// CHECK-NEXT:  signature_defs: [ ]
// CHECK-NEXT:}

  %0 = "tfl.pseudo_const" () {value = dense<1.0> : tensor<4xf32>} : () -> tensor<4xf32> loc("Const")
  %1 = "tfl.mul"(%arg0, %0) {fused_activation_function = "NONE"} : (tensor<4xf32>, tensor<4xf32>) -> tensor<4xf32> loc("mul")
  // tf.MyCustomOp is the result of conversion to a Custom op

  %1 = "tfl.squared_difference"(%arg0, %0) {fused_activation_function = "NONE"} : (tensor<4xf32>, tensor<4xf32>) -> tensor<4xf32> loc("squared_difference")
  %2 = "tfl.mul"(%arg0, %1) {fused_activation_function = "NONE"} : (tensor<4xf32>, tensor<4xf32>) -> tensor<4xf32> loc("mul")
  %3 = "tfl.div"(%2, %1) {fused_activation_function = "NONE"} : (tensor<4xf32>, tensor<4xf32>) -> tensor<4xf32> loc("div")

  %2 = "tfl.mul"(%0, %1) {fused_activation_function = "NONE"} : (tensor<4xf32>, tensor<4xf32>) -> tensor<4xf32> loc("mul")
  func.return %2 : tensor<4xf32>

// CHECK-LABEL: main
// CHECK-NOT: tfl.squared_difference
// CHECK: tfl.mul %[[CONST:.*]], %arg0

  %1 = "tfl.mul"(%arg0, %0) {fused_activation_function = "NONE"} : (tensor<3x!quant.uniform<i8:f32, 0.1>>, tensor<3x!quant.uniform<i8:f32, 0.1>>) -> tensor<3x!quant.uniform<i8:f32, 0.1>> loc("mul")
  func.return %1 : tensor<3x!quant.uniform<i8:f32, 0.1>>

  %1 = "tfl.mul"(%arg0, %0) {fused_activation_function = "NONE"} : (tensor<3x!quant.uniform<i8:f32, 1.0>>, tensor<3x!quant.uniform<i8:f32, 1.0>>) -> tensor<3x!quant.uniform<i8:f32, 1.0>> loc("mul")
  func.return %1 : tensor<3x!quant.uniform<i8:f32, 1.0>>

//	then UV = u*v + x*(u*VV+v*UU) + x*x*UU*VV

func Mul(U, V PS) PS {
	Z := mkPS()
	go func() {
		<-Z.req
		uv := get2(U, V)
		if end(uv[0]) != 0 || end(uv[1]) != 0 {
			Z.dat <- finis
		} else {
			Z.dat <- mul(uv[0], uv[1])
			UU := Split(U)
			VV := Split(V)
			W := Add(Cmul(uv[0], VV[0]), Cmul(uv[1], UU[0]))
			<-Z.req
			Z.dat <- get(W)
			copy(Add(W, Mul(UU[1], VV[1])), Z)
		}
	}()
	return Z

// CHECK-NEXT:  signature_defs: [ ]
// CHECK-NEXT:}

  %0 = "tfl.pseudo_const" () {value = dense<1.0> : tensor<4xf32>} : () -> tensor<4xf32> loc("Const")
  %1 = "tfl.mul"(%arg0, %0) {fused_activation_function = "NONE"} : (tensor<4xf32>, tensor<4xf32>) -> tensor<4xf32> loc("mul")
  // tf.div is the result of conversion to a Flex TF op
  %2 = "tf.Div"(%1, %0)  : (tensor<4xf32>, tensor<4xf32>) -> tensor<4xf32> loc("div")

  // CHECK:  %[[IS_ZERO:.*]] = "tf.Equal"(%[[Y]], %[[ZERO]]) <{incompatible_shape_error = true}> : (tensor<3xf32>, tensor<f32>) -> tensor<3xi1>
  // CHECK:  %[[MUL:.*]] = "tf.Mul"(%[[X]], %[[Y]]) : (tensor<2x3xf32>, tensor<3xf32>) -> tensor<2x3xf32>
  // CHECK:  %[[RESULT:.*]] = "tf.SelectV2"(%[[IS_ZERO]], %[[ZERO]], %[[MUL]]) : (tensor<3xi1>, tensor<f32>, tensor<2x3xf32>) -> tensor<2x3xf32>
  %0 = "tf.MulNoNan"(%arg0, %arg1) : (tensor<2x3xf32>, tensor<3xf32>) -> tensor<2x3xf32>

// conditions are also hoisted (i.e., `tf.Add` and `tf.Mul`).

// CHECK-LABEL: readvariableop_is_hoisted_if_readonly
// CHECK:       [[CST_0:%.*]] = "tf.Const"
// CHECK:       [[VAR:%.*]] = "tf.VarHandleOp"
// CHECK:       [[CST_1:%.*]] = "tf.Const"
// CHECK:       [[VAR_VAL:%.*]] = "tf.ReadVariableOp"
// CHECK:       [[RES_1:%.*]] = "tf.Add"([[VAR_VAL]], [[CST_0]])
// CHECK:       [[RES_2:%.*]] = "tf.Mul"([[RES_1]], [[CST_1]])

	// X=Z1; Y=Z1; MUL; T-   // T1 = Z1*Z1
	// X-  ; Y=T ; MUL; R=T  // R  = Z1*T1
	// X=X2; Y-  ; MUL; H=T  // H  = X2*T1
	// X=Z2; Y=Z2; MUL; T-   // T2 = Z2*Z2
	// X-  ; Y=T ; MUL; S1=T // S1 = Z2*T2
	// X=X1; Y-  ; MUL; U1=T // U1 = X1*T2
	// SUB(H<H-T)            // H  = H-U1
	// X=Z1; Y=Z2; MUL; T-   // Z3 = Z1*Z2