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path: root/src/runtime/CL/functions/CLReductionOperation.cpp
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Diffstat (limited to 'src/runtime/CL/functions/CLReductionOperation.cpp')
-rw-r--r--src/runtime/CL/functions/CLReductionOperation.cpp334
1 files changed, 62 insertions, 272 deletions
diff --git a/src/runtime/CL/functions/CLReductionOperation.cpp b/src/runtime/CL/functions/CLReductionOperation.cpp
index b659ecfaf6..ba5489018e 100644
--- a/src/runtime/CL/functions/CLReductionOperation.cpp
+++ b/src/runtime/CL/functions/CLReductionOperation.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2020 ARM Limited.
+ * Copyright (c) 2017-2021 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -24,39 +24,46 @@
#include "arm_compute/runtime/CL/functions/CLReductionOperation.h"
#include "arm_compute/core/CL/ICLTensor.h"
-#include "arm_compute/core/CL/kernels/CLReductionOperationKernel.h"
-#include "arm_compute/core/Error.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/PixelValue.h"
#include "arm_compute/core/TensorInfo.h"
-#include "arm_compute/core/Validate.h"
#include "arm_compute/core/utils/misc/ShapeCalculator.h"
+#include "arm_compute/core/Validate.h"
#include "arm_compute/runtime/CL/CLScheduler.h"
-#include "arm_compute/runtime/Tensor.h"
-#include "arm_compute/runtime/Utils.h"
-#include "support/MemorySupport.h"
+
+#include "src/common/utils/Log.h"
+#include "src/core/CL/kernels/CLReductionOperationKernel.h"
+#include "src/core/helpers/AutoConfiguration.h"
+#include "src/runtime/Utils.h"
namespace arm_compute
{
CLReductionOperation::CLReductionOperation(std::shared_ptr<IMemoryManager> memory_manager)
- : _memory_group(std::move(memory_manager)), _results_vector(), _reduction_kernels_vector(), _border_handlers_vector(), _reshape_kernel(), _op(), _num_of_stages(), _reduction_axis(), _is_serial(),
+ : _memory_group(std::move(memory_manager)),
+ _unreshaped_output(),
+ _reduction_kernel(),
+ _reshape(),
+ _reduction_axis(),
_is_reshape_required(false)
{
}
-Status CLReductionOperation::validate(const ITensorInfo *input, const ITensorInfo *output, unsigned int axis, ReductionOperation op, bool keep_dims)
+CLReductionOperation::~CLReductionOperation() = default;
+
+Status CLReductionOperation::validate(
+ const ITensorInfo *input, const ITensorInfo *output, unsigned int axis, ReductionOperation op, bool keep_dims)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
- ARM_COMPUTE_RETURN_ERROR_ON_MSG(axis >= TensorShape::num_max_dimensions, "Reduction axis greater than max number of dimensions");
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(axis >= TensorShape::num_max_dimensions,
+ "Reduction axis greater than max number of dimensions");
ARM_COMPUTE_RETURN_ERROR_ON_MSG(axis > 3, "Unsupported reduction axis");
- const unsigned int num_of_stages = calculate_number_of_stages_only_x_axis(input->dimension(0), axis);
- const bool is_serial = needs_serialized_reduction(op, input->data_type(), axis);
- const bool is_reshape_required = !keep_dims;
+ const bool is_reshape_required = !keep_dims;
- if(is_reshape_required && output->total_size() != 0)
+ if (is_reshape_required && output->total_size() != 0)
{
- const TensorInfo expected_output_shape = output->clone()->set_tensor_shape(arm_compute::misc::shape_calculator::compute_reduced_shape(input->tensor_shape(), axis, keep_dims));
+ const TensorInfo expected_output_shape = output->clone()->set_tensor_shape(
+ arm_compute::misc::shape_calculator::compute_reduced_shape(input->tensor_shape(), axis, keep_dims));
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(&expected_output_shape, output);
}
@@ -64,95 +71,29 @@ Status CLReductionOperation::validate(const ITensorInfo *input, const ITensorInf
TensorInfo output_before_reshape;
const auto input_shape = input->tensor_shape();
- const auto input_data_type = input->data_type();
const auto input_num_channles = input->num_channels();
const auto input_qinfo = input->quantization_info();
