// floating point negative abs
(FNEG (F(ABS|NABS) x)) => (F(NABS|ABS) x)

// floating-point fused multiply-add/sub
(F(ADD|SUB) (FMUL x y) z) && x.Block.Func.useFMA(v) => (FM(ADD|SUB) x y z)
(F(ADDS|SUBS) (FMULS x y) z) && x.Block.Func.useFMA(v) => (FM(ADDS|SUBS) x y z)

// Arch-specific inlining for small or disjoint runtime.memmove

  TF_Operation* add1 = Add(params_->body_inputs[0], params_->body_inputs[1],
                           params_->body_graph, s_, "add1");
  ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);
  TF_Operation* one = ScalarConst(1, params_->body_graph, s_);
  ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);
  TF_Operation* add2 = Add(add1, one, params_->body_graph, s_, "add2");

// in the range [addr, addr+span.elemsize).
//
// nosplit because it is used during write barriers and must not be preempted.
//
//go:nosplit
func (span *mspan) typePointersOfUnchecked(addr uintptr) typePointers {
	const doubleCheck = false
	if doubleCheck && span.objBase(addr) != addr {
		print("runtime: addr=", addr, " base=", span.objBase(addr), "\n")

        builder.opts().WithName("unstage").WithAttr("dtypes", {DT_FLOAT}));

    Node* add0 = ops::BinaryOp("Add", a, b, builder.opts().WithName("add0"));
    Node* add1 =
        ops::BinaryOp("Add", unstage, b, builder.opts().WithName("add1"));
    Node* relu0 = ops::UnaryOp("Relu", add0, builder.opts().WithName("relu0"));
    ops::UnaryOp("Relu", add1, builder.opts().WithName("relu1"));
    MakeStageNode(builder, "stage", {DT_FLOAT}, {relu0});

  // CHECK: %[[ADD0:.*]] = "tf.AddV2"(%[[OLD_SLICE0]], %[[UPDATE_SLICE0]])
  // CHECK: %[[UPDATE0:.*]] = "tf.XlaDynamicUpdateSlice"(%[[READ2]], %[[ADD0]]
  // CHECK-SAME: (tensor<5x3xf32>, tensor<1x3xf32>, tensor<2xi32>) -> tensor<5x3xf32>

  func.return %0 : tensor<2x3xf32>

// CHECK-NEXT: %[[ADD0:.*]] = "tf.RiscAdd"(%arg0, %arg1) : (tensor<2x3xf32>, tensor<2x3xf32>) -> tensor<*xf32>
// CHECK-NEXT: %[[ADD1:.*]] = "tf.RiscAdd"(%[[ADD0]], %arg2) : (tensor<*xf32>, tensor<2x3xf32>) -> tensor<*xf32>
// CHECK-NEXT: %[[ES:.*]] = "tf.EnsureShape"(%[[ADD1]]) <{shape = #tf_type.shape<2x3>}> : (tensor<*xf32>) -> tensor<2x3xf32>

)

func TestUint128AddSub(t *testing.T) {
	const add1 = 1
	const sub1 = -1
	tests := []struct {
		in   uint128
		op   int // +1 or -1 to add vs subtract
		want uint128
	}{
		{uint128{0, 0}, add1, uint128{0, 1}},
		{uint128{0, 1}, add1, uint128{0, 2}},
		{uint128{1, 0}, add1, uint128{1, 1}},
		{uint128{0, ^uint64(0)}, add1, uint128{1, 0}},
		{uint128{^uint64(0), ^uint64(0)}, add1, uint128{0, 0}},

  auto x = ops::Placeholder(root.WithOpName("x"), DT_FLOAT);
  auto add1 = ops::Add(root.WithOpName("add1"), x, x);
  add1.node()->AddAttr("_cluster", "cluster1");
  auto add2 = ops::Add(root.WithOpName("add2"), add1, add1);
  add2.node()->AddAttr("_cluster", "cluster2");
  auto out = ops::Mul(root.WithOpName("mul"), add1, add2);

  Graph graph_before_encapsulation(OpRegistry::Global());

      "    node_def {"
      "      name: 'add1'"
      "      op: 'Add'"
      "      input: 'read0:value:0'"
      "      input: 'read1:value:0'"
      "      attr {"
      "        key: 'T'"
      "        value {"
      "          type: DT_FLOAT"
      "        }"
      "      }"
      "    }"
      "    node_def {"
      "      name: 'add2'"
      "      op: 'Add'"
      "      input: 'add1:z:0'"

====

Then the version is considered a <<rich_versions.adoc#sec:required-version,required version>> which means that it should _minimally_ be `1.7.15` but can be upgraded by the engine (optimistic upgrade).

There is, however, a shorthand notation for <<rich_versions.adoc#sec:strict-version,strict versions>>, using the `!!` notation:

.Shorthand notation for strict dependencies
====