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/CpuSoftmaxKernel.cpp b/src/cpu/kernels/CpuSoftmaxKernel.cpp
index e06ab99..ce14435 100644
--- a/src/cpu/kernels/CpuSoftmaxKernel.cpp
+++ b/src/cpu/kernels/CpuSoftmaxKernel.cpp
@@ -30,11 +30,11 @@
#include "arm_compute/core/Utils.h"
#include "arm_compute/core/Validate.h"
#include "arm_compute/core/Window.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/core/common/Registrars.h"
#include "src/cpu/kernels/softmax/list.h"
namespace arm_compute
@@ -46,61 +46,44 @@
namespace
{
/* Softmax Logits 1D Max - identifying the max value of 1D Logits */
-static const std::vector<CpuLogits1DMaxKernel::SoftmaxLogits1DMaxKernel> available_kernels_max_logits =
-{
- {
- "sve_fp32_logits_1d_max",
- [](const DataTypeISASelectorData & data) { return (data.dt == DataType::F32) && data.isa.sve; },
- REGISTER_FP32_SVE(sve_fp32_logits)
- },
- {
- "sve_fp16_logits_1d_max",
- [](const DataTypeISASelectorData & data) { return (data.dt == DataType::F16) && data.isa.sve && data.isa.fp16; },
- REGISTER_FP16_SVE(sve_fp16_logits)
- },
- {
- "sve_qu8_logits_1d_max",
- [](const DataTypeISASelectorData & data) { return (data.dt == DataType::QASYMM8) && data.isa.sve; },
- REGISTER_QASYMM8_SVE(sve_qasymm8_logits)
- },
- {
- "sve_qs8_logits_1d_max",
- [](const DataTypeISASelectorData & data) { return (data.dt == DataType::QASYMM8_SIGNED) && data.isa.sve; },
- REGISTER_QASYMM8_SIGNED_SVE(sve_qasymm8_signed_logits)
- },
- {
- "neon_fp32_logits_1d_max",
- [](const DataTypeISASelectorData & data) { return (data.dt == DataType::F32); },
- REGISTER_FP32_NEON(neon_fp32_logits)
- },
- {
- "neon_fp16_logits_1d_max",
- [](const DataTypeISASelectorData & data) { return (data.dt == DataType::F16) && data.isa.fp16; },
- REGISTER_FP16_NEON(neon_fp16_logits)
- },
- {
- "neon_qu8_logits_1d_max",
- [](const DataTypeISASelectorData & data) { return (data.dt == DataType::QASYMM8); },
- REGISTER_QASYMM8_NEON(neon_qasymm8_logits)
- },
- {
- "neon_qs8_logits_1d_max",
- [](const DataTypeISASelectorData & data) { return (data.dt == DataType::QASYMM8_SIGNED); },
- REGISTER_QASYMM8_SIGNED_NEON(neon_qasymm8_singed_logits)
- },
+static const std::vector<CpuLogits1DMaxKernel::SoftmaxLogits1DMaxKernel> available_kernels_max_logits = {
+ {"sve_fp32_logits_1d_max",
+ [](const DataTypeISASelectorData &data) { return (data.dt == DataType::F32) && data.isa.sve; },
+ REGISTER_FP32_SVE(sve_fp32_logits)},
+ {"sve_fp16_logits_1d_max",
+ [](const DataTypeISASelectorData &data) { return (data.dt == DataType::F16) && data.isa.sve && data.isa.fp16; },
+ REGISTER_FP16_SVE(sve_fp16_logits)},
+ {"sve_qu8_logits_1d_max",
+ [](const DataTypeISASelectorData &data) { return (data.dt == DataType::QASYMM8) && data.isa.sve; },
+ REGISTER_QASYMM8_SVE(sve_qasymm8_logits)},
+ {"sve_qs8_logits_1d_max",
+ [](const DataTypeISASelectorData &data) { return (data.dt == DataType::QASYMM8_SIGNED) && data.isa.sve; },
+ REGISTER_QASYMM8_SIGNED_SVE(sve_qasymm8_signed_logits)},
+ {"neon_fp32_logits_1d_max", [](const DataTypeISASelectorData &data) { return (data.dt == DataType::F32); },
+ REGISTER_FP32_NEON(neon_fp32_logits)},
+ {"neon_fp16_logits_1d_max",
+ [](const DataTypeISASelectorData &data) { return (data.dt == DataType::F16) && data.isa.fp16; },
+ REGISTER_FP16_NEON(neon_fp16_logits)},
+ {"neon_qu8_logits_1d_max", [](const DataTypeISASelectorData &data) { return (data.dt == DataType::QASYMM8); },
+ REGISTER_QASYMM8_NEON(neon_qasymm8_logits)},
+ {"neon_qs8_logits_1d_max",
