argLen: 0,
		reg:    regInfo{},
	},
	{
		name:   "FlagGT_UGT",
		argLen: 0,
		reg:    regInfo{},
	},
	{
		name:   "FlagGT_ULT",
		argLen: 0,
		reg:    regInfo{},
	},
	{
		name:    "MOVSSconst1",
		auxType: auxFloat32,
		argLen:  0,
		reg: regInfo{
			outputs: []outputInfo{
				{0, 239}, // AX CX DX BX BP SI DI
			},
		},
	},
	{

// JavaScript functions.
// Note: All JavaScript functions return a JavaScript array, which will cause
// one allocation to be created to track the Value.gcPtr for the Value finalizer.
var allocTests = []struct {
	argLen  int // The number of arguments to use for the syscall
	expected int // The expected number of allocations
}{
	// For less than or equal to 16 arguments, we expect 1 alloction:
	// - makeValue new(ref)
	{0,  1},

// for each architecture.
type Op int32

type opInfo struct {
	name              string
	reg               regInfo
	auxType           auxType
	argLen            int32 // the number of arguments, -1 if variable length
	asm               obj.As
	generic           bool      // this is a generic (arch-independent) opcode
	rematerializeable bool      // this op is rematerializeable

	cleanup = func() {} // no cleanup by default

	var argLen int
	for _, arg := range cmd.Args {
		argLen += len(arg)
	}

	// If we're not approaching 32KB of args, just pass args normally.
	// (use 30KB instead to be conservative; not sure how accounting is done)
	if !useResponseFile(cmd.Path, argLen) {
		return
	}

	tf, err := os.CreateTemp("", "args")
	if err != nil {

LogicalResult MatchReduceToArgMinMaxType2(mhlo::ReduceOp reduce_op,
                                          bool is_argmax);

// Base class for converting mhlo::ReduceOp to TF/TFL ArgMax/ArgMin ops.
template <typename Reduce, typename ArgReduce, typename BooleanReduce,
          bool is_argmax>
class ConvertReduceOpToArgMinMax : public OpConversionPattern<mhlo::ReduceOp> {
 public:

  if (!operand) return InvalidArgument("Unable to cast input to MlirTensor");
  operands_.push_back(operand->getValue());

  // Get the next ArgDef and use it to infer the derived attributes associated
  // to this input.
  const tensorflow::OpDef::ArgDef& arg_def =
      op_def_->input_arg(current_ods_input_++);
  Type expected_type;
  if (arg_def.type() != tensorflow::DT_INVALID) {
    Builder builder(context_);

//   func A2e(arr [] byte)
//   code page conversion from  819 to 1047
TEXT ·A2e(SB), NOSPLIT|NOFRAME, $0
	MOVD arg_base+0(FP), R2                        // pointer to arry of characters
	MOVD arg_len+8(FP), R3                         // count
	XOR  R0, R0
	XOR  R1, R1
	BYTE $0xA7; BYTE $0x15; BYTE $0x00; BYTE $0x82 // BRAS 1,(2+(256/2))

	// ASCII -> EBCDIC conversion table:

		case "CGO_CXXFLAGS", "CGO_CFLAGS", "CGO_FFLAGS", "GGO_LDFLAGS":
			ev.Changed = ev.Value != work.DefaultCFlags
		}
	}

	return ret
}

// argKey returns the KEY part of the arg KEY=VAL, or else arg itself.
func argKey(arg string) string {
	i := strings.Index(arg, "=")
	if i < 0 {
		return arg
	}
	return arg[:i]
}

func runEnv(ctx context.Context, cmd *base.Command, args []string) {

    const auto set_segment_sizes_attr =
        [&](const tensorflow::NameRangeMap& arg_ranges,
            const tensorflow::protobuf::RepeatedPtrField<
                tensorflow::OpDef::ArgDef>& args,
            llvm::StringRef attr_name) {
          std::vector<int32_t> values;
          values.reserve(args.size());
          for (const auto& arg : args) {
            auto range = arg_ranges.at(arg.name());

	// This can only happen when we are letting the kernel pick a port (laddr == nil)
	// and when there is no listener for the destination address.
	// It's hard to argue this is anything other than a kernel bug. If we
	// see this happen, rather than expose the buggy effect to users, we
	// close the fd and try again. If it happens twice more, we relent and
	// use the result. See also: