continue entries;
          }
        }
        if (outI < i) { // if outI == i don't bother writing the values back where they came from
          alternatingKeysAndValues[outKeyIndex] = key;
          alternatingKeysAndValues[outKeyIndex ^ 1] = value;
        }
        outI++;
      }
      return outI == n ? hashTable : new Object[] {hashTable, outI, duplicateKey};
    } else if (tableSize <= SHORT_MAX_SIZE) {
      /*

	if _, err := outf.Seek(int64(dwarfCmdOffset), 0); err != nil {
		return err
	}
	if _, err := io.CopyN(outf, bytes.NewReader(realdwarf.Raw()), int64(realdwarf.Len)); err != nil {
		return err
	}
	if _, err := outf.Seek(int64(unsafe.Offsetof(exem.FileHeader.Ncmd)), 0); err != nil {
		return err
	}
	if err := binary.Write(outf, exem.ByteOrder, exem.Ncmd+1); err != nil {
		return err
	}

func machoRewriteUuid(ctxt *Link, exef *os.File, exem *macho.File, outexe string) error {
	outf, err := os.OpenFile(outexe, os.O_RDWR|os.O_CREATE|os.O_TRUNC, 0755)
	if err != nil {
		return err
	}
	defer outf.Close()

	// Copy over the file.
	if _, err := io.Copy(outf, exef); err != nil {
		return err
	}

	// Locate the portion of the binary containing the load commands.

    private static class OptionComparator implements Comparator<Option> {
        public int compare(Option opt1, Option opt2) {
            String s1 = opt1.getOpt() != null ? opt1.getOpt() : opt1.getLongOpt();
            String s2 = opt2.getOpt() != null ? opt2.getOpt() : opt2.getLongOpt();
            return s1.compareToIgnoreCase(s2);
        }
    }

    private static class CLIManagerExtension extends CLIManager {

  );

  let results = (outs
    TF_NumberTensor:$out
  );

  TF_DerivedOperandTypeAttr T = TF_DerivedOperandTypeAttr<0>;
  TF_DerivedOperandTypeAttr Tidx = TF_DerivedOperandTypeAttr<1>;

  let hasVerifier = 1;
}

def TF_CumsumOp : TF_Op<"Cumsum", [Pure, TF_AllTypesMatch<["x", "out"]>]> {

  let description = [{
    Transfer a CPU tensor to device.

    Example:
      %device_tensor = gpurt.transfer_to_device %cpu_tensor
  }];

  let arguments = (ins TFTensorType);
  let results = (outs TFTensorType);
  let assemblyFormat = "operands attr-dict";
}

// TODO(b/260267885): We may add a device argument when we want to support
// GPU MIG.
def TransferFromDeviceOp: Gpu_Op<"transfer_from_device"> {

	SUBVU	R9, R5, R7
	AND	$7, R7
	BNE	R7, out1

	// if less than 8 bytes, do byte copying
	SGTU	$8, R6, R7
	BNE	R7, out1

	// do one byte at a time until 8-aligned
	AND	$7, R9, R8
	BEQ	R8, words1
	ADDV	$-1, R5
	MOVB	(R5), R7
	ADDV	$-1, R9
	MOVB	R7, (R9)
	JMP	-6(PC)

words1:
	// do 8 bytes at a time if there is room
	ADDV	$7, R4, R6 // R6 is start pointer+7

    $future: A value of type !mlrt.future. The underlying value must be a tensorflow tensor.

    $result: a tensorflow tensor.
  }];

  let arguments = (ins
    MlrtFutureType:$future
  );

  let results = (outs
    TF_Tensor:$result
  );
}

// tf_mlrt.tf_promise takes a tensorflow Tensor. It is a fake op that is only
// used during parallelization and has no runtime implementation.

			mustRun(t, cmd)

			cmd = hangProneCmd(outPath)
			cmd.Dir = dir.Base()
			outb, err := cmd.CombinedOutput()
			out := string(outb)
			if err == nil {
				t.Fatalf("fuzzing succeeded unexpectedly; output:\n%s", out)
			}
			if !strings.Contains(out, tc.expectedError) {
				t.Errorf("exited without expected error %q; got\n%s", tc.expectedError, out)
			}
		})
	}
}

out=$(diff -qpruN expanded_ns.txt decommissioned_ns.txt)
ret=$?
if [ $ret -ne 0 ]; then
	echo "BUG: expected no missing entries after decommission: $out"
	exit 1
fi

out=$(diff -qpruN expanded_ns_versions.txt decommissioned_ns_versions.txt)
ret=$?
if [ $ret -ne 0 ]; then
	echo "BUG: expected no missing entries after decommission: $out"
	exit 1
fi