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/operators/ClSoftmax.cpp b/src/gpu/cl/operators/ClSoftmax.cpp
index 0380955..2bec400 100644
--- a/src/gpu/cl/operators/ClSoftmax.cpp
+++ b/src/gpu/cl/operators/ClSoftmax.cpp
@@ -22,7 +22,10 @@
* SOFTWARE.
*/
#include "src/gpu/cl/operators/ClSoftmax.h"
+
#include "arm_compute/core/utils/misc/ShapeCalculator.h"
+
+#include "src/common/utils/Log.h"
#include "src/core/helpers/MemoryHelpers.h"
#include "src/core/helpers/SoftmaxHelpers.h"
#include "src/gpu/cl/kernels/ClSoftmaxKernel.h"
@@ -30,8 +33,6 @@
#include "src/gpu/cl/utils/ClAuxTensorHandler.h"
#include "support/Cast.h"
-#include "src/common/utils/Log.h"
-
using namespace arm_compute::experimental;
namespace arm_compute
@@ -52,7 +53,10 @@
{
}
-void ClSoftmax::configure(const CLCompileContext &compile_context, const ITensorInfo &src, ITensorInfo &dst, const SoftmaxKernelInfo &info)
+void ClSoftmax::configure(const CLCompileContext &compile_context,
+ const ITensorInfo &src,
+ ITensorInfo &dst,
+ const SoftmaxKernelInfo &info)
{
ARM_COMPUTE_ERROR_THROW_ON(validate(src, dst, info));
ARM_COMPUTE_LOG_PARAMS(src, dst, info);
@@ -64,14 +68,15 @@
const ITensorInfo &tmp_input_info = _needs_permute ? _permuted_src_info : src;
ITensorInfo &tmp_output_info = _needs_permute ? _permuted_dst_info : dst;
- if(_needs_permute)
+ if (_needs_permute)
{
const auto perm_info = softmax_helpers::get_permutation_vector_from_softmax_axis(actual_axis);
_permute_input->configure(compile_context, &src, &_permuted_src_info, perm_info);
}
- DataType tmp_data_type = is_data_type_quantized_asymmetric(tmp_input_info.data_type()) ? DataType::S32 : tmp_input_info.data_type();
- _tmp_info = tmp_input_info.clone()->set_data_type(tmp_data_type);
+ DataType tmp_data_type =
+ is_data_type_quantized_asymmetric(tmp_input_info.data_type()) ? DataType::S32 : tmp_input_info.data_type();
+ _tmp_info = tmp_input_info.clone()->set_data_type(tmp_data_type);
TensorShape max_sum_shape = tmp_input_info.tensor_shape();
_max_info = tmp_input_info.clone()->set_tensor_shape(max_sum_shape);
@@ -83,33 +88,41 @@
_max_shift_exp_sum_kernel->configure(compile_context, tmp_input_info, _max_info, _tmp_info, _sum_info, info);
_norm_kernel->configure(compile_context, _tmp_info, _sum_info, tmp_output_info, info);
- if(_needs_permute)
+ if (_needs_permute)
{
const auto perm_info = softmax_helpers::get_permutation_vector_from_softmax_axis(actual_axis);
_permute_output->configure(compile_context, &_permuted_dst_info, &dst, perm_info);
}
- _aux_mem[InternalTensorIdx::SUM] = MemoryInfo(offset_int_vec(InternalTensorIdx::SUM), MemoryLifetime::Temporary, _sum_info.total_size());
- _aux_mem[InternalTensorIdx::TMP] = MemoryInfo(offset_int_vec(InternalTensorIdx::TMP), MemoryLifetime::Temporary, _tmp_info.total_size());
- _aux_mem[InternalTensorIdx::MAX] = MemoryInfo(offset_int_vec(InternalTensorIdx::MAX), MemoryLifetime::Temporary, _max_info.total_size());
+ _aux_mem[InternalTensorIdx::SUM] =
+ MemoryInfo(offset_int_vec(InternalTensorIdx::SUM), MemoryLifetime::Temporary, _sum_info.total_size());
+ _aux_mem[InternalTensorIdx::TMP] =
+ MemoryInfo(offset_int_vec(InternalTensorIdx::TMP), MemoryLifetime::Temporary, _tmp_info.total_size());
+ _aux_mem[InternalTensorIdx::MAX] =
+ MemoryInfo(offset_int_vec(InternalTensorIdx::MAX), MemoryLifetime::Temporary, _max_info.total_size());
- _aux_mem[InternalTensorIdx::PERMUTED_SRC] = MemoryInfo(offset_int_vec(InternalTensorIdx::PERMUTED_SRC), MemoryLifetime::Temporary, _permuted_src_info.total_size());
- _aux_mem[InternalTensorIdx::PERMUTED_DST] = MemoryInfo(offset_int_vec(InternalTensorIdx::PERMUTED_DST), MemoryLifetime::Temporary, _permuted_dst_info.total_size());
+ _aux_mem[InternalTensorIdx::PERMUTED_SRC] = MemoryInfo(offset_int_vec(InternalTensorIdx::PERMUTED_SRC),
+ MemoryLifetime::Temporary, _permuted_src_info.total_size());
+ _aux_mem[InternalTensorIdx::PERMUTED_DST] = MemoryInfo(offset_int_vec(InternalTensorIdx::PERMUTED_DST),
+ MemoryLifetime::Temporary, _permuted_dst_info.total_size());
}
Status ClSoftmax::validate(const ITensorInfo &src, const ITensorInfo &dst, const SoftmaxKernelInfo &info)