const auto output_data_type = output->data_type();
- auto initialize_tensorinfo = [](TensorInfo & ti, TensorShape shape, DataType data_type, int num_channels, QuantizationInfo qinfo)
- {
+ auto initialize_tensorinfo = [](TensorInfo &ti, TensorShape shape, DataType data_type, int num_channels,
+ QuantizationInfo qinfo) {
ti.set_data_type(data_type).set_tensor_shape(shape).set_num_channels(num_channels).set_quantization_info(qinfo);
};
- if(is_reshape_required)
+ if (is_reshape_required)
{
auto shape_before_reshape = input_shape;
shape_before_reshape.set(axis, 1);
- initialize_tensorinfo(output_before_reshape, shape_before_reshape, output_data_type, input_num_channles, input_qinfo);
+ initialize_tensorinfo(output_before_reshape, shape_before_reshape, output_data_type, input_num_channles,
+ input_qinfo);
output_internal = &output_before_reshape;
}
- if(is_serial)
- {
- ARM_COMPUTE_RETURN_ON_ERROR(CLReductionOperationKernel::validate(input, output_internal, axis, op));
- }
- else
- {
- // Create temporary tensor infos
- std::vector<TensorInfo> sums_vector(num_of_stages - 1);
-
- // Create intermediate tensor info
- TensorShape shape{ input_shape };
-
- shape.set(0, ceil(shape.x() / 128.f));
+ ARM_COMPUTE_RETURN_ON_ERROR(CLReductionOperationKernel::validate(input, output_internal, axis, op));
- for(unsigned int i = 0; i < num_of_stages - 1; i++)
- {
- initialize_tensorinfo(sums_vector[i], shape, input_data_type, input_num_channles, input_qinfo);
- }
-
- ReductionOperation first_kernel_op;
- ReductionOperation intermediate_kernel_op;
- ReductionOperation last_kernel_op;
- switch(op)
- {
- case ReductionOperation::SUM:
- case ReductionOperation::MEAN_SUM:
- first_kernel_op = ReductionOperation::SUM;
- intermediate_kernel_op = ReductionOperation::SUM;
- last_kernel_op = op;
- break;
- case ReductionOperation::SUM_SQUARE:
- first_kernel_op = ReductionOperation::SUM_SQUARE;
- intermediate_kernel_op = ReductionOperation::SUM;
- last_kernel_op = ReductionOperation::SUM;
- break;
- case ReductionOperation::PROD:
- first_kernel_op = ReductionOperation::PROD;
- intermediate_kernel_op = ReductionOperation::PROD;
- last_kernel_op = ReductionOperation::PROD;
- break;
- case ReductionOperation::MIN:
- first_kernel_op = ReductionOperation::MIN;
- intermediate_kernel_op = ReductionOperation::MIN;
- last_kernel_op = ReductionOperation::MIN;
- break;
- case ReductionOperation::MAX:
- first_kernel_op = ReductionOperation::MAX;
- intermediate_kernel_op = ReductionOperation::MAX;
- last_kernel_op = ReductionOperation::MAX;
- break;
- default:
- ARM_COMPUTE_ERROR("Not supported");
- }
-
- // Validate ReductionOperation only on first kernel
- ARM_COMPUTE_RETURN_ON_ERROR(CLReductionOperationKernel::validate(input, &sums_vector[0], axis, first_kernel_op));
-
- // Validate ReductionOperation on intermediate stages
- for(unsigned int i = 1; i < num_of_stages - 1; ++i)
- {
- ARM_COMPUTE_RETURN_ON_ERROR(CLReductionOperationKernel::validate(&sums_vector[i - 1], &sums_vector[i], axis, intermediate_kernel_op));
- }
-
- // Validate ReductionOperation on the last stage
- const unsigned int last_stage = num_of_stages - 1;
- ARM_COMPUTE_RETURN_ON_ERROR(CLReductionOperationKernel::validate(&sums_vector[last_stage - 1], output_internal, axis, last_kernel_op, input->dimension(0)));
- }
-
- if(is_reshape_required)
+ if (is_reshape_required)
{
- ARM_COMPUTE_RETURN_ON_ERROR(CLReshapeLayerKernel::validate(output_internal, output));
+ ARM_COMPUTE_RETURN_ON_ERROR(CLReshapeLayer::validate(output_internal, output));
}
return Status{};
@@ -160,199 +101,59 @@ Status CLReductionOperation::validate(const ITensorInfo *input, const ITensorInf
ICLTensor *CLReductionOperation::configure_intermediate_result_vector(ICLTensor *input, ICLTensor *output)
{
- if(!_is_reshape_required && _is_serial)
+ if (!_is_reshape_required)
{
return output;
}
- auto intermediate_result_vector_size = _is_serial ? 1 : _num_of_stages;
-
- if(!_is_reshape_required)
- {
- --intermediate_result_vector_size;
- }
