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/core/CL/kernels/CLComparisonKernel.cpp b/src/core/CL/kernels/CLComparisonKernel.cpp
index f4d6316..f272707 100644
--- a/src/core/CL/kernels/CLComparisonKernel.cpp
+++ b/src/core/CL/kernels/CLComparisonKernel.cpp
@@ -26,6 +26,7 @@
#include "arm_compute/core/CL/CLHelpers.h"
#include "arm_compute/core/CL/ICLTensor.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"
@@ -38,14 +39,10 @@
namespace
{
// Create supported comparisons map
-const std::map<ComparisonOperation, std::string> supported_comparison_ops =
-{
- { ComparisonOperation::Equal, "EQUAL" },
- { ComparisonOperation::NotEqual, "NOTEQUAL" },
- { ComparisonOperation::Greater, "GREATER" },
- { ComparisonOperation::GreaterEqual, "GREATEREQUAL" },
- { ComparisonOperation::Less, "LESS" },
- { ComparisonOperation::LessEqual, "LESSEQUAL" },
+const std::map<ComparisonOperation, std::string> supported_comparison_ops = {
+ {ComparisonOperation::Equal, "EQUAL"}, {ComparisonOperation::NotEqual, "NOTEQUAL"},
+ {ComparisonOperation::Greater, "GREATER"}, {ComparisonOperation::GreaterEqual, "GREATEREQUAL"},
+ {ComparisonOperation::Less, "LESS"}, {ComparisonOperation::LessEqual, "LESSEQUAL"},
};
int calculate_num_elems_processed_per_iteration(const ITensorInfo &input)
@@ -53,7 +50,10 @@
return 16 / input.element_size();
}
-Status validate_arguments(const ITensorInfo &input1, const ITensorInfo &input2, const ITensorInfo &output, ComparisonOperation operation)
+Status validate_arguments(const ITensorInfo &input1,
+ const ITensorInfo &input2,
+ const ITensorInfo &output,
+ ComparisonOperation operation)
{
ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(&input1);
ARM_COMPUTE_RETURN_ERROR_ON(input1.data_type() == DataType::UNKNOWN);
@@ -64,7 +64,7 @@
ARM_COMPUTE_RETURN_ERROR_ON_MSG(out_shape.total_size() == 0, "Inputs are not broadcast compatible");
// Validate in case of configured output
- if(output.total_size() > 0)
+ if (output.total_size() > 0)
{
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&output, 1, DataType::U8);
ARM_COMPUTE_RETURN_ERROR_ON_MSG(detail::have_different_dimensions(out_shape, output.tensor_shape(), 0),
@@ -76,7 +76,7 @@
std::pair<Status, Window> validate_and_configure_window(ITensorInfo &input1, ITensorInfo &input2, ITensorInfo &output)
{
- const TensorShape &out_shape = TensorShape::broadcast_shape(input1.tensor_shape(), input2.tensor_shape());
+ const TensorShape &out_shape = TensorShape::broadcast_shape(input1.tensor_shape(), input2.tensor_shape());
const unsigned int num_elems_processed_per_iteration = calculate_num_elems_processed_per_iteration(input1);
// Auto initialize output if not initialized
@@ -90,27 +90,34 @@
AccessWindowHorizontal input2_access(&input2, 0, num_elems_processed_per_iteration);
AccessWindowHorizontal output_access(&output, 0, num_elems_processed_per_iteration);
- bool window_changed = update_window_and_padding(win_input1, input1_access)
- || update_window_and_padding(win_input2, input2_access)
- || update_window_and_padding(win, output_access);
+ bool window_changed = update_window_and_padding(win_input1, input1_access) ||
+ update_window_and_padding(win_input2, input2_access) ||
+ update_window_and_padding(win, output_access);
- Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
+ Status err =
+ (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
return std::make_pair(err, win);
}
} // namespace
-CLComparisonKernel::CLComparisonKernel()
- : _input1(nullptr), _input2(nullptr), _output(nullptr)
+CLComparisonKernel::CLComparisonKernel() : _input1(nullptr), _input2(nullptr), _output(nullptr)
{
_type = CLKernelType::ELEMENTWISE;
}
-void CLComparisonKernel::configure(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, ComparisonOperation operation)
+void CLComparisonKernel::configure(const ICLTensor *input1,
+ const ICLTensor *input2,
+ ICLTensor *output,
+ ComparisonOperation operation)
{
configure(CLKernelLibrary::get().get_compile_context(), input1, input2, output, operation);
}
-void CLComparisonKernel::configure(const CLCompileContext &compile_context, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, ComparisonOperation operation)
