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path: root/src/runtime/CL/functions/CLArgMinMaxLayer.cpp
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Diffstat (limited to 'src/runtime/CL/functions/CLArgMinMaxLayer.cpp')
-rw-r--r--src/runtime/CL/functions/CLArgMinMaxLayer.cpp149
1 files changed, 54 insertions, 95 deletions
diff --git a/src/runtime/CL/functions/CLArgMinMaxLayer.cpp b/src/runtime/CL/functions/CLArgMinMaxLayer.cpp
index 8c32563abb..f9bbd31e8a 100644
--- a/src/runtime/CL/functions/CLArgMinMaxLayer.cpp
+++ b/src/runtime/CL/functions/CLArgMinMaxLayer.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018-2020 Arm Limited.
+ * Copyright (c) 2018-2021, 2023 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -27,8 +27,10 @@
#include "arm_compute/core/Error.h"
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/Types.h"
-#include "arm_compute/core/Validate.h"
#include "arm_compute/core/utils/misc/ShapeCalculator.h"
+#include "arm_compute/core/Validate.h"
+
+#include "src/common/utils/Log.h"
#include "src/core/CL/CLValidate.h"
#include "src/core/CL/kernels/CLArgMinMaxLayerKernel.h"
#include "src/core/helpers/AutoConfiguration.h"
@@ -37,76 +39,52 @@
namespace arm_compute
{
CLArgMinMaxLayer::CLArgMinMaxLayer(std::shared_ptr<IMemoryManager> memory_manager)
- : _memory_group(std::move(memory_manager)), _results_vector(), _not_reshaped_output(), _reduction_kernels_vector(), _reshape(), _num_of_stages(), _reduction_axis()
+ : _memory_group(std::move(memory_manager)),
+ _not_reshaped_output(),
+ _arg_min_max_kernel(),
+ _reshape(),
+ _reduction_axis()
{
}
CLArgMinMaxLayer::~CLArgMinMaxLayer() = default;
-Status CLArgMinMaxLayer::validate(const ITensorInfo *input, int axis, const ITensorInfo *output, const ReductionOperation &op)
+Status
+CLArgMinMaxLayer::validate(const ITensorInfo *input, int axis, const ITensorInfo *output, const ReductionOperation &op)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input);
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::S32, DataType::F16, DataType::F32);
- ARM_COMPUTE_RETURN_ERROR_ON_MSG(op != ReductionOperation::ARG_IDX_MAX && op != ReductionOperation::ARG_IDX_MIN, "Invalid reduction operation");
- ARM_COMPUTE_RETURN_ERROR_ON_MSG(axis >= static_cast<int>(TensorShape::num_max_dimensions), "Reduction axis greater than max number of dimensions");
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED,
+ DataType::S32, DataType::F16, DataType::F32);
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(op != ReductionOperation::ARG_IDX_MAX && op != ReductionOperation::ARG_IDX_MIN,
+ "Invalid reduction operation");
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(axis >= static_cast<int>(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 = utils::calculate_number_of_stages_only_x_axis(input->dimension(0), axis);
DataType output_data_type = DataType::S32;
TensorInfo not_reshaped_output;
const auto input_num_channles = input->num_channels();
const auto input_qinfo = input->quantization_info();
- if(output->total_size() != 0)
+ if (output->total_size() != 0)
{
output_data_type = output->data_type();
- const TensorInfo expected_output_shape = output->clone()->set_tensor_shape(arm_compute::misc::shape_calculator::compute_reduced_shape(input->tensor_shape(), axis, false));
+ const TensorInfo expected_output_shape = output->clone()->set_tensor_shape(
+ arm_compute::misc::shape_calculator::compute_reduced_shape(input->tensor_shape(), axis, false));
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(&expected_output_shape, output);
}
auto shape_before_reshape = input->tensor_shape();
shape_before_reshape.set(axis, 1);
- 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);
};
initialize_tensorinfo(not_reshaped_output, shape_before_reshape, output_data_type, input_num_channles, input_qinfo);
- if(num_of_stages == 1)
- {
- ARM_COMPUTE_RETURN_ON_ERROR(CLArgMinMaxLayerKernel::validate(input, nullptr, &not_reshaped_output, axis, op));
- }
- else
- {
- // Create temporary tensor infos
- std::vector<TensorInfo> sums_vector(num_of_stages - 1);
-
- // Create intermediate tensor info
- TensorShape shape{ input->tensor_shape() };
-
- for(unsigned int i = 0; i < num_of_stages - 1; i++)
- {
- shape.set(0, ceil(shape.x() / 128.f));
- sums_vector[i].set_data_type(input->data_type());
- sums_vector[i].set_tensor_shape(shape);
- sums_vector[i].set_num_channels(input->num_channels());
- }
-
- // Validate ReductionOperation only on first kernel
- ARM_COMPUTE_RETURN_ON_ERROR(CLArgMinMaxLayerKernel::validate(input, nullptr, &sums_vector[0], axis, op));
-
- // Validate ReductionOperation on intermediate stages
