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/*
* Copyright (c) 2017 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/graph/nodes/BranchLayer.h"
#include "arm_compute/graph/Graph.h"
#include "arm_compute/graph/SubGraph.h"
#include "arm_compute/graph/Tensor.h"
#include "arm_compute/runtime/IFunction.h"
#include "support/ToolchainSupport.h"
#include "utils/TypePrinter.h"
#include <memory>
#include <tuple>
#include <vector>
using namespace arm_compute::graph;
namespace
{
void depth_concatenate_output_info(ITensorInfo *info, ITensorInfo *sub_tensor_info)
{
ARM_COMPUTE_ERROR_ON(info == nullptr);
ARM_COMPUTE_ERROR_ON(sub_tensor_info == nullptr);
TensorShape info_shape = info->tensor_shape();
const TensorShape &sub_tensor_info_shape = sub_tensor_info->tensor_shape();
// Update parent info and valid region
if(info_shape.total_size() == 0)
{
arm_compute::auto_init_if_empty(*info,
sub_tensor_info->tensor_shape(),
sub_tensor_info->num_channels(),
sub_tensor_info->data_type(), sub_tensor_info->fixed_point_position());
info->set_valid_region(sub_tensor_info->valid_region());
}
else
{
ARM_COMPUTE_ERROR_ON(info->num_channels() != sub_tensor_info->num_channels());
ARM_COMPUTE_ERROR_ON(info->data_type() != sub_tensor_info->data_type());
ARM_COMPUTE_ERROR_ON(info->fixed_point_position() != sub_tensor_info->fixed_point_position());
// Concatenate depth
ARM_COMPUTE_ERROR_ON(info_shape.x() != sub_tensor_info_shape.x());
ARM_COMPUTE_ERROR_ON(info_shape.y() != sub_tensor_info_shape.y());
info_shape.set(2, info_shape.z() + sub_tensor_info_shape.z());
info->set_tensor_shape(info_shape);
// Update valid region
arm_compute::ValidRegion info_valid_region = info->valid_region();
info_valid_region.shape.set(2, info_shape.z());
arm_compute::ValidRegion updated_region = arm_compute::intersect_valid_regions(info_valid_region, sub_tensor_info->valid_region());
info->set_valid_region(updated_region);
}
}
} // namespace
/** Branch function */
class BranchFunction final : public arm_compute::IFunction
{
public:
/** Default Constructor */
BranchFunction()
: _graphs()
{
}
/** Registers graph to be executed by the branch function
*
* @param[in] graph Graph to register
*/
void register_graph(std::unique_ptr<Graph> graph)
{
_graphs.push_back(std::move(graph));
}
// Inherited methods overriden:
void run() override
{
for(auto &g : _graphs)
{
ARM_COMPUTE_ERROR_ON(g.get() == nullptr);
g->run();
}
}
private:
std::vector<std::unique_ptr<Graph>> _graphs;
};
std::unique_ptr<arm_compute::IFunction> BranchLayer::instantiate_node(GraphContext &ctx, ITensorObject *input, ITensorObject *output)
{
ARM_COMPUTE_ERROR_ON(_branch_merge_method != BranchMergeMethod::DEPTH_CONCATENATE);
ARM_COMPUTE_UNUSED(_branch_merge_method);
ARM_COMPUTE_ERROR_ON(input == nullptr || input->tensor() == nullptr);
ARM_COMPUTE_ERROR_ON(output == nullptr || output->tensor() == nullptr);
// Create branch function
auto func = arm_compute::support::cpp14::make_unique<BranchFunction>();
// Track output SubTensorInfo and depth
TensorInfo out_info;
int depth = 0;
// Constuct all sub-graphs given the input/output
for(auto &sg : _sub_graphs)
{
ARM_COMPUTE_ERROR_ON(sg.get() == nullptr);
// IO buffers
std::unique_ptr<ITensorObject> in;
std::unique_ptr<ITensorObject> out;
SubTensor *out_sub_tensor = nullptr;
// Create input sub-tensor
if(!sg->has_input())
{
ARM_COMPUTE_ERROR_ON(dynamic_cast<Tensor *>(input) == nullptr);
in = arm_compute::support::cpp14::make_unique<SubTensor>(*dynamic_cast<Tensor *>(input),
input->tensor()->info()->tensor_shape(),
Coordinates());
}
// Create output sub-tensor
if(!sg->has_output())
{
ARM_COMPUTE_ERROR_ON(dynamic_cast<Tensor *>(output) == nullptr);
out = arm_compute::support::cpp14::make_unique<SubTensor>(*dynamic_cast<Tensor *>(output),
output->tensor()->info()->tensor_shape(),
Coordinates(0, 0, depth));
out_sub_tensor = dynamic_cast<SubTensor *>(out.get());
}
// Construct sub_graph
auto g = sg->construct(ctx.hints().target_hint(), std::move(in), std::move(out));
// Register graph to function
func->register_graph(std::move(g));
// Update and track depth
if(out_sub_tensor != nullptr)
{
ARM_COMPUTE_ERROR_ON(out_sub_tensor->tensor() == nullptr);
depth += out_sub_tensor->tensor()->info()->tensor_shape()[2];
depth_concatenate_output_info(&out_info, out_sub_tensor->tensor()->info());
}
}
// Auto-init output
arm_compute::auto_init_if_empty(*output->tensor()->info(),
out_info.tensor_shape(),
out_info.num_channels(),
out_info.data_type(),
out_info.fixed_point_position());
return std::move(func);
}
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