+void CLComparisonKernel::configure(const CLCompileContext &compile_context,
+ const ICLTensor *input1,
+ const ICLTensor *input2,
+ ICLTensor *output,
+ ComparisonOperation operation)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output);
ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(*input1->info(), *input2->info(), *output->info(), operation));
@@ -129,10 +136,11 @@
// Set kernel build options
std::set<std::string> build_opts;
build_opts.emplace("-DDATA_TYPE=" + get_cl_type_from_data_type(input1->info()->data_type()));
- build_opts.emplace("-DVEC_SIZE=" + support::cpp11::to_string(calculate_num_elems_processed_per_iteration(*input1->info())));
+ build_opts.emplace("-DVEC_SIZE=" +
+ support::cpp11::to_string(calculate_num_elems_processed_per_iteration(*input1->info())));
build_opts.emplace("-DOP=" + operation_name);
build_opts.emplace("-DOP_NAME=" + lower_string(operation_name));
- if(is_data_type_quantized(input1->info()->data_type()))
+ if (is_data_type_quantized(input1->info()->data_type()))
{
const UniformQuantizationInfo iq1_info = input1->info()->quantization_info().uniform();
const UniformQuantizationInfo iq2_info = input2->info()->quantization_info().uniform();
@@ -160,12 +168,16 @@
_config_id += lower_string(string_from_data_layout(input1->info()->data_layout()));
}
-Status CLComparisonKernel::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, ComparisonOperation operation)
+Status CLComparisonKernel::validate(const ITensorInfo *input1,
+ const ITensorInfo *input2,
+ const ITensorInfo *output,
+ ComparisonOperation operation)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input1, input2, output);
ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(*input1, *input2, *output, operation));
- ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(*input1->clone(), *input2->clone(), *output->clone()).first);
+ ARM_COMPUTE_RETURN_ON_ERROR(
+ validate_and_configure_window(*input1->clone(), *input2->clone(), *output->clone()).first);
return Status{};
}
@@ -181,17 +193,18 @@
bool can_collapse = true;
const bool is_vector = in_shape1.num_dimensions() == 1 || in_shape2.num_dimensions() == 1;
- if(std::min(in_shape1.total_size(), in_shape2.total_size()) > 1 && !is_vector)
+ if (std::min(in_shape1.total_size(), in_shape2.total_size()) > 1 && !is_vector)
{
can_collapse = (std::min(in_shape1.num_dimensions(), in_shape2.num_dimensions()) > Window::DimZ);
- for(size_t d = Window::DimZ; can_collapse && (d < out_shape.num_dimensions()); d++)
+ for (size_t d = Window::DimZ; can_collapse && (d < out_shape.num_dimensions()); d++)
{
can_collapse = (in_shape1[d] == in_shape2[d]);
}
}
bool has_collapsed = false;
- Window collapsed = can_collapse ? window.collapse_if_possible(ICLKernel::window(), Window::DimZ, &has_collapsed) : window;
+ Window collapsed =
+ can_collapse ? window.collapse_if_possible(ICLKernel::window(), Window::DimZ, &has_collapsed) : window;
const TensorShape &in_shape1_collapsed = has_collapsed ? in_shape1.collapsed_from(Window::DimZ) : in_shape1;
const TensorShape &in_shape2_collapsed = has_collapsed ? in_shape2.collapsed_from(Window::DimZ) : in_shape2;
@@ -212,16 +225,16 @@
ARM_COMPUTE_UNUSED(collapsed.slide_window_slice_3D(slice_input1));
ARM_COMPUTE_UNUSED(collapsed.slide_window_slice_3D(slice_input2));
- }
- while(collapsed.slide_window_slice_3D(slice));
+ } while (collapsed.slide_window_slice_3D(slice));
}
BorderSize CLComparisonKernel::border_size() const
{
const int num_elems_processed_per_iteration = calculate_num_elems_processed_per_iteration(*_input1->info());
- const unsigned int replicateSize = _output->info()->dimension(0) - std::min(_input1->info()->dimension(0), _input2->info()->dimension(0));
- const unsigned int border = std::min<unsigned int>(num_elems_processed_per_iteration - 1U, replicateSize);
- return BorderSize{ 0, border, 0, 0 };
+ const unsigned int replicateSize =
+ _output->info()->dimension(0) - std::min(_input1->info()->dimension(0), _input2->info()->dimension(0));
+ const unsigned int border = std::min<unsigned int>(num_elems_processed_per_iteration - 1U, replicateSize);
+ return BorderSize{0, border, 0, 0};
}
} // namespace arm_compute