+ [](const DataTypeISASelectorData &data) { return (data.dt == DataType::QASYMM8_SIGNED); },
+ REGISTER_QASYMM8_SIGNED_NEON(neon_qasymm8_singed_logits)},
};
Status validate_arguments_logits_1d_max(const ITensorInfo &input, const ITensorInfo &output)
{
ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(&input);
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&input, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::F16, DataType::F32);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&input, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED,
+ DataType::F16, DataType::F32);
// Validate in case of configured output
- if(output.total_size() != 0)
+ if (output.total_size() != 0)
{
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(&input, &output);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_QUANTIZATION_INFO(&input, &output);
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output.tensor_shape(), TensorShape(input.tensor_shape()).set(0, 1));
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output.tensor_shape(),
+ TensorShape(input.tensor_shape()).set(0, 1));
}
return Status{};
@@ -121,7 +104,7 @@
// Output auto initialization if not yet initialized
auto_init_if_empty(*dst, output_shape, 1, src->data_type(), src->quantization_info());
- const auto *uk = get_implementation(DataTypeISASelectorData{ src->data_type(), CPUInfo::get().get_isa() });
+ const auto *uk = get_implementation(DataTypeISASelectorData{src->data_type(), CPUInfo::get().get_isa()});
ARM_COMPUTE_ERROR_ON(uk == nullptr || uk->ukernel == nullptr);
_run_method = uk->ukernel;
@@ -158,60 +141,46 @@
}
/* Softmax Logits 1D - computation for QASYMM8 with pre-computed max. */
-template <bool IS_LOG>
-static const std::vector<typename CpuLogits1DSoftmaxKernel<IS_LOG>::SoftmaxLogits1DKernel> available_kernels_logits =
-{
- {
- "sve2_qu8_softmax_logits_1d",
- [](const DataTypeISASelectorData & data) { return (data.dt == DataType::QASYMM8) && data.isa.sve2; },
- REGISTER_QASYMM8_SVE2(sve2_qasymm8_softmax)
- },
- {
- "sve2_qs8_softmax_logits_1d",
- [](const DataTypeISASelectorData & data) { return (data.dt == DataType::QASYMM8_SIGNED) && data.isa.sve2; },
- REGISTER_QASYMM8_SIGNED_SVE2(sve2_qasymm8_signed_softmax)
- },
- {
- "sve_fp32_softmax_logits_1d",
- [](const DataTypeISASelectorData & data) { return (data.dt == DataType::F32) && data.isa.sve; },
- REGISTER_FP32_SVE(sve_fp32_softmax)
- },
- {
- "sve_fp16_softmax_logits_1d",
- [](const DataTypeISASelectorData & data) { return (data.dt == DataType::F16) && data.isa.sve && data.isa.fp16; },
- REGISTER_FP16_SVE(sve_fp16_softmax)
- },
+template <bool IS_LOG>
+static const std::vector<typename CpuLogits1DSoftmaxKernel<IS_LOG>::SoftmaxLogits1DKernel> available_kernels_logits = {
+ {"sve2_qu8_softmax_logits_1d",
+ [](const DataTypeISASelectorData &data) { return (data.dt == DataType::QASYMM8) && data.isa.sve2; },
+ REGISTER_QASYMM8_SVE2(sve2_qasymm8_softmax)},
+ {"sve2_qs8_softmax_logits_1d",
+ [](const DataTypeISASelectorData &data) { return (data.dt == DataType::QASYMM8_SIGNED) && data.isa.sve2; },
+ REGISTER_QASYMM8_SIGNED_SVE2(sve2_qasymm8_signed_softmax)},
+ {"sve_fp32_softmax_logits_1d",
+ [](const DataTypeISASelectorData &data) { return (data.dt == DataType::F32) && data.isa.sve; },
+ REGISTER_FP32_SVE(sve_fp32_softmax)},
+ {"sve_fp16_softmax_logits_1d",
+ [](const DataTypeISASelectorData &data) { return (data.dt == DataType::F16) && data.isa.sve && data.isa.fp16; },
+ REGISTER_FP16_SVE(sve_fp16_softmax)},