{
ARM_COMPUTE_RETURN_ERROR_ON_MSG(src.num_dimensions() > 4, "Only up to 4 dimensions are supported");
ARM_COMPUTE_UNUSED(info.beta);
- ARM_COMPUTE_RETURN_ERROR_ON(info.axis < static_cast<int32_t>(-src.num_dimensions()) || static_cast<int32_t>(src.num_dimensions()) <= info.axis);
+ ARM_COMPUTE_RETURN_ERROR_ON(info.axis < static_cast<int32_t>(-src.num_dimensions()) ||
+ static_cast<int32_t>(src.num_dimensions()) <= info.axis);
- const size_t actual_axis = static_cast<size_t>(wrap_around(info.axis, static_cast<int32_t>(src.num_dimensions())));
+ const size_t actual_axis = static_cast<size_t>(wrap_around(info.axis, static_cast<int32_t>(src.num_dimensions())));
const bool needs_permute = actual_axis != 0;
- if(needs_permute)
+ if (needs_permute)
{
- const PermutationVector permutation_vector = softmax_helpers::get_permutation_vector_from_softmax_axis(actual_axis);
- const TensorShape permuted_shape = misc::shape_calculator::compute_permutation_output_shape(src, permutation_vector);
- TensorInfo input_permuted(src.clone()->set_tensor_shape(permuted_shape));
+ const PermutationVector permutation_vector =
+ softmax_helpers::get_permutation_vector_from_softmax_axis(actual_axis);
+ const TensorShape permuted_shape =
+ misc::shape_calculator::compute_permutation_output_shape(src, permutation_vector);
+ TensorInfo input_permuted(src.clone()->set_tensor_shape(permuted_shape));
ARM_COMPUTE_RETURN_ON_ERROR(ClPermute::validate(&src, &input_permuted, permutation_vector));
TensorInfo output_permuted(dst.clone()->set_tensor_shape(permuted_shape));
ARM_COMPUTE_RETURN_ON_ERROR(ClPermute::validate(&output_permuted, &dst, permutation_vector));
@@ -122,9 +135,14 @@
TensorShape max_sum_shape = src.tensor_shape();
max_sum_shape.set(0, 1);
TensorInfo tensor_info_max(src.clone()->set_tensor_shape(max_sum_shape).set_is_resizable(true));
- TensorInfo tensor_info_sum(src.clone()->set_tensor_shape(max_sum_shape).set_data_type(tmp_data_type).set_quantization_info(QuantizationInfo()).set_is_resizable(true));
+ TensorInfo tensor_info_sum(src.clone()
+ ->set_tensor_shape(max_sum_shape)
+ .set_data_type(tmp_data_type)
+ .set_quantization_info(QuantizationInfo())
+ .set_is_resizable(true));
- ARM_COMPUTE_RETURN_ON_ERROR(kernels::ClLogits1DMaxShiftExpSumKernel::validate(src, tensor_info_max, tensor_info_tmp, tensor_info_sum));
+ ARM_COMPUTE_RETURN_ON_ERROR(
+ kernels::ClLogits1DMaxShiftExpSumKernel::validate(src, tensor_info_max, tensor_info_tmp, tensor_info_sum));
ARM_COMPUTE_RETURN_ON_ERROR(kernels::ClLogits1DNormKernel::validate(tensor_info_tmp, tensor_info_sum, dst, info));
return Status{};
@@ -139,10 +157,12 @@
CLAuxTensorHandler tmp(offset_int_vec(InternalTensorIdx::TMP), _tmp_info, tensors, false);
CLAuxTensorHandler max(offset_int_vec(InternalTensorIdx::MAX), _max_info, tensors, false);
- CLAuxTensorHandler permuted_src(offset_int_vec(InternalTensorIdx::PERMUTED_SRC), _permuted_src_info, tensors, false);
- CLAuxTensorHandler permuted_dst(offset_int_vec(InternalTensorIdx::PERMUTED_DST), _permuted_dst_info, tensors, false);
+ CLAuxTensorHandler permuted_src(offset_int_vec(InternalTensorIdx::PERMUTED_SRC), _permuted_src_info, tensors,
+ false);
+ CLAuxTensorHandler permuted_dst(offset_int_vec(InternalTensorIdx::PERMUTED_DST), _permuted_dst_info, tensors,
+ false);
- if(_needs_permute)
+ if (_needs_permute)
{
ITensorPack pack;
pack.add_const_tensor(TensorType::ACL_SRC, src);
@@ -152,7 +172,7 @@
ITensorPack sum_pack;
ITensorPack norm_pack;
- if(_needs_permute)
+ if (_needs_permute)
{
sum_pack.add_const_tensor(TensorType::ACL_SRC, permuted_src.get());
norm_pack.add_tensor(TensorType::ACL_DST, permuted_dst.get());
@@ -172,7 +192,7 @@
CLScheduler::get().enqueue_op(*_max_shift_exp_sum_kernel.get(), sum_pack, false);
CLScheduler::get().enqueue_op(*_norm_kernel.get(), norm_pack, false);
- if(_needs_permute)
+ if (_needs_permute)
{
ITensorPack pack;
pack.add_const_tensor(TensorType::ACL_SRC, permuted_dst.get());
@@ -186,4 +206,4 @@
return _aux_mem;
}
} // namespace opencl
-} // namespace arm_compute
\ No newline at end of file
+} // namespace arm_compute