.Input(inputs)
          .Attr("Tin", {DT_RESOURCE})
          .Attr("Tout", {DT_RESOURCE})
          .Attr("f", f_name_attr)
          .Finalize(root.graph(), &call));
  call->AddAttr(std::string(kMustCompileAttr), true);

  TF_ASSERT_OK(root.ToGraph(&graph));

  // Required for passing the PS server parameter check.
  for (Node* node : graph.nodes()) {

    if (args[i]->output_type(0) == DT_RESOURCE &&
        variable_start_index == num_args) {
      variable_start_index = i;
    }
    (*input_permutation)[index] = i;
    args[i]->AddAttr("index", i);
  }
  VLOG(4) << "variable_start_index: " << variable_start_index;

  // Computes the permutation to produce the correct retval order, and update
  // the argument indices.

	if !internal.IgnorePC {
		var pcs [1]uintptr
		// skip [runtime.Callers, this function, this function's caller]
		runtime.Callers(3, pcs[:])
		pc = pcs[0]
	}
	r := NewRecord(time.Now(), level, msg, pc)
	r.AddAttrs(attrs...)
	if ctx == nil {
		ctx = context.Background()
	}
	_ = l.Handler().Handle(ctx, r)
}

// Debug calls [Logger.Debug] on the default logger.
func Debug(msg string, args ...any) {

and hidden fields that refer to state (such as attributes) indirectly. This
means that modifying a simple copy of a Record (e.g. by calling
[Record.Add] or [Record.AddAttrs] to add attributes)
may have unexpected effects on the original.
Before modifying a Record, use [Record.Clone] to
create a copy that shares no state with the original,
or create a new Record with [NewRecord]

          .node();

  TF_RETURN_IF_ERROR(main_scope.status());

  std::vector<string> compile_time_const_inputs;
  compile_time_const_inputs.push_back("size");
  (*result)->AddAttr(kXlaCompileTimeConstantInputsAttr,
                     compile_time_const_inputs);
  return status;
}

void ReplaceTensorFlowSliceWithStaticShapedSlice(Graph* g, Node* slice,

                               cluster_info.function);

  bool has_ref_attr;
  TF_RETURN_IF_ERROR(
      GetNodeAttr(n->attrs(), kXlaHasReferenceVarsAttr, &has_ref_attr));
  xla_compile.operation.node()->AddAttr(kXlaHasReferenceVarsAttr, has_ref_attr);
  TF_RETURN_IF_ERROR(
      CopyIncomingControlEdges(g, /*from=*/n, /*to=*/xla_compile.key.node()));

  std::vector<Output> xla_run_args =

pkg log/slog, method (*Logger) Warn(string, ...interface{}) #56345
pkg log/slog, method (*Logger) WithGroup(string) *Logger #56345
pkg log/slog, method (*Logger) With(...interface{}) *Logger #56345
pkg log/slog, method (*Record) AddAttrs(...Attr) #56345
pkg log/slog, method (*Record) Add(...interface{}) #56345
pkg log/slog, method (Record) Attrs(func(Attr) bool) #59060
pkg log/slog, method (Record) Clone() Record #56345

const TFE_OpAttrs* TFE_OpGetAttrs(const TFE_Op* op) {
  return tensorflow::wrap(tensorflow::unwrap(op)->GetOpAttrs());
}

void TFE_OpAddAttrs(TFE_Op* op, const TFE_OpAttrs* attrs) {
  tensorflow::unwrap(op)->AddAttrs(tensorflow::unwrap(attrs));
}

void TFE_OpAttrsSerialize(const TFE_OpAttrs* attrs, TF_Buffer* buf,
                          TF_Status* status) {
  tensorflow::NameAttrList name_and_attrs;