inference-engine/thirdparty/fluid/modules/gapi/src/compiler/passes/kernels.cpp

   1 // This file is part of OpenCV project.
   2 // It is subject to the license terms in the LICENSE file found in the top-level directory
   3 // of this distribution and at http://opencv.org/license.html.
   4 //
   5 // Copyright (C) 2018-2019 Intel Corporation
   6
   7
   8 #include "precomp.hpp"
   9
  10 #include <ade/util/zip_range.hpp>   // util::indexed
  11 #include <ade/graph.hpp>
  12 #include <ade/passes/check_cycles.hpp>
  13
  14 #include "opencv2/gapi/gcompoundkernel.hpp" // compound::backend()
  15
  16 #include "compiler/gmodel.hpp"
  17 #include "compiler/passes/passes.hpp"
  18
  19 #include "api/gbackend_priv.hpp"
  20 #include "backends/common/gbackend.hpp"
  21 #include "compiler/gmodelbuilder.hpp"
  22 #include "logger.hpp"    // GAPI_LOG
  23
  24 namespace
  25 {
  26     struct ImplInfo
  27     {
  28         cv::GKernelImpl impl;
  29         cv::GArgs       in_args;
  30     };
  31
  32     // Generaly the algorithm is following
  33     //
  34     // 1. Get GCompoundKernel implementation
  35     // 2. Create GCompoundContext
  36     // 3. Run GCompoundKernel with GCompoundContext
  37     // 4. Build subgraph from imputs/outputs GCompoundKernel
  38     // 5. Replace compound node to subgraph
  39
  40     void expand(ade::Graph& g, ade::NodeHandle nh, const ImplInfo& impl_info)
  41     {
  42         cv::gimpl::GModel::Graph gr(g);
  43         auto compound_impl = cv::util::any_cast<cv::detail::GCompoundKernel>(impl_info.impl.opaque);
  44
  45         // GCompoundContext instantiates its own objects
  46         // in accordance with the RcDescs from in_args
  47         cv::detail::GCompoundContext context(impl_info.in_args);
  48         compound_impl.apply(context);
  49
  50         cv::GProtoArgs ins, outs;
  51         ins.reserve(context.m_args.size());
  52         outs.reserve(context.m_results.size());
  53
  54         // Inputs can be non-dynamic types.
  55         // Such inputs are not used when building a graph
  56         for (const auto& arg : context.m_args)
  57         {
  58             if (cv::gimpl::proto::is_dynamic(arg))
  59             {
  60                 ins.emplace_back(cv::gimpl::proto::rewrap(arg));
  61             }
  62         }
  63
  64         ade::util::transform(context.m_results, std::back_inserter(outs), &cv::gimpl::proto::rewrap);
  65
  66         cv::gimpl::GModelBuilder builder(g);
  67
  68         // Build the subgraph graph which will need to replace the compound node
  69         const auto& proto_slots = builder.put(ins, outs);
  70
  71         const auto& in_nhs  = std::get<2>(proto_slots);
  72         const auto& out_nhs = std::get<3>(proto_slots);
  73
  74         auto sorted_in_nhs  = cv::gimpl::GModel::orderedInputs(gr, nh);
  75         auto sorted_out_nhs = cv::gimpl::GModel::orderedOutputs(gr, nh);
  76
  77         // Reconnect expanded kernels from graph data objects
  78         // to subgraph data objects, then drop that graph data objects
  79         for (const auto& it : ade::util::zip(in_nhs, sorted_in_nhs))
  80         {
  81             const auto& subgr_in_nh = std::get<0>(it);
  82             const auto& comp_in_nh  = std::get<1>(it);
  83
  84             cv::gimpl::GModel::redirectReaders(gr, subgr_in_nh, comp_in_nh);
  85             gr.erase(subgr_in_nh);
  86         }
  87
  88         gr.erase(nh);
  89
  90         for (const auto& it : ade::util::zip(out_nhs, sorted_out_nhs))
  91         {
  92             const auto& subgr_out_nh = std::get<0>(it);
  93             const auto& comp_out_nh  = std::get<1>(it);
  94
  95             cv::gimpl::GModel::redirectWriter(gr, subgr_out_nh, comp_out_nh);
  96             gr.erase(subgr_out_nh);
  97         }
  98     }
  99 }
 100 // This pass, given the kernel package, selects a kernel implementation
 101 // for every operation in the graph
 102 void cv::gimpl::passes::resolveKernels(ade::passes::PassContext   &ctx,
 103                                        const gapi::GKernelPackage &kernels,
 104                                        const gapi::GLookupOrder   &order)
 105 {
 106     std::unordered_set<cv::gapi::GBackend> active_backends;
 107
 108     GModel::Graph gr(ctx.graph);
 109     for (const auto &nh : gr.nodes())
 110     {
 111         if (gr.metadata(nh).get<NodeType>().t == NodeType::OP)
 112         {
 113             auto &op = gr.metadata(nh).get<Op>();
 114             cv::gapi::GBackend selected_backend;
 115             cv::GKernelImpl    selected_impl;
 116             std::tie(selected_backend, selected_impl)
 117                 = kernels.lookup(op.k.name, order);
 118
 119             selected_backend.priv().unpackKernel(ctx.graph, nh, selected_impl);
 120             op.backend = selected_backend;
 121             active_backends.insert(selected_backend);
 122         }
 123     }
 124     gr.metadata().set(ActiveBackends{active_backends});
 125 }
 126
 127 void cv::gimpl::passes::expandKernels(ade::passes::PassContext &ctx, const gapi::GKernelPackage &kernels)
 128 {
 129     GModel::Graph gr(ctx.graph);
 130
 131     // Repeat the loop while there are compound kernels.
 132     // Restart procedure after every successfull unrolling
 133     bool has_compound_kernel = true;
 134     while (has_compound_kernel)
 135     {
 136         has_compound_kernel = false;
 137         for (const auto& nh : gr.nodes())
 138         {
 139             if (gr.metadata(nh).get<NodeType>().t == NodeType::OP)
 140             {
 141                 const auto& op = gr.metadata(nh).get<Op>();
 142
 143                 cv::gapi::GBackend selected_backend;
 144                 cv::GKernelImpl    selected_impl;
 145                 std::tie(selected_backend, selected_impl) = kernels.lookup(op.k.name);
 146
 147                 if (selected_backend == cv::gapi::compound::backend())
 148                 {
 149                     has_compound_kernel = true;
 150                     expand(ctx.graph, nh, ImplInfo{selected_impl, op.args});
 151                     break;
 152                 }
 153             }
 154         }
 155     }
 156     GAPI_LOG_INFO(NULL, "Final graph: " << ctx.graph.nodes().size() << " nodes" << std::endl);
 157 }