInfo &gemm_info)
+void ClGemmMatrixMultiplyReshapedKernel::configure(const CLCompileContext &compile_context,
+ const ITensorInfo *src0,
+ const ITensorInfo *src1,
+ const ITensorInfo *src2,
+ ITensorInfo *dst,
+ float alpha,
+ float beta,
+ const GEMMLHSMatrixInfo &lhs_info,
+ const GEMMRHSMatrixInfo &rhs_info,
+ const GEMMKernelInfo &gemm_info)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(src0, src1, dst);
// dst tensor auto initialization if not yet initialized
- auto_init_if_empty(*dst, src0->clone()->set_tensor_shape(misc::shape_calculator::compute_mm_shape(*src0, *src1, gemm_info)));
+ auto_init_if_empty(
+ *dst, src0->clone()->set_tensor_shape(misc::shape_calculator::compute_mm_shape(*src0, *src1, gemm_info)));
ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(src0, src1, src2, dst, alpha, beta, lhs_info, rhs_info, gemm_info));
- auto padding_info = get_padding_info({ src0, src1, src2, dst });
+ auto padding_info = get_padding_info({src0, src1, src2, dst});
_reinterpret_output_as_3d = gemm_info.depth_output_gemm3d != 0;
_use_dummy_work_items = preferred_dummy_work_items_support(CLKernelLibrary::get().get_device());
_add_bias = src2 != nullptr;
@@ -188,14 +220,9 @@
ElementsProcessed num_elements_processed{};
// Configure kernel window
- auto win_config = validate_and_configure_window(src0->clone().get(),
- src1->clone().get(),
- (src2 != nullptr) ? src2->clone().get() : nullptr,
- dst->clone().get(),
- lhs_info,
- rhs_info,
- gemm_info,
- num_elements_processed);
+ auto win_config = validate_and_configure_window(
+ src0->clone().get(), src1->clone().get(), (src2 != nullptr) ? src2->clone().get() : nullptr, dst->clone().get(),
+ lhs_info, rhs_info, gemm_info, num_elements_processed);
ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
ICLKernel::configure_internal(win_config.second);
@@ -213,12 +240,15 @@
// Create build options
CLBuildOptions build_opts;
- build_opts.add_option_if(!(helpers::float_ops::is_one(alpha)), "-DALPHA=" + float_to_string_with_full_precision(alpha));
+ build_opts.add_option_if(!(helpers::float_ops::is_one(alpha)),
+ "-DALPHA=" + float_to_string_with_full_precision(alpha));
build_opts.add_option_if(src2 != nullptr, "-DBETA=" + float_to_string_with_full_precision(beta));
build_opts.add_option_if(helpers::float_ops::is_one(beta), "-DUNIT_BETA");
build_opts.add_option_if(_reinterpret_output_as_3d, "-DREINTERPRET_OUTPUT_AS_3D");
- build_opts.add_option_if(_reinterpret_output_as_3d, "-DHEIGHT_GEMM3D=" + support::cpp11::to_string(dst->dimension(1)));
- build_opts.add_option_if(_reinterpret_output_as_3d, "-DDEPTH_GEMM3D=" + support::cpp11::to_string(dst->dimension(2)));
+ build_opts.add_option_if(_reinterpret_output_as_3d,
+ "-DHEIGHT_GEMM3D=" + support::cpp11::to_string(dst->dimension(1)));
+ build_opts.add_option_if(_reinterpret_output_as_3d,
+ "-DDEPTH_GEMM3D=" + support::cpp11::to_string(dst->dimension(2)));
build_opts.add_option_if(gemm_info.broadcast_bias, "-DBROADCAST_BIAS");
build_opts.add_option_if(!_slide_matrix_b, "-DMATRIX_B_DEPTH=" + support::cpp11::to_string(src1->dimension(2)));
build_opts.add_option_if(lhs_info.interleave, "-DLHS_INTERLEAVE");
@@ -229,7 +259,9 @@
build_opts.add_option_if(rhs_info.export_to_cl_image, "-DOPENCL_IMAGE_SUPPORT");
build_opts.add_option("-DRHS_HEIGHT=" + support::cpp11::to_string(src1->dimension(1)));
build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(data_type));
- build_opts.add_option("-DDATA_TYPE_ACCUMULATOR=" + (enable_mixed_precision ? get_cl_type_from_data_type(DataType::F32) : get_cl_type_from_data_type(data_type)));
+ build_opts.add_option("-DDATA_TYPE_ACCUMULATOR=" + (enable_mixed_precision
+ ? get_cl_type_from_data_type(DataType::F32)
+ : get_cl_type_from_data_type(data_type)));
build_opts.add_option("-DM0=" + support::cpp11::to_string(lhs_info.m0));
build_opts.add_option("-DN0=" + support::cpp11::to_string(rhs_info.n0));
build_opts.add_option("-DK0=" + support::cpp11::to_string(lhs_info.k0));
@@ -237,9 +269,13 @@
build_opts.add_option("-DH0=" + support::cpp11::to_string(rhs_info.h0));
build_opts.add_option("-DPARTIAL_STORE_M0=" + support::cpp11::to_string(partial_store_m0));
build_opts.add_option("-DPARTIAL_STORE_N0=" + support::cpp11::to_string(partial_store_n0));
- build_opts.add_option_if(gemm_info.activation_info.enabled(), "-DACTIVATION_TYPE=" + lower_string(string_from_activation_func(gemm_info.activation_info.activation())));
- build_opts.add_option_if(gemm_info.activation_info.enabled(), "-DA_VAL=" + float_to_string_with_full_precision(gemm_info.activation_info.a()));
