(TF_ConstOp:$res DenseElementsAttr:$value),
  (Arith_ConstantOp $value),
  [(AnyStaticShapeTensor $res)], [], (addBenefit 10)>;

//===----------------------------------------------------------------------===//
// Unary ops patterns.
//===----------------------------------------------------------------------===//
def IsDataFormatNHWC : ConstantAttr<TF_ConvnetDataFormatAttr, "\"NHWC\"">;

	switch x := x.(type) {
	case *Name:
		return x, nil
	case *Operation:
		if x.Y == nil {
			break // unary expr
		}
		switch x.Op {
		case Mul:
			if name, _ := x.X.(*Name); name != nil && (force || isTypeElem(x.Y)) {
				// x = name *x.Y
				op := *x
				op.X, op.Y = op.Y, nil // change op into unary *op.Y
				return name, &op
			}
		case Or:

}

// is63bit reports whether x can be represented using 63 bits.
func is63bit(x int64) bool {
	const s = 63
	return -1<<(s-1) <= x && x <= 1<<(s-1)-1
}

// UnaryOp returns the result of the unary expression op y.
// The operation must be defined for the operand.
// If prec > 0 it specifies the ^ (xor) result size in bits.
// If y is [Unknown], the result is [Unknown].

  });
  if (!args_same_op) return failure();

  // Collect unary operations operands.
  auto unary_operands = llvm::map_range(op.getValues(), [](Value arg) -> Value {
    return arg.getDefiningOp()->getOperand(0);
  });
  SmallVector<Value, 8> unary_ops_args(unary_operands);

  // Concatenate unary ops operands.
  auto concat_unary_operands = CreateTfOp<ConcatV2Op>(

          (TF_ModOp $l, $r),
          [(IsLegalNumpyRankedBroadcast $l, $r, $broadcast_dimensions)]>;

//===----------------------------------------------------------------------===//
// Unary op patterns.
//===----------------------------------------------------------------------===//

def : Pat<(MHLO_ConvertOp MHLO_Tensor:$operand),
          (TF_CastOp $operand, ConstBoolAttrFalse)>;

	case *CallExpr:
		p.print(n.Fun, _Lparen)
		p.printExprList(n.ArgList)
		if n.HasDots {
			p.print(_DotDotDot)
		}
		p.print(_Rparen)

	case *Operation:
		if n.Y == nil {
			// unary expr
			p.print(n.Op)
			// if n.Op == lexical.Range {
			// 	p.print(blank)
			// }
			p.print(n.X)
		} else {
			// binary expr
			// TODO(gri) eventually take precedence into account

			return &ast.ChanType{pos, ast.RECV, value}
		}

		x := p.parseUnaryExpr(false)
		return &ast.UnaryExpr{pos, token.ARROW, p.checkExpr(x)}

	case token.MUL:
		// pointer type or unary "*" expression
		pos := p.pos
		p.next()
		x := p.parseUnaryExpr(false)
		return &ast.StarExpr{pos, p.checkExprOrType(x)}
	}

	return p.parsePrimaryExpr(lhs)
}

	{name: "binary", format: "package main; var x = «1+»1"},
	{name: "binaryparen", format: "package main; var x = «1+(«1»)»", parseMultiplier: 2}, // Parser nodes: BinaryExpr, ParenExpr
	{name: "unary", format: "package main; var x = «^»1"},
	{name: "addr", format: "package main; var x = «& »x"},
	{name: "star", format: "package main; var x = «*»x"},
	{name: "recv", format: "package main; var x = «<-»x"},

  if (dim_size != op.getNumResults())
    return op.emitOpError("result count must be equal to ") << dim_size;

  return success();
}

namespace {

// Hoist coefficient-wise unary operation out of the Unpack op:
//
//   %unpacked:N = "tf.Unpack"(%0)
//   %neg0 = "tf.Neg"(%unpacked#0)
//   %neg1 = "tf.Neg"(%unpacked#1)
//   ...
//   %negN-1 = "tf.Neg"(%unpacked:N-1)
//

			n.SetType(nil)
			return n
		}
		base.Errorf("%v is not a type", l)
		return n
	}

	n.SetType(t.Elem())
	return n
}

// tcUnaryArith typechecks a unary arithmetic expression.
func tcUnaryArith(n *ir.UnaryExpr) ir.Node {
	n.X = Expr(n.X)
	l := n.X
	t := l.Type()
	if t == nil {
		n.SetType(nil)
		return n
	}
	if !okfor[n.Op()][defaultType(t).Kind()] {