auto rhs_type = mlir::cast<RankedTensorType>(input_rhs.getType());

  // Skip int8 x int8 => int32.
  if (lhs_type.getElementType().isInteger(8) &&
      rhs_type.getElementType().isInteger(8)) {
    return rewriter.notifyMatchFailure(op,
                                       "skip unrolling for int8 BatchMatMulV3");
  }

  auto element_type = lhs_type.getElementType();

			break
		}
		n.SetType(t)
		return n

	case ir.OLSH, ir.ORSH:
		n := n.(*ir.BinaryExpr)
		n.X = convlit1(n.X, t, explicit, nil)
		n.SetType(n.X.Type())
		if n.Type() != nil && !n.Type().IsInteger() {
			base.Errorf("invalid operation: %v (shift of type %v)", n, n.Type())
			n.SetType(nil)
		}
		return n
	}

	if explicit {
		base.Fatalf("cannot convert %L to type %v", n, t)

	// within evconst. See #38117.
	if srcConstant && (src.IsInteger() || src.IsFloat() || src.IsComplex()) && (dst.IsInteger() || dst.IsFloat() || dst.IsComplex()) {
		return ir.OCONV, ""
	}

	// 6. src is an integer or has type []byte or []rune
	// and dst is a string type.
	if src.IsInteger() && dst.IsString() {
		return ir.ORUNESTR, ""
	}

	if src.IsSlice() && dst.IsString() {

		for _, b := range po {
			for i := len(b.Values) - 1; i >= 0; i-- {
				v := b.Values[i]
				if !loadAddr.contains(v.ID) {
					continue
				}
				for _, a := range v.Args {
					if a.Type.IsInteger() || a.Type.IsPtr() || a.Type.IsUnsafePtr() {
						loadAddr.add(a.ID)
					}
				}
			}
		}
		if loadAddr.size() == n {
			break
		}
	}

	change := true
	for change {
		change = false

	var toDelete []namedVal
	var newNames []*LocalSlot
	for i, name := range f.Names {
		t := name.Type
		switch {
		case t.IsInteger() && t.Size() > f.Config.RegSize:
			hiName, loName := f.SplitInt64(name)
			newNames = maybeAppend2(f, newNames, hiName, loName)
			for j, v := range f.NamedValues[*name] {
				if v.Op != OpInt64Make {
					continue

		return l, r, nil
	}

	r = DefaultLit(r, types.Types[types.TUINT])
	t := r.Type()
	if !t.IsInteger() {
		base.Errorf("invalid operation: %v (shift count type %v, must be integer)", n, r.Type())
		return l, r, nil
	}
	t = l.Type()
	if t != nil && t.Kind() != types.TIDEAL && !t.IsInteger() {
		base.Errorf("invalid operation: %v (shift of type %v)", n, t)
		return l, r, nil
	}

	// no DefaultLit for left

				cost := strCost * regexCost
				return &cost
			}
		}
	case "format.named":
		// Simply dictionary lookup
		cost := uint64(1)
		return &cost
	case "sign", "asInteger", "isInteger", "asApproximateFloat", "isGreaterThan", "isLessThan", "compareTo", "add", "sub":
		cost := uint64(1)
		return &cost
	}
	return nil
}

		}
		return -1
	}

	if isUntyped(x.typ) || isInteger(x.typ) {
		if val := constant.ToInt(x.val); val.Kind() == constant.Int {
			if representableConst(val, check, Typ[Int], nil) {
				if n, ok := constant.Int64Val(val); ok && n >= 0 {
					return n
				}
			}
		}
	}

	var msg string
	if isInteger(x.typ) {
		msg = "invalid array length %s"
	} else {

		}
		return -1
	}

	if isUntyped(x.typ) || isInteger(x.typ) {
		if val := constant.ToInt(x.val); val.Kind() == constant.Int {
			if representableConst(val, check, Typ[Int], nil) {
				if n, ok := constant.Int64Val(val); ok && n >= 0 {
					return n
				}
			}
		}
	}

	var msg string
	if isInteger(x.typ) {
		msg = "invalid array length %s"
	} else {

      Value handle = tensor_array_v3_op.getHandle();
      auto handle_type = mlir::cast<TensorType>(handle.getType());
      if (handle_type.getElementType().isInteger(/*width=*/32)) {
        Type resource_tensor_type =
            handle_type.clone(TF::ResourceType::get(rewriter.getContext()));
        handle.setType(resource_tensor_type);
      }
    }