}
	// stringtoslicebyte(*32[byte], string) []byte
	return mkcall("stringtoslicebyte", n.Type(), init, a, typecheck.Conv(s, types.Types[types.TSTRING]))
}

// walkStringToBytesTemp walks an OSTR2BYTESTMP node.
func walkStringToBytesTemp(n *ir.ConvExpr, init *ir.Nodes) ir.Node {
	// []byte(string) conversion that creates a slice
	// referring to the actual string bytes.
	// This conversion is handled later by the backend and

		if off&int64(types.PtrSize-1) != 0 {
			base.Fatalf("typebits.Set: invalid alignment, %v", t)
		}
		bv.Set(int32(off / int64(types.PtrSize))) // pointer

	case types.TSTRING:
		// struct { byte *str; intgo len; }
		if off&int64(types.PtrSize-1) != 0 {
			base.Fatalf("typebits.Set: invalid alignment, %v", t)
		}
		bv.Set(int32(off / int64(types.PtrSize))) //pointer in first slot

		// embed/embed.go type file is:
		//	name string
		//	data string
		//	hash [16]byte
		// Emit one of these per file in the set.
		const hashSize = 16
		hash := make([]byte, hashSize)
		for _, file := range files {
			off = objw.SymPtr(slicedata, off, StringSym(v.Pos(), file), 0) // file string
			off = objw.Uintptr(slicedata, off, uint64(len(file)))
			if strings.HasSuffix(file, "/") {
				// entry for directory - no data

      }
    }
  }

  if (!aliases.empty()) {
    strings::StrAppend(&comment, "\nAliases:\n");
    for (const auto& alias : aliases) {
      strings::StrAppend(&comment, "* ", alias, "\n");
    }
  }
  comment = MakeComment(comment, "");
}

string OpInfo::GetOpAttrStruct() const {
  string struct_fields;
  string setters;
  string defaults_static_storage;

	}
}

func TestABIUtilsSliceString(t *testing.T) {
	// func(p1 []int32, p2 int8, p3 []int32, p4 int8, p5 string,
	//      p6 int64, p6 []intr32) (r1 string, r2 int64, r3 string, r4 []int32)
	i32 := types.Types[types.TINT32]
	sli32 := types.NewSlice(i32)
	str := types.Types[types.TSTRING]
	i8 := types.Types[types.TINT8]
	i64 := types.Types[types.TINT64]

#include "tensorflow/compiler/mlir/tensorflow/utils/convert_tensor.h"

#include <cstdint>
#include <limits>
#include <optional>
#include <string>
#include <vector>

#include "absl/base/casts.h"
#include "absl/container/inlined_vector.h"
#include "absl/strings/str_cat.h"
#include "absl/strings/string_view.h"
#include "llvm/ADT/APFloat.h"
#include "llvm/ADT/ArrayRef.h"
#include "llvm/ADT/SmallVector.h"

  }

  TF_ASSIGN_OR_RETURN(string clustering_summary, SummarizeClustering(graphdef));

  // To update golden files flip this to true and run
  //
  // bazel test --test_strategy=local \
  //   tensorflow/compiler/jit/tests:auto_clustering_test
  bool update_golden = false;
  if (update_golden) {
    TF_RETURN_IF_ERROR(WriteStringToFile(
        Env::Default(), string(golden_summary_file_path), clustering_summary));

  }

  Status PRunSetup(const std::vector<string>& input_names,
                   const std::vector<string>& output_names,
                   const std::vector<string>& target_nodes,
                   string* handle) override {
    return absl::UnimplementedError("Session::PRunSetup()");
  }

  Status PRun(const string& handle,
              const std::vector<std::pair<string, Tensor>>& inputs,

	case TANY: // not a real type; should be replaced before use.
		base.Fatalf("CalcSize any")

	case TSTRING:
		if StringSize == 0 {
			base.Fatalf("early CalcSize string")
		}
		w = StringSize
		t.align = uint8(PtrSize)
		t.intRegs = 2
		t.setAlg(ASTRING)
		t.ptrBytes = int64(PtrSize)

	case TARRAY:
		if t.Elem() == nil {
			break
		}

		CalcSize(t.Elem())

			// Create temporary buffer for result string on stack.
			buf = stackBufAddr(tmpstringbufsize, types.Types[types.TUINT8])
		}
	}

	// build list of string arguments
	args := []ir.Node{buf}
	for _, n2 := range n.List {
		args = append(args, typecheck.Conv(n2, types.Types[types.TSTRING]))
	}

	var fn string
	if c <= 5 {
		// small numbers of strings use direct runtime helpers.