- build_opts.add_option_if(gemm_info.activation_info.enabled(), "-DB_VAL=" + float_to_string_with_full_precision(gemm_info.activation_info.b()));
+ build_opts.add_option_if(gemm_info.activation_info.enabled(),
+ "-DACTIVATION_TYPE=" +
+ lower_string(string_from_activation_func(gemm_info.activation_info.activation())));
+ build_opts.add_option_if(gemm_info.activation_info.enabled(),
+ "-DA_VAL=" + float_to_string_with_full_precision(gemm_info.activation_info.a()));
+ build_opts.add_option_if(gemm_info.activation_info.enabled(),
+ "-DB_VAL=" + float_to_string_with_full_precision(gemm_info.activation_info.b()));
std::string kernel_name("gemm_mm_reshaped_");
kernel_name += lhs_info.transpose ? "lhs_t_" : "lhs_nt_";
@@ -287,9 +323,15 @@
ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info));
}
-Status ClGemmMatrixMultiplyReshapedKernel::validate(const ITensorInfo *src0, const ITensorInfo *src1, const ITensorInfo *src2, const ITensorInfo *dst, float alpha, float beta,
+Status ClGemmMatrixMultiplyReshapedKernel::validate(const ITensorInfo *src0,
+ const ITensorInfo *src1,
+ const ITensorInfo *src2,
+ const ITensorInfo *dst,
+ float alpha,
+ float beta,
const GEMMLHSMatrixInfo &lhs_info,
- const GEMMRHSMatrixInfo &rhs_info, const GEMMKernelInfo &gemm_info)
+ const GEMMRHSMatrixInfo &rhs_info,
+ const GEMMKernelInfo &gemm_info)
{
ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(src0, src1, src2, dst, alpha, beta, lhs_info, rhs_info, gemm_info));
return Status{};
@@ -300,15 +342,18 @@
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window);
- const auto src0 = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_0));
- const auto src1 = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_1));
- const auto src2 = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_2));
- auto dst = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_DST));
+ const auto src0 =
+ utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_0));
+ const auto src1 =
+ utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_1));
+ const auto src2 =
+ utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_2));
+ auto dst = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_DST));
ARM_COMPUTE_ERROR_ON_NULLPTR(src0, src1, dst);
ARM_COMPUTE_ERROR_ON(_add_bias && src2 == nullptr);
- if(src1->info()->num_dimensions() < 3)
+ if (src1->info()->num_dimensions() < 3)
{
// The stride_z for matrix B must be zero if we do not slice
ARM_COMPUTE_ERROR_ON(src1->info()->strides_in_bytes()[3] != 0);
@@ -324,12 +369,14 @@
cl::Image2D src1_image2d;
- if(_export_to_cl_image)
+ if (_export_to_cl_image)
{
- const TensorShape shape2d(src1->info()->dimension(0) / 4, src1->info()->dimension(1) * src1->info()->dimension(2));
+ const TensorShape shape2d(src1->info()->dimension(0) / 4,
+ src1->info()->dimension(1) * src1->info()->dimension(2));
const size_t image_row_pitch = src1->info()->strides_in_bytes()[1];
- src1_image2d = create_image2d_from_buffer(CLKernelLibrary::get().context(), src1->cl_buffer(), shape2d, src1->info()->data_type(), image_row_pitch, CLImage2DType::ReadOnly);
+ src1_image2d = create_image2d_from_buffer(CLKernelLibrary::get().context(), src1->cl_buffer(), shape2d,
+ src1->info()->data_type(), image_row_pitch, CLImage2DType::ReadOnly);
}
do
@@ -337,7 +384,7 @@
Window slice_b = slice;
// Don't slice matrix B along the z dimension if matrix B has just 2 dimensions and matrix A more than 2
// This scenario can happen when the matrix multiplication is used to perform a convolution operation
- if(!_slide_matrix_b)
+ if (!_slide_matrix_b)
{
slice_b = slice_matrix_b;
}
@@ -348,7 +395,7 @@
add_2D_tensor_argument(idx, src0, slice);
// RHS buffer or RHS OpenCL image (_export_to_cl_image == true)
- if(_export_to_cl_image)
+ if (_export_to_cl_image)
{
_kernel.setArg(idx++, src1_image2d);
}
@@ -370,7 +417,7 @@
_kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(src1->info()->strides_in_bytes()[2]));
// Bias stride_z (if _add_bias == true)
- if(_add_bias)
+ if (_add_bias)
{
_kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(src2->info()->strides_in_bytes()[2]));
}
@@ -379,7 +426,7 @@
_kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(dst->info()->strides_in_bytes()[2]));
// Cross-plan padding (if _reinterpret_output_as_3d = true)
- if(_reinterpret_output_as_3d)
+ if (_reinterpret_output_as_3d)
{
_kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(total_cross_plane_pad));
}
@@ -393,8 +440,7 @@
// Dispatch kernel
enqueue(queue, *this, slice, lws_hint(), _use_dummy_work_items);
- }
- while(window.slide_window_slice_3D(slice));
+ } while (window.slide_window_slice_3D(slice));
}
} // namespace kernels
} // namespace opencl