Method mutate

src/graph/mutators/DepthConcatSubTensorMutator.cpp:50–114

}

void DepthConcatSubTensorMutator::mutate(Graph &g)
{
    // Early exit if no Concatenation layers exist in graph
    if (g.nodes(NodeType::ConcatenateLayer).empty())
    {
        return;
    }

    // Perform topological sort
    std::vector<NodeID> topological_sorted_node_ids = dfs(g);

    // Should be in reverse order of execution
    for (auto &node_id : arm_compute::utils::iterable::reverse_iterate(topological_sorted_node_ids))
    {
        INode *node = g.node(node_id);
        if (node != nullptr && node->type() == NodeType::ConcatenateLayer && node->output(0) != nullptr)
        {
            // Get output tensor
            auto output_tensor = node->output(0);

            // Check concatenation axis (Sub-tensor optimization is supported for concatenation axis >=2)
            auto *concat_node = arm_compute::utils::cast::polymorphic_downcast<ConcatenateLayerNode *>(node);
            if (output_tensor == nullptr ||
                get_dimension_idx(output_tensor->desc().layout, concat_node->concatenation_axis()) < 2)
            {
                continue;
            }

            // Check that all tensor have the same target, valid inputs and same quantization info
            bool is_valid =
                std::all_of(node->input_edges().cbegin(), node->input_edges().cend(),
                            [&](const EdgeID &eid)
                            {
                                return (g.edge(eid) != nullptr) && (g.edge(eid)->tensor() != nullptr) &&
                                       (g.edge(eid)->tensor()->desc().target == output_tensor->desc().target) &&
                                       (g.edge(eid)->tensor()->desc().quant_info == output_tensor->desc().quant_info);
                            });

            // Create subtensors
            if (is_valid && is_target_supported(output_tensor->desc().target))
            {
                ARM_COMPUTE_LOG_GRAPH_VERBOSE("Using sub-tensors for the node with ID : "
                                              << node->id() << " and name : " << node->name() << std::endl);
                // Create sub-tensor handles
                unsigned depth = 0;
                for (unsigned int i = 0; i < node->input_edges().size(); ++i)
                {
                    auto       input_tensor = node->input(i);
                    const auto input_shape  = input_tensor->desc().shape;

                    backends::IDeviceBackend &backend =
                        backends::BackendRegistry::get().get_backend(input_tensor->desc().target);
                    std::unique_ptr<ITensorHandle> handle =
                        backend.create_subtensor(output_tensor->handle(), input_shape, Coordinates(0, 0, depth), false);
                    input_tensor->set_handle(std::move(handle));

                    depth += input_shape.z();
                }