Function InlineFunctionBody

tensorflow/core/common_runtime/function.cc:1893–2176

Function inlining must preserve function execution semantics with regards to side-effects visibility. Tensorflow in Eager mode has an automatic control dependencies tracking mechanism, which enforces well-defined execution order of all side-effects. Any other frontend (e.g. Swift) must produce graphs following the same rules, to ensure that function inlining works correctly. IMPORTANT: Currently

//
// TODO(ezhulenev): Documentation above is ahead of implementation below.
Status InlineFunctionBody(const FunctionLibraryDefinition& flib_def, Graph* g,
                          Node* caller, const FunctionBody* fbody,
                          const InlineFunctionBodyOptions& options) {
  VLOG(3) << "Inline function call: " << SummarizeNode(*caller) << " ["
          << options.DebugString() << "]";
  VLOG(5) << "Inlined function definition: " << DebugString(fbody->fdef);

  Status validation = ValidateInlining(caller, fbody, options);
  if (!validation.ok()) {
    return errors::Internal("Inlining mismatch: ", validation.error_message());
  }

  // Placer is responsible for assigning devices for all nodes that we will add
  // to the graph.
  const std::unique_ptr<InlinedFunctionBodyPlacer> placer =
      options.inlined_function_body_placer.get(*g, *caller);

  // We can't possibly introduce a duplicate control edge during function
  // inlining, so we skip this check in calls to the 'g->AddControlEdge(...)'.
  static constexpr bool kDoNotCheckDuplicates = true;

  // ------------------------------------------------------------------------ //
  // Helper functions to create `NoOp` and `Identity` nodes for auxiliary
  // control nodes and inlined function inputs and outputs.

  // Add a NoOp node for function control inputs/outputs.
  const auto no_op = [&](StringPiece name) -> Node* {
    Node* node = AddNoOp(absl::StrCat(caller->name(), "/", name), g);
    const absl::optional<string> device = placer->ControlNodeDevice();
    if (device.has_value()) node->set_requested_device(*device);
    return node;
  };

  // Add an Identity node for function input.
  const auto input_identity = [&](StringPiece name, Endpoint input,
                                  int index) -> Node* {
    Node* node = AddIdentity(absl::StrCat(caller->name(), "/", name), g, input);
    const absl::optional<string> device = placer->InputNodeDevice(index);
    if (device.has_value()) node->set_requested_device(*device);
    return node;
  };

  // Add an Identity node for function output.
  const auto output_identity = [&](StringPiece name, Endpoint input,
                                   int index) -> Node* {
    Node* node = AddIdentity(absl::StrCat(caller->name(), "/", name), g, input);
    const absl::optional<string> device = placer->OutputNodeDevice(index);
    if (device.has_value()) node->set_requested_device(*device);
    return node;
  };

  // ------------------------------------------------------------------------ //
  // Input edges. For data edges coming into "caller", we first compute the
  // <src>:<src_output> for the i-th input in "inputs".
  // If "caller" has any input control dependencies, we add a NoOp
  // node "input_control_node", which depends on "caller"'s control inputs.
  std::vector<Endpoint> inputs(caller->num_inputs());
  Node* input_control_node = nullptr;