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/*
* Copyright (c) 2018-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to
* deal in the Software without restriction, including without limitation the
* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
* sell copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "arm_compute/runtime/NEON/functions/NEConcatenateLayer.h"
#include "arm_compute/runtime/NEON/functions/NEDepthConcatenateLayer.h"
#include "arm_compute/runtime/NEON/functions/NEWidthConcatenateLayer.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/ToolchainSupport.h"
namespace arm_compute
{
NEConcatenateLayer::NEConcatenateLayer()
: _concat_function(nullptr),
_hconcat_kernels(),
_num_inputs(0),
_axis(Window::DimX)
{
}
Status NEConcatenateLayer::validate_h_concatenate(const std::vector<ITensorInfo *> &inputs_vector, const ITensorInfo *output)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output);
ARM_COMPUTE_RETURN_ERROR_ON(inputs_vector.size() < 2);
// Output auto inizialitation if not yet initialized
TensorInfo tmp_output_info = *output->clone();
TensorShape output_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(inputs_vector, Window::DimY);
auto_init_if_empty(tmp_output_info, output_shape, 1, inputs_vector[0]->data_type());
unsigned int offset = 0;
for(const auto &input : inputs_vector)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input);
ARM_COMPUTE_RETURN_ON_ERROR(NEHeightConcatenateLayerKernel::validate(input, offset, &tmp_output_info));
offset += input->dimension(Window::DimY);
}
return Status{};
}
void NEConcatenateLayer::configure_h_concatenate(std::vector<ITensor *> inputs_vector, ITensor *output)
{
_num_inputs = inputs_vector.size();
std::vector<ITensorInfo *> inputs_vector_info;
for(unsigned int i = 0; i < _num_inputs; ++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, Window::DimY);
// 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(validate_h_concatenate(inputs_vector_info, output->info()));
unsigned int offset = 0;
_hconcat_kernels = arm_compute::support::cpp14::make_unique<NEHeightConcatenateLayerKernel[]>(_num_inputs);
for(unsigned int i = 0; i < _num_inputs; ++i)
{
_hconcat_kernels[i].configure(inputs_vector.at(i), offset, output);
offset += inputs_vector.at(i)->info()->dimension(Window::DimY);
}
}
void NEConcatenateLayer::configure(const std::vector<ITensor *> &inputs_vector, ITensor *output, DataLayoutDimension axis)
{
ARM_COMPUTE_ERROR_ON(output == nullptr);
_axis = get_data_layout_dimension_index(output->info()->data_layout(), axis);
switch(_axis)
{
case 0:
{
auto func = support::cpp14::make_unique<NEWidthConcatenateLayer>();
func->configure(inputs_vector, output);
_concat_function = std::move(func);
break;
}
case 1:
{
configure_h_concatenate(inputs_vector, output);
break;
}
case 2:
{
auto func = support::cpp14::make_unique<NEDepthConcatenateLayer>();
func->configure(inputs_vector, output);
_concat_function = std::move(func);
break;
}
default:
ARM_COMPUTE_ERROR("Concatenation is supported across width, height and depth only!");
}
}
Status NEConcatenateLayer::validate(const std::vector<ITensorInfo *> &inputs_vector, const ITensorInfo *output, DataLayoutDimension axis)
{
ARM_COMPUTE_RETURN_ERROR_ON(output == nullptr);
switch(get_data_layout_dimension_index(output->data_layout(), axis))
{
case 0:
ARM_COMPUTE_RETURN_ON_ERROR(NEWidthConcatenateLayer::validate(inputs_vector, output));
break;
case 1:
ARM_COMPUTE_RETURN_ON_ERROR(NEConcatenateLayer::validate_h_concatenate(inputs_vector, output));
break;
case 2:
ARM_COMPUTE_RETURN_ON_ERROR(NEDepthConcatenateLayer::validate(inputs_vector, output));
break;
default:
ARM_COMPUTE_RETURN_ERROR_MSG("Concatenation is supported across width and depth only!");
}
return Status{};
}
void NEConcatenateLayer::run()
{
switch(_axis)
{
case 0:
case 2:
{
ARM_COMPUTE_ERROR_ON(_concat_function == nullptr);
_concat_function->run();
break;
}
case 1:
{
for(unsigned i = 0; i < _num_inputs; ++i)
{
NEScheduler::get().schedule(_hconcat_kernels.get() + i, Window::DimY);
}
break;
}
default:
{
ARM_COMPUTE_ERROR("Axis not supported.");
break;
}
}
}
} // namespace arm_compute