- {
- "neon_fp32_softmax_logits_1d",
- [](const DataTypeISASelectorData & data) { return (data.dt == DataType::F32); },
- REGISTER_FP32_NEON(neon_fp32_softmax)
- },
- {
- "neon_fp16_softmax_logits_1d",
- [](const DataTypeISASelectorData & data) { return (data.dt == DataType::F16) && data.isa.fp16; },
- REGISTER_FP16_NEON(neon_fp16_softmax)
- },
- {
- "neon_qu8_softmax_logits_1d",
- [](const DataTypeISASelectorData & data) { return (data.dt == DataType::QASYMM8); },
- REGISTER_QASYMM8_NEON(arm_compute::cpu::neon_qasymm8_softmax)
- },
- {
- "neon_qs8_softmax_logits_1d",
- [](const DataTypeISASelectorData & data) { return (data.dt == DataType::QASYMM8_SIGNED); },
- REGISTER_QASYMM8_SIGNED_NEON(arm_compute::cpu::neon_qasymm8_signed_softmax)
- },
+ {"neon_fp32_softmax_logits_1d", [](const DataTypeISASelectorData &data) { return (data.dt == DataType::F32); },
+ REGISTER_FP32_NEON(neon_fp32_softmax)},
+ {"neon_fp16_softmax_logits_1d",
+ [](const DataTypeISASelectorData &data) { return (data.dt == DataType::F16) && data.isa.fp16; },
+ REGISTER_FP16_NEON(neon_fp16_softmax)},
+ {"neon_qu8_softmax_logits_1d", [](const DataTypeISASelectorData &data) { return (data.dt == DataType::QASYMM8); },
+ REGISTER_QASYMM8_NEON(arm_compute::cpu::neon_qasymm8_softmax)},
+ {"neon_qs8_softmax_logits_1d",
+ [](const DataTypeISASelectorData &data) { return (data.dt == DataType::QASYMM8_SIGNED); },
+ REGISTER_QASYMM8_SIGNED_NEON(arm_compute::cpu::neon_qasymm8_signed_softmax)},
};
namespace
{
-Status validate_arguments_logits_softmax(const ITensorInfo &src, const ITensorInfo &max,
- const ITensorInfo &dst, const float beta, const ITensorInfo &tmp, bool is_log)
+Status validate_arguments_logits_softmax(const ITensorInfo &src,
+ const ITensorInfo &max,
+ const ITensorInfo &dst,
+ const float beta,
+ const ITensorInfo &tmp,
+ bool is_log)
{
ARM_COMPUTE_UNUSED(beta);
// Check input
ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(&src);
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&src, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::F16, DataType::F32);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&src, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED,
+ DataType::F16, DataType::F32);
const bool is_quantized_asymmetric = is_data_type_quantized_asymmetric(src.data_type());
@@ -221,16 +190,18 @@
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_QUANTIZATION_INFO(&src, &max);
// Check output if configured
- if(dst.total_size() != 0)
+ if (dst.total_size() != 0)
{
- const QuantizationInfo output_quantization = is_quantized_asymmetric ? arm_compute::get_softmax_output_quantization_info(src.data_type(), is_log) : dst.quantization_info();
+ const QuantizationInfo output_quantization =
+ is_quantized_asymmetric ? arm_compute::get_softmax_output_quantization_info(src.data_type(), is_log)
+ : dst.quantization_info();
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(&src, &dst);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(&src, &dst);
ARM_COMPUTE_RETURN_ERROR_ON(dst.quantization_info() != output_quantization);
}
// Check tmp if configured
- if(tmp.total_size() != 0)
+ if (tmp.total_size() != 0)
{
const DataType tmp_data_type = is_quantized_asymmetric ? DataType::F32 : src.data_type();
ARM_COMPUTE_RETURN_ERROR_ON(tmp.data_type() != tmp_data_type);
@@ -243,14 +214,16 @@
}
} // namespace
-template <bool IS_LOG>
-const std::vector<typename CpuLogits1DSoftmaxKernel<IS_LOG>::SoftmaxLogits1DKernel> &CpuLogits1DSoftmaxKernel<IS_LOG>::get_available_kernels()
