got := pat1.conflictsWith(pat2)
		if got != test.want {
			t.Errorf("%q.ConflictsWith(%q) = %t, want %t",
				test.p1, test.p2, got, test.want)
		}
		// conflictsWith should be commutative.
		got = pat2.conflictsWith(pat1)
		if got != test.want {
			t.Errorf("%q.ConflictsWith(%q) = %t, want %t",
				test.p2, test.p1, got, test.want)
		}
	}
}

func TestRegisterConflict(t *testing.T) {

	// may be a nonzero exponent exp. The radix point amounts to a
	// division by base**(-fcount), which equals a multiplication by
	// base**fcount. An exponent means multiplication by ebase**exp.
	// Multiplications are commutative, so we can apply them in any
	// order. We only have powers of 2 and 10, and we split powers
	// of 10 into the product of the same powers of 2 and 5. This
	// may reduce the size of shift/multiplication factors or

(I64ShrU (I64Const [x]) (I64Const [y])) => (I64Const [int64(uint64(x) >> uint64(y))])
(I64ShrS (I64Const [x]) (I64Const [y])) => (I64Const [x >> uint64(y)])

// TODO: declare these operations as commutative and get rid of these rules?
(I64Add (I64Const [x]) y) && y.Op != OpWasmI64Const => (I64Add y (I64Const [x]))
(I64Mul (I64Const [x]) y) && y.Op != OpWasmI64Const => (I64Mul y (I64Const [x]))

// loaded by LOAD_KEY, and key size information held in CR1EQ/CR2EQ.
//
// Vxor is ideally V6 (Key[0-3]), but for slightly improved encrypting
// performance V6 and IVEC can be swapped (xor is both associative and
// commutative) during encryption:
//
//	VXOR INOUT, IVEC, INOUT
//	VXOR INOUT, V6, INOUT
//
//	into
//
//	VXOR INOUT, V6, INOUT
//	VXOR INOUT, IVEC, INOUT
//

	}
	for i, tt := range tests {
		if got := tt.a.Overlaps(tt.b); got != tt.want {
			t.Errorf("%d. (%v).Overlaps(%v) = %v; want %v", i, tt.a, tt.b, got, tt.want)
		}
		// Overlaps is commutative
		if got := tt.b.Overlaps(tt.a); got != tt.want {
			t.Errorf("%d. (%v).Overlaps(%v) = %v; want %v", i, tt.b, tt.a, got, tt.want)
		}
	}
}

// Sink variables are here to force the compiler to not elide

			goto replacedStart
		}
		panic(fmt.Sprintf("unreachable, ind: %v, start: %v, end: %v", ind, start, end))
	replacedStart:

		if nxt.Args[0] != ind {
			// unlike additions subtractions are not commutative so be sure we get it right
			nxt.Args[0], nxt.Args[1] = nxt.Args[1], nxt.Args[0]
		}

		switch nxt.Op {
		case OpAdd8:
			nxt.Op = OpSub8
		case OpAdd16:
			nxt.Op = OpSub16
		case OpAdd32:

  let results = (outs
    TF_NumberNotQuantizedOrStrTensor:$z
  );

  TF_DerivedOperandTypeAttr T = TF_DerivedOperandTypeAttr<0>;

  let hasCanonicalizer = 1;
}

def TF_AddNOp : TF_Op<"AddN", [Commutative, Pure]> {
  let summary = "Add all input tensors element wise.";

  let description = [{
Inputs must be of same size and shape.

  ```python
  x = [9, 7, 10]
  tf.math.add_n(x) ==> 26
  ```

// LEAQ is rematerializeable, so this helps to avoid register spill.
// See issue 22947 for details
(ADD(Q|L)const [off] x:(SP)) => (LEA(Q|L) [off] x)

// HMULx is commutative, but its first argument must go in AX.
// If possible, put a rematerializeable value in the first argument slot,
// to reduce the odds that another value will be have to spilled
// specifically to free up AX.

t := max("", "foo", "bar")  // t == "foo" (string kind)
</pre>

<p>
For numeric arguments, assuming all NaNs are equal, <code>min</code> and <code>max</code> are
commutative and associative:
</p>

<pre>
min(x, y)    == min(y, x)
min(x, y, z) == min(min(x, y), z) == min(x, min(y, z))
</pre>

<p>