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path: root/src/runtime/NEON/functions/NEConcatenateLayer.cpp
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-rw-r--r--src/runtime/NEON/functions/NEConcatenateLayer.cpp167
1 files changed, 37 insertions, 130 deletions
diff --git a/src/runtime/NEON/functions/NEConcatenateLayer.cpp b/src/runtime/NEON/functions/NEConcatenateLayer.cpp
index 61d41b44f8..59a0892f1f 100644
--- a/src/runtime/NEON/functions/NEConcatenateLayer.cpp
+++ b/src/runtime/NEON/functions/NEConcatenateLayer.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018-2020 ARM Limited.
+ * Copyright (c) 2018-2021 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -23,162 +23,69 @@
*/
#include "arm_compute/runtime/NEON/functions/NEConcatenateLayer.h"
-#include "arm_compute/core/NEON/kernels/NEBatchConcatenateLayerKernel.h"
-#include "arm_compute/core/NEON/kernels/NEDepthConcatenateLayerKernel.h"
-#include "arm_compute/core/NEON/kernels/NEHeightConcatenateLayerKernel.h"
-#include "arm_compute/core/NEON/kernels/NEWidthConcatenateLayerKernel.h"
-
-#include "arm_compute/core/utils/misc/ShapeCalculator.h"
-#include "arm_compute/runtime/NEON/NEScheduler.h"
-
#include "arm_compute/core/Error.h"
#include "arm_compute/core/ITensor.h"
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/Types.h"
-#include "support/MemorySupport.h"
+#include "arm_compute/core/utils/misc/ShapeCalculator.h"
+#include "arm_compute/runtime/NEON/NEScheduler.h"
+
+#include "src/core/helpers/AutoConfiguration.h"
+#include "src/cpu/operators/CpuConcatenate.h"
namespace arm_compute
{
-NEConcatenateLayer::NEConcatenateLayer()
- : _concat_kernels(),
- _num_inputs(0),
- _axis(Window::DimX)
+struct NEConcatenateLayer::Impl
{
-}
-
-void NEConcatenateLayer::configure(std::vector<ITensor *> inputs_vector, ITensor *output, size_t axis)
+ std::vector<const ITensor *> srcs{};
+ ITensor *dst{nullptr};
+ unsigned int num_inputs{0};
+ unsigned int axis{0};
+ std::unique_ptr<cpu::CpuConcatenate> op{nullptr};
+};
+
+NEConcatenateLayer::NEConcatenateLayer() : _impl(std::make_unique<Impl>())
{
- configure_internal(std::move(inputs_vector), output, axis);
}
+NEConcatenateLayer::NEConcatenateLayer(NEConcatenateLayer &&) = default;
+NEConcatenateLayer &NEConcatenateLayer::operator=(NEConcatenateLayer &&) = default;
+NEConcatenateLayer::~NEConcatenateLayer() = default;
void NEConcatenateLayer::configure(std::vector<const ITensor *> inputs_vector, ITensor *output, size_t axis)
{
- configure_internal(std::move(inputs_vector), output, axis);
-}
-
-Status NEConcatenateLayer::validate(const std::vector<ITensorInfo *> &inputs_vector, const ITensorInfo *output, size_t axis)
-{
- return validate_internal(inputs_vector, output, axis);
-}
-
-Status NEConcatenateLayer::validate(const std::vector<const ITensorInfo *> &inputs_vector, const ITensorInfo *output, size_t axis)
-{
- return validate_internal(inputs_vector, output, axis);
-}
-
-template <typename TensorType, typename>
-void NEConcatenateLayer::configure_internal(std::vector<TensorType *> &&inputs_vector, ITensor *output, size_t axis)
-{
ARM_COMPUTE_ERROR_ON(output == nullptr);
- _axis = axis;
- _num_inputs = inputs_vector.size();
- std::vector<ITensorInfo *> inputs_vector_info;
- inputs_vector_info.reserve(_num_inputs);
- for(unsigned int i = 0; i < _num_inputs; ++i)
+ _impl->srcs = inputs_vector;
+ _impl->dst = output;
+ _impl->axis = axis;
+ _impl->num_inputs = inputs_vector.size();
+ _impl->op = std::make_unique<cpu::CpuConcatenate>();
+
+ std::vector<const ITensorInfo *> inputs_vector_info;
+ for (unsigned int i = 0; i < inputs_vector.size(); ++i)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(inputs_vector.at(i));