+template <bool IS_LOG>
+const std::vector<typename CpuLogits1DSoftmaxKernel<IS_LOG>::SoftmaxLogits1DKernel> &
+CpuLogits1DSoftmaxKernel<IS_LOG>::get_available_kernels()
{
return available_kernels_logits<IS_LOG>;
}
template <bool IS_LOG>
-void CpuLogits1DSoftmaxKernel<IS_LOG>::configure(const ITensorInfo *src, const ITensorInfo *max, ITensorInfo *dst, const float beta, ITensorInfo *tmp)
+void CpuLogits1DSoftmaxKernel<IS_LOG>::configure(
+ const ITensorInfo *src, const ITensorInfo *max, ITensorInfo *dst, const float beta, ITensorInfo *tmp)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(src, max, dst, tmp);
ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_logits_softmax(*src, *max, *dst, beta, *tmp, IS_LOG));
@@ -259,17 +232,21 @@
const bool is_quantized_asymmetric = is_data_type_quantized_asymmetric(src->data_type());
// Output auto initialization if not yet initialized
- const QuantizationInfo output_quantization = is_quantized_asymmetric ? arm_compute::get_softmax_output_quantization_info(src->data_type(), IS_LOG) : dst->quantization_info();
+ const QuantizationInfo output_quantization =
+ is_quantized_asymmetric ? arm_compute::get_softmax_output_quantization_info(src->data_type(), IS_LOG)
+ : dst->quantization_info();
auto_init_if_empty(*dst, TensorInfo(*src).set_quantization_info(output_quantization).reset_padding());
// Tmp auto initialization if not yet initialized
const DataType tmp_data_type = is_quantized_asymmetric ? DataType::F32 : src->data_type();
auto_init_if_empty(*tmp, TensorInfo(*src).set_data_type(tmp_data_type).reset_padding());
- const auto *uk = CpuLogits1DSoftmaxKernel<IS_LOG>::get_implementation(DataTypeISASelectorData{ src->data_type(), CPUInfo::get().get_isa() });
+ const auto *uk = CpuLogits1DSoftmaxKernel<IS_LOG>::get_implementation(
+ DataTypeISASelectorData{src->data_type(), CPUInfo::get().get_isa()});
ARM_COMPUTE_ERROR_ON(uk == nullptr || uk->ukernel == nullptr);
- std::string kernel_name = IS_LOG ? std::string("CpuLogits1DLogSoftmaxKernel") : std::string("CpuLogits1DSoftmaxKernel");
+ std::string kernel_name =
+ IS_LOG ? std::string("CpuLogits1DLogSoftmaxKernel") : std::string("CpuLogits1DSoftmaxKernel");
_beta = beta;
_run_method = uk->ukernel;
@@ -282,8 +259,8 @@
}
template <bool IS_LOG>
-Status CpuLogits1DSoftmaxKernel<IS_LOG>::validate(const ITensorInfo *src, const ITensorInfo *max,
- const ITensorInfo *dst, const float beta, const ITensorInfo *tmp)
+Status CpuLogits1DSoftmaxKernel<IS_LOG>::validate(
+ const ITensorInfo *src, const ITensorInfo *max, const ITensorInfo *dst, const float beta, const ITensorInfo *tmp)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(src, max, dst, tmp);
ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_logits_softmax(*src, *max, *dst, beta, *tmp, IS_LOG));
@@ -305,7 +282,7 @@
auto tmp = tensors.get_tensor(TensorType::ACL_DST_1);
const unsigned int num_elems_processed_per_iteration = src->info()->valid_region().shape.x();
- const unsigned int tmp_size_for_thread = tmp->info()->element_size() * num_elems_processed_per_iteration;
+ const unsigned int tmp_size_for_thread = tmp->info()->element_size() * num_elems_processed_per_iteration;
ARM_COMPUTE_ERROR_ON(tmp->info()->total_size() < (info.num_threads * tmp_size_for_thread));
@@ -314,7 +291,7 @@
}
template <bool IS_LOG>
-const char *CpuLogits1DSoftmaxKernel<IS_LOG>::name() const
+const char *CpuLogits1DSoftmaxKernel<IS_LOG>::name() const
{
return _name.c_str();
}