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/cpu/kernels/CpuAddMulAddKernel.cpp b/src/cpu/kernels/CpuAddMulAddKernel.cpp
index b84bdd5..6a632e8 100644
--- a/src/cpu/kernels/CpuAddMulAddKernel.cpp
+++ b/src/cpu/kernels/CpuAddMulAddKernel.cpp
@@ -27,8 +27,8 @@
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/Validate.h"
-#include "src/core/CPP/Validate.h"
#include "src/core/common/Registrars.h"
+#include "src/core/CPP/Validate.h"
#include "src/core/helpers/AutoConfiguration.h"
#include "src/core/helpers/WindowHelpers.h"
#include "src/cpu/kernels/addmuladd/list.h"
@@ -41,36 +41,28 @@
{
namespace
{
-static const std::vector<CpuAddMulAddKernel::AddMulAddKernel> available_kernels =
-{
+static const std::vector<CpuAddMulAddKernel::AddMulAddKernel> available_kernels = {
#ifdef __aarch64__
- {
- "neon_fp32_add_mul_add",
- [](const DataTypeISASelectorData & data) { return (data.dt == DataType::F32); },
- REGISTER_FP32_NEON(arm_compute::cpu::add_mul_add_fp32_neon)
- },
- {
- "neon_fp16_add_mul_add",
- [](const DataTypeISASelectorData & data) { return (data.dt == DataType::F16); },
- REGISTER_FP16_NEON(arm_compute::cpu::add_mul_add_fp16_neon)
- },
- {
- "neon_qasymm8_add_mul_add",
- [](const DataTypeISASelectorData & data) { return (data.dt == DataType::QASYMM8); },
- REGISTER_QASYMM8_NEON(arm_compute::cpu::add_mul_add_u8_neon)
- },
- {
- "neon_qasymm8_signed_add_mul_add",
- [](const DataTypeISASelectorData & data) { return (data.dt == DataType::QASYMM8_SIGNED); },
- REGISTER_QASYMM8_SIGNED_NEON(arm_compute::cpu::add_mul_add_s8_neon)
- }
+ {"neon_fp32_add_mul_add", [](const DataTypeISASelectorData &data) { return (data.dt == DataType::F32); },
+ REGISTER_FP32_NEON(arm_compute::cpu::add_mul_add_fp32_neon)},
+ {"neon_fp16_add_mul_add", [](const DataTypeISASelectorData &data) { return (data.dt == DataType::F16); },
+ REGISTER_FP16_NEON(arm_compute::cpu::add_mul_add_fp16_neon)},
+ {"neon_qasymm8_add_mul_add", [](const DataTypeISASelectorData &data) { return (data.dt == DataType::QASYMM8); },
+ REGISTER_QASYMM8_NEON(arm_compute::cpu::add_mul_add_u8_neon)},
+ {"neon_qasymm8_signed_add_mul_add",
+ [](const DataTypeISASelectorData &data) { return (data.dt == DataType::QASYMM8_SIGNED); },
+ REGISTER_QASYMM8_SIGNED_NEON(arm_compute::cpu::add_mul_add_s8_neon)}
#endif // __aarch64__
};
-Status validate_arguments(const ITensorInfo *input1, const ITensorInfo *input2,
- const ITensorInfo *bn_mul, const ITensorInfo *bn_add,
- const ITensorInfo *add_output, const ITensorInfo *final_output,
- ConvertPolicy policy, const ActivationLayerInfo &act_info)
+Status validate_arguments(const ITensorInfo *input1,
+ const ITensorInfo *input2,
+ const ITensorInfo *bn_mul,
+ const ITensorInfo *bn_add,
+ const ITensorInfo *add_output,
+ const ITensorInfo *final_output,
+ ConvertPolicy policy,
+ const ActivationLayerInfo &act_info)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input1, input2, bn_mul, bn_add, final_output);
@@ -78,16 +70,16 @@
using ActFunction = ActivationLayerInfo::ActivationFunction;
const ActFunction act_func = act_info.activation();
- ARM_COMPUTE_RETURN_ERROR_ON_MSG(
- (act_func != ActFunction::BOUNDED_RELU && act_func != ActFunction::RELU && act_func != ActFunction::LU_BOUNDED_RELU && act_func != ActFunction::IDENTITY),
- "Only RELU Family activations, or no activation, is supported");
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG((act_func != ActFunction::BOUNDED_RELU && act_func != ActFunction::RELU &&
+ act_func != ActFunction::LU_BOUNDED_RELU && act_func != ActFunction::IDENTITY),
+ "Only RELU Family activations, or no activation, is supported");
ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(input1);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input1, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED,
DataType::F16, DataType::F32);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input1, input2);
- if(is_data_type_quantized(input1->data_type()))
+ if (is_data_type_quantized(input1->data_type()))
{
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(bn_mul, 1, DataType::F32);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(bn_add, 1, DataType::F32);
@@ -101,39 +93,47 @@