inputs_vector_info.emplace_back(inputs_vector.at(i)->info());
}
- TensorShape output_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(inputs_vector, _axis);
-
- // Output auto inizialitation if not yet initialized
- auto_init_if_empty(*output->info(), output_shape, 1, inputs_vector[0]->info()->data_type());
- ARM_COMPUTE_ERROR_THROW_ON(NEConcatenateLayer::validate(inputs_vector_info, output->info(), axis));
-
- unsigned int offset = 0;
-
- for(unsigned int i = 0; i < _num_inputs; ++i)
- {
- switch(_axis)
- {
- case Window::DimX:
- {
- auto kernel = support::cpp14::make_unique<NEWidthConcatenateLayerKernel>();
- kernel->configure(inputs_vector.at(i), offset, output);
- _concat_kernels.emplace_back(std::move(kernel));
- break;
- }
- case Window::DimY:
- {
- auto kernel = support::cpp14::make_unique<NEHeightConcatenateLayerKernel>();
- kernel->configure(inputs_vector.at(i), offset, output);
- _concat_kernels.emplace_back(std::move(kernel));
- break;
- }
- case Window::DimZ:
- {
- auto kernel = support::cpp14::make_unique<NEDepthConcatenateLayerKernel>();
- kernel->configure(inputs_vector.at(i), offset, output);
- _concat_kernels.emplace_back(std::move(kernel));
- break;
- }
- case 3:
- {
- auto kernel = support::cpp14::make_unique<NEBatchConcatenateLayerKernel>();
- kernel->configure(inputs_vector.at(i), offset, output);
- _concat_kernels.emplace_back(std::move(kernel));
- break;
- }
- default:
- ARM_COMPUTE_ERROR("Axis not supported");
- }
- offset += inputs_vector.at(i)->info()->dimension(_axis);
- }
+ _impl->op->configure(inputs_vector_info, _impl->dst->info(), axis);
}
-template <typename TensorInfoType, typename>
-Status NEConcatenateLayer::validate_internal(const std::vector<TensorInfoType *> &inputs_vector, const ITensorInfo *output, size_t axis)
+Status NEConcatenateLayer::validate(const std::vector<const ITensorInfo *> &inputs_vector,
+ const ITensorInfo *output,
+ size_t axis)
{
- ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output);
- ARM_COMPUTE_RETURN_ERROR_ON(inputs_vector.size() < 2);
-
- unsigned int offset = 0;
- for(const auto &input : inputs_vector)
- {
- ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input);
- switch(axis)
- {
- case Window::DimX:
- {
- ARM_COMPUTE_RETURN_ON_ERROR(NEWidthConcatenateLayerKernel::validate(input, offset, output));
- break;
- }
- case Window::DimY:
- {
- ARM_COMPUTE_RETURN_ON_ERROR(NEHeightConcatenateLayerKernel::validate(input, offset, output));
- break;
- }
- case Window::DimZ:
- {
- ARM_COMPUTE_RETURN_ON_ERROR(NEDepthConcatenateLayerKernel::validate(input, offset, output));
- break;
- }
- case 3:
- {
- ARM_COMPUTE_RETURN_ON_ERROR(NEBatchConcatenateLayerKernel::validate(input, offset, output));
- break;
- }
- default:
- ARM_COMPUTE_ERROR("Axis not supported");
- }
- offset += input->dimension(axis);
- }
-
- if(output->total_size() != 0)
- {
- TensorShape output_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(inputs_vector, axis);
- ARM_COMPUTE_RETURN_ERROR_ON(output_shape.total_size() != output->tensor_shape().total_size());
- }
-
- return Status{};
+ return cpu::CpuConcatenate::validate(inputs_vector, output, axis);
}
void NEConcatenateLayer::run()
{
- for(auto &kernel : _concat_kernels)
+ ITensorPack pack;
+ for (unsigned i = 0; i < _impl->num_inputs; ++i)
{
- NEScheduler::get().schedule(kernel.get(), Window::DimY);
+ pack.add_tensor(TensorType::ACL_SRC_VEC + i, _impl->srcs.at(i));
}
+ pack.add_tensor(TensorType::ACL_DST, _impl->dst);
+
+ _impl->op->run(pack);
}
} // namespace arm_compute
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-05 17:19:12 +0000