-
- _results_vector.resize(intermediate_result_vector_size);
auto shape = input->info()->tensor_shape();
-
- shape.set(_reduction_axis, _is_serial ? 1 : ceil(shape.x() / 128.f));
-
- for(auto &v : _results_vector)
- {
- if(&v == &_results_vector.back() && _is_reshape_required)
- {
- shape.set(_reduction_axis, 1);
- }
- v.allocator()->init(input->info()->clone()->set_tensor_shape(shape));
- }
-
- return _is_reshape_required ? &_results_vector.back() : output;
+ shape.set(_reduction_axis, 1);
+ _unreshaped_output.allocator()->init(input->info()->clone()->set_tensor_shape(shape));
+ return &_unreshaped_output;
}
-void CLReductionOperation::configure(ICLTensor *input, ICLTensor *output, unsigned int axis, ReductionOperation op, bool keep_dims)
+void CLReductionOperation::configure(
+ ICLTensor *input, ICLTensor *output, unsigned int axis, ReductionOperation op, bool keep_dims)
{
configure(CLKernelLibrary::get().get_compile_context(), input, output, axis, op, keep_dims);
}
-void CLReductionOperation::configure(const CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output, unsigned int axis, ReductionOperation op, bool keep_dims)
+void CLReductionOperation::configure(const CLCompileContext &compile_context,
+ ICLTensor *input,
+ ICLTensor *output,
+ unsigned int axis,
+ ReductionOperation op,
+ bool keep_dims)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
- _op = op;
- _num_of_stages = calculate_number_of_stages_only_x_axis(input->info()->dimension(0), axis);
+ ARM_COMPUTE_LOG_PARAMS(input, output, axis, op, keep_dims);
_reduction_axis = axis;
- _is_serial = needs_serialized_reduction(op, input->info()->data_type(), axis);
_is_reshape_required = !keep_dims;
auto *output_internal = configure_intermediate_result_vector(input, output);
- if(_is_reshape_required)
+ if (_is_reshape_required)
{
- const TensorShape output_shape = arm_compute::misc::shape_calculator::compute_reduced_shape(input->info()->tensor_shape(), axis, false);
- const auto output_data_type = input->info()->data_type();
- auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(output_shape).set_data_type(output_data_type).reset_padding().set_is_resizable(true));
- }
-
- // Configure reduction operation kernels
- _reduction_kernels_vector.resize(_num_of_stages);
+ const TensorShape output_shape =
+ arm_compute::misc::shape_calculator::compute_reduced_shape(input->info()->tensor_shape(), axis, false);
+ const auto output_data_type = input->info()->data_type();
+ auto_init_if_empty(*output->info(), input->info()
+ ->clone()
+ ->set_tensor_shape(output_shape)
+ .set_data_type(output_data_type)
+ .reset_padding()
+ .set_is_resizable(true));
- // Create temporary tensors
- if(_is_serial)
- {
- if(_is_reshape_required)
- {
- _memory_group.manage(&_results_vector.back());
- }
-
- _reduction_kernels_vector[0].configure(compile_context, input, output_internal, axis, op, 0);
+ _memory_group.manage(&_unreshaped_output);
}
- else
- {
- _border_handlers_vector.resize(_num_of_stages);
- _memory_group.manage(&_results_vector[0]);
- ReductionOperation first_kernel_op;
- ReductionOperation intermediate_kernel_op;
- ReductionOperation last_kernel_op;
- PixelValue pixelValue;
- switch(op)
- {
- case ReductionOperation::SUM:
- case ReductionOperation::MEAN_SUM:
- first_kernel_op = ReductionOperation::SUM;
- intermediate_kernel_op = ReductionOperation::SUM;
- last_kernel_op = op;
- pixelValue = PixelValue();
- break;
- case ReductionOperation::SUM_SQUARE:
- first_kernel_op = ReductionOperation::SUM_SQUARE;
- intermediate_kernel_op = ReductionOperation::SUM;
- last_kernel_op = ReductionOperation::SUM;
- pixelValue = PixelValue();
- break;
- case ReductionOperation::PROD:
- first_kernel_op = ReductionOperation::PROD;
- intermediate_kernel_op = ReductionOperation::PROD;
- last_kernel_op = ReductionOperation::PROD;
- pixelValue = PixelValue(1, input->info()->data_type());
- break;
- case ReductionOperation::MIN:
- first_kernel_op = ReductionOperation::MIN;
- intermediate_kernel_op = ReductionOperation::MIN;