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input1, input2); // No broadcasting
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(bn_mul, bn_add);
ARM_COMPUTE_RETURN_ERROR_ON_MSG(bn_mul->num_dimensions() != 1, "BatchNorm coefficients should be 1D array");
- ARM_COMPUTE_RETURN_ERROR_ON_MSG(bn_mul->tensor_shape()[0] != input1->tensor_shape()[0], "First dimensions of inputs and batchNorm coefs should match");
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(bn_mul->tensor_shape()[0] != input1->tensor_shape()[0],
+ "First dimensions of inputs and batchNorm coefs should match");
// Validate in case we have add layer's output (intermediate) initialized
- if(add_output != nullptr && add_output->total_size() > 0)
+ if (add_output != nullptr && add_output->total_size() > 0)
{
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input1, add_output);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input1, add_output);
}
// Validate in case final output has been initialized
- if(final_output->total_size() > 0)
+ if (final_output->total_size() > 0)
{
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input1, final_output);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input1, final_output);
}
- const auto uk = CpuAddMulAddKernel::get_implementation<DataTypeISASelectorData>(DataTypeISASelectorData{ input1->data_type(), CPUInfo::get().get_isa() });
+ const auto uk = CpuAddMulAddKernel::get_implementation<DataTypeISASelectorData>(
+ DataTypeISASelectorData{input1->data_type(), CPUInfo::get().get_isa()});
ARM_COMPUTE_RETURN_ERROR_ON(uk == nullptr || uk->ukernel == nullptr);
return Status{};
}
} // namespace
-void CpuAddMulAddKernel::configure(const ITensorInfo *input1, const ITensorInfo *input2,
- const ITensorInfo *bn_mul, const ITensorInfo *bn_add,
- ITensorInfo *add_output, ITensorInfo *final_output,
- ConvertPolicy policy, const ActivationLayerInfo &act_info)
+void CpuAddMulAddKernel::configure(const ITensorInfo *input1,
+ const ITensorInfo *input2,
+ const ITensorInfo *bn_mul,
+ const ITensorInfo *bn_add,
+ ITensorInfo *add_output,
+ ITensorInfo *final_output,
+ ConvertPolicy policy,
+ const ActivationLayerInfo &act_info)
{
ARM_COMPUTE_UNUSED(bn_mul, bn_add, input2);
ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, bn_add, bn_mul, final_output);
- ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input1, input2, bn_mul, bn_add, add_output, final_output, policy, act_info));
+ ARM_COMPUTE_ERROR_THROW_ON(
+ validate_arguments(input1, input2, bn_mul, bn_add, add_output, final_output, policy, act_info));
- const auto uk = CpuAddMulAddKernel::get_implementation<DataTypeISASelectorData>(DataTypeISASelectorData{ input1->data_type(), CPUInfo::get().get_isa() });
+ const auto uk = CpuAddMulAddKernel::get_implementation<DataTypeISASelectorData>(
+ DataTypeISASelectorData{input1->data_type(), CPUInfo::get().get_isa()});
ARM_COMPUTE_ERROR_ON_NULLPTR(uk);
ARM_COMPUTE_ERROR_ON(uk->ukernel == nullptr);
@@ -146,7 +146,7 @@
set_shape_if_empty(*final_output, input1->tensor_shape());
set_data_type_if_unknown(*final_output, input1->data_type());
- if(add_output != nullptr)
+ if (add_output != nullptr)
{
set_shape_if_empty(*add_output, input1->tensor_shape());
set_data_type_if_unknown(*add_output, input1->data_type());
@@ -158,14 +158,19 @@
ICpuKernel::configure(win);
}
-Status CpuAddMulAddKernel::validate(const ITensorInfo *input1, const ITensorInfo *input2,
- const ITensorInfo *bn_mul, const ITensorInfo *bn_add,
- const ITensorInfo *add_output, const ITensorInfo *final_output,
- ConvertPolicy policy, const ActivationLayerInfo &act_info)
+Status CpuAddMulAddKernel::validate(const ITensorInfo *input1,
+ const ITensorInfo *input2,
+ const ITensorInfo *bn_mul,
+ const ITensorInfo *bn_add,
+ const ITensorInfo *add_output,
+ const ITensorInfo *final_output,
+ ConvertPolicy policy,
+ const ActivationLayerInfo &act_info)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input1, input2, bn_mul, bn_add, final_output);
- ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input1, input2, bn_mul, bn_add, add_output, final_output, policy, act_info));
+ ARM_COMPUTE_RETURN_ON_ERROR(
+ validate_arguments(input1, input2, bn_mul, bn_add, add_output, final_output, policy, act_info));
return Status{};
}