// CHECK: %[[SUM0:.*]] = "tf.AddV2"(%arg0, %arg1)
  // CHECK: %[[SUM1:.*]] = "tf.AddV2"(%arg2, %arg3)
  // CHECK: %[[SUM2:.*]] = "tf.AddV2"(%[[SUM0]], %[[SUM1]])
  // CHECK: %[[SUM3:.*]] = "tf.AddV2"(%[[SUM2]], %arg4)
  // return %[[SUM3]]

//
// is lowered to:
//
//   %sum0 = "tf.AddV2"(%0, %1)
//   %result = "tf.AddV2"(%sum0, %2)
//
// While
//
//   %result = "tf.AddN"(%0, %1, %2, %3, %4)
//
// is lowered to:
//
//   %sum0 = "tf.AddV2"(%0, %1)
//   %sum1 = "tf.AddV2"(%2, %3)
//   %sum2 = "tf.AddV2"(%sum0, %sum1)
//   %result = "tf.AddV2"(%sum2, %4)
//
class LowerAddNOp : public RewritePattern {
 public:

        then:
        from.empty
        collection.from.empty

        when:
        def add1 = from.add('a')
        def add2 = from.add('b')
        def add3 = from.add('a')

        then:
        add1
        add2
        !add3

        and:
        from as List == ['a', 'b']
        collection.from as List == ['a', 'b']

        when:

  ops::Switch switch_b(root.WithOpName("switch_b"), value, cond_b);

  Output add_a = ops::Add(root.WithOpName("add_a"), switch_a.output_true,
                          switch_b.output_true);
  Output add_b = ops::Add(root.WithOpName("add_b"), switch_a.output_true,
                          switch_b.output_true);
  Output add = ops::Add(root.WithOpName("add_c"), add_a, add_b);

  std::unique_ptr<Graph> graph(new Graph(OpRegistry::Global()));

  %0 = "tf.AddV2"(%arg0, %arg1) : (tensor<ui32>, tensor<ui32>) -> tensor<ui32>
  func.return %0 : tensor<ui32>

  // CHECK-LABEL: add_v2_uint32
  // CHECK:  %[[CAST:.*]] = "tf.Cast"(%arg0) <{Truncate = false}> : (tensor<ui32>) -> tensor<i32>
  // CHECK:  %[[CAST1:.*]] = "tf.Cast"(%arg1) <{Truncate = false}> : (tensor<ui32>) -> tensor<i32>

          %add1 = "tf.Add"(%arg0, %arg1) : (tensor<*xi32>, tensor<i32>) -> tensor<*xi32>
          %add2 = "tf.Add"(%add1, %arg1) : (tensor<*xi32>, tensor<i32>) -> tensor<*xi32>
          %res = "tf.Print"(%add2) { message = "add result" } : (tensor<*xi32>) -> (tensor<*xi32>)
          tf_executor.yield