- last_kernel_op = ReductionOperation::MIN;
- switch(input->info()->data_type())
- {
- case DataType::F32:
- {
- pixelValue = PixelValue(std::numeric_limits<float>::max());
- break;
- }
- case DataType::F16:
- {
- pixelValue = PixelValue(static_cast<half>(65504.0f));
- break;
- }
- case DataType::QASYMM8:
- {
- pixelValue = std::get<1>(get_min_max(input->info()->data_type()));
- break;
- }
- case DataType::QASYMM8_SIGNED:
- {
- pixelValue = PixelValue(127, input->info()->data_type(), input->info()->quantization_info());
- break;
- }
- default:
- {
- ARM_COMPUTE_ERROR("Unsupported DataType");
- }
- }
- break;
- case ReductionOperation::MAX:
- first_kernel_op = ReductionOperation::MAX;
- intermediate_kernel_op = ReductionOperation::MAX;
- last_kernel_op = ReductionOperation::MAX;
- switch(input->info()->data_type())
- {
- case DataType::F32:
- {
- pixelValue = PixelValue(-std::numeric_limits<float>::max());
- break;
- }
- case DataType::F16:
- {
- pixelValue = PixelValue(static_cast<half>(-65504.0f));
- break;
- }
- case DataType::QASYMM8:
- {
- pixelValue = std::get<0>(get_min_max(input->info()->data_type()));
- break;
- }
- case DataType::QASYMM8_SIGNED:
- {
- pixelValue = PixelValue(-128, input->info()->data_type(), input->info()->quantization_info());
- break;
- }
- default:
- {
- ARM_COMPUTE_ERROR("Unsupported DataType");
- }
- }
- break;
- default:
- ARM_COMPUTE_ERROR("Not supported");
- }
+ _reduction_kernel = std::make_unique<CLReductionOperationKernel>();
+ _reduction_kernel->configure(compile_context, input, output_internal, axis, op);
- _reduction_kernels_vector[0].configure(compile_context, input, &_results_vector[0], axis, first_kernel_op);
- _border_handlers_vector[0].configure(compile_context, input, _reduction_kernels_vector[0].border_size(), BorderMode::CONSTANT, pixelValue);
-
- // Apply ReductionOperation on intermediate stages
- for(unsigned int i = 1; i < _num_of_stages - 1; ++i)
- {
- _memory_group.manage(&_results_vector[i]);
- _reduction_kernels_vector[i].configure(compile_context, &_results_vector[i - 1], &_results_vector[i], axis, intermediate_kernel_op);
- _border_handlers_vector[i].configure(compile_context, &_results_vector[i - 1], _reduction_kernels_vector[i].border_size(), BorderMode::CONSTANT, pixelValue);
- _results_vector[i - 1].allocator()->allocate();
- }
-
- // Apply ReductionOperation on the last stage
- const unsigned int last_stage = _num_of_stages - 1;
- const unsigned int input_width = input->info()->dimension(0);
-
- if(_is_reshape_required)
- {
- _memory_group.manage(&_results_vector.back());
- }
-
- _reduction_kernels_vector[last_stage].configure(compile_context, &_results_vector[last_stage - 1], output_internal, axis, last_kernel_op, input_width);
- _border_handlers_vector[last_stage].configure(compile_context, &_results_vector[last_stage - 1], _reduction_kernels_vector[last_stage].border_size(), BorderMode::CONSTANT, pixelValue);
- _results_vector[last_stage - 1].allocator()->allocate();
- }
-
- if(_is_reshape_required)
+ if (_is_reshape_required)
{
- _reshape_kernel.configure(compile_context, &_results_vector.back(), output);
- _results_vector.back().allocator()->allocate();
+ _reshape.configure(compile_context, &_unreshaped_output, output);
+ _unreshaped_output.allocator()->allocate();
}
}
@@ -360,22 +161,11 @@ void CLReductionOperation::run()
{
MemoryGroupResourceScope scope_mg(_memory_group);
- if(_is_serial)
- {
- CLScheduler::get().enqueue(_reduction_kernels_vector[0], false);
- }
- else
- {
- for(unsigned int i = 0; i < _num_of_stages; ++i)
- {
- CLScheduler::get().enqueue(_border_handlers_vector[i], false);
- CLScheduler::get().enqueue(_reduction_kernels_vector[i], false);
- }
- }
+ CLScheduler::get().enqueue(*_reduction_kernel, false);
- if(_is_reshape_required)
+ if (_is_reshape_required)
{
- CLScheduler::get().enqueue(_reshape_kernel, false);
+ _reshape.run();
}
}
} // namespace arm_compute
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-05 18:51:15 +0000