- for(unsigned int i = 1; i < num_of_stages - 1; ++i)
- {
- ARM_COMPUTE_RETURN_ON_ERROR(CLArgMinMaxLayerKernel::validate(input, &sums_vector[i - 1], &sums_vector[i], axis, op));
- }
-
- // Validate ReductionOperation on the last stage
- const unsigned int last_stage = num_of_stages - 1;
- ARM_COMPUTE_RETURN_ON_ERROR(CLArgMinMaxLayerKernel::validate(input, &sums_vector[last_stage - 1], &not_reshaped_output, axis, op));
- }
+ ARM_COMPUTE_RETURN_ON_ERROR(CLArgMinMaxLayerKernel::validate(input, &not_reshaped_output, axis, op));
ARM_COMPUTE_RETURN_ON_ERROR(CLReshapeLayer::validate(&not_reshaped_output, output));
return Status{};
}
@@ -116,58 +94,42 @@ void CLArgMinMaxLayer::configure(const ICLTensor *input, int axis, ICLTensor *ou
configure(CLKernelLibrary::get().get_compile_context(), input, axis, output, op);
}
-void CLArgMinMaxLayer::configure(const CLCompileContext &compile_context, const ICLTensor *input, int axis, ICLTensor *output, const ReductionOperation &op)
+void CLArgMinMaxLayer::configure(const CLCompileContext &compile_context,
+ const ICLTensor *input,
+ int axis,
+ ICLTensor *output,
+ const ReductionOperation &op)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
- _num_of_stages = utils::calculate_number_of_stages_only_x_axis(input->info()->dimension(0), axis);
- _reduction_axis = axis;
-
- const TensorShape output_shape = arm_compute::misc::shape_calculator::compute_reduced_shape(input->info()->tensor_shape(), axis, false);
- DataType output_data_type = (output->info()->data_type() == DataType::UNKNOWN) ? DataType::S32 : output->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));
+ ARM_COMPUTE_LOG_PARAMS(input, axis, output, op);
- // Configure reduction operation kernels
- _reduction_kernels_vector.reserve(_num_of_stages);
+ _reduction_axis = axis;
- auto add_reduction_kernel = [this, &compile_context, axis, op](const ICLTensor * input, const ICLTensor * prev_output, ICLTensor * output)
- {
- _reduction_kernels_vector.emplace_back(std::make_unique<CLArgMinMaxLayerKernel>());
- _reduction_kernels_vector.back()->configure(compile_context, input, prev_output, output, axis, op);
- };
+ const TensorShape output_shape =
+ arm_compute::misc::shape_calculator::compute_reduced_shape(input->info()->tensor_shape(), axis, false);
+ DataType output_data_type =
+ (output->info()->data_type() == DataType::UNKNOWN) ? DataType::S32 : output->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));
+
+ TensorShape not_reshaped_output_shape{input->info()->tensor_shape()};
+ not_reshaped_output_shape.set(axis, 1);
+ auto_init_if_empty(*_not_reshaped_output.info(), input->info()
+ ->clone()
+ ->set_tensor_shape(not_reshaped_output_shape)
+ .set_data_type(output_data_type)
+ .reset_padding()
+ .set_is_resizable(true));
+
+ _arg_min_max_kernel = std::make_unique<CLArgMinMaxLayerKernel>();
+ _arg_min_max_kernel->configure(compile_context, input, &_not_reshaped_output, axis, op);
_memory_group.manage(&_not_reshaped_output);
- // Create temporary tensors
- if(_num_of_stages == 1)
- {
- add_reduction_kernel(input, nullptr, &_not_reshaped_output);
- }
- else
- {
- _results_vector.resize(_num_of_stages - 1);
- TensorShape shape{ input->info()->tensor_shape() };
- for(unsigned int i = 0; i < _num_of_stages - 1; i++)
- {
- shape.set(0, ceil(shape.x() / 128.f));
- _results_vector[i].allocator()->init(input->info()->clone()->set_tensor_shape(shape).set_data_type(output_data_type));
- }
-
- // Apply ReductionOperation only on first kernel
- _memory_group.manage(&_results_vector[0]);
- add_reduction_kernel(input, nullptr, &_results_vector[0]);
-
- // Apply ReductionOperation on intermediate stages
- for(unsigned int i = 1; i < _num_of_stages - 1; ++i)
- {
- _memory_group.manage(&_results_vector[i]);
- add_reduction_kernel(input, &_results_vector[i - 1], &_results_vector[i]);
- _results_vector[i - 1].allocator()->allocate();
- }
-
- // Apply ReductionOperation on the last stage
- const unsigned int last_stage = _num_of_stages - 1;
- add_reduction_kernel(input, &_results_vector[last_stage - 1], &_not_reshaped_output);
- _results_vector[last_stage - 1].allocator()->allocate();
- }
+
_reshape.configure(compile_context, &_not_reshaped_output, output);
_not_reshaped_output.allocator()->allocate();
}
@@ -176,10 +138,7 @@ void CLArgMinMaxLayer::run()
{
MemoryGroupResourceScope scope_mg(_memory_group);
- for(unsigned int i = 0; i < _num_of_stages; ++i)
- {
- CLScheduler::get().enqueue(*_reduction_kernels_vector[i], false);
- }
+ CLScheduler::get().enqueue(*_arg_min_max_kernel, false);
_reshape.run();
}
} // namespace arm_compute
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-03 19:35:36 +0000