}
		}
		var out []byte
		out, err = sh.runOut(p.Dir, nil, b.PkgconfigCmd(), "--cflags", pcflags, "--", pkgs)
		if err != nil {
			desc := b.PkgconfigCmd() + " --cflags " + strings.Join(pcflags, " ") + " -- " + strings.Join(pkgs, " ")
			return nil, nil, sh.reportCmd(desc, "", out, err)
		}
		if len(out) > 0 {
			cflags, err = splitPkgConfigOutput(bytes.TrimSpace(out))
			if err != nil {

	}

	outc := make(chan []byte, 1)
	go func() {
		b, err := io.ReadAll(out)
		if err != nil {
			t.Error(err)
		}
		outc <- b
	}()

	const msg = "O:Hello, pipe!\n"

	_, err = io.WriteString(in, msg)
	if err != nil {
		t.Fatal(err)
	}
	in.Close()

	b := <-outc
	if !bytes.Equal(b, []byte(msg)) {

			cmd := exec.Command(exe, []string{"-mode", s.mode}...)
			out, _ := cmd.CombinedOutput()
			outs := strings.ReplaceAll(string(out), "\n", " ")
			outs = strings.TrimSpace(outs)
			if s.expected != "" && s.expected != outs {
				t.Fatalf("failed%s mode %s: wanted %q\noutput:\n%s", bt,
					s.mode, s.expected, outs)
			}
			for _, need := range s.musthave {
				if !strings.Contains(outs, need) {

  );

  let results = (outs);
}


def TFL_HashtableSizeOp: TFL_Op<"hashtable_size", []> {
  let summary = "Computes the number of elements in the given table.";

  let arguments = (ins
    TFL_ResourceTensor:$hash_table
  );

  let results = (outs
    TFL_I64Tensor:$out
  );
}

def TFL_BroadcastArgsOp : TFL_Op<"broadcast_args",[

  let description = [{
    The ConstOp creates a constant tensorflow::Tensor from serialized proto.
  }];

  let arguments = (ins
    StrAttr:$tensor_proto
  );

  let results = (outs
    TFTensorType:$result
  );

  let assemblyFormat = "attr-dict";
}

def ExecuteOp : TensorflowMlrt_Op<"executeop", []> {
  let summary = "The Fallback ExecuteOp";
  let description = [{

	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.

    $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)
			}
		})
	}
}

ret=$?
function cleanup() {
  rm -f "${OUTPUT}"
}

trap cleanup EXIT

if [[ ${ret} -eq 0 ]];then
  cat "${OUTPUT}"
else
  # ignore NotFound errors
  OUT2=$(grep -v NotFound "${OUTPUT}")
  if [[ -n ${OUT2} ]];then
    cat "${OUTPUT}"
    exit ${ret}
  fi
fi

# wait for 30 sec for bookinfo to clean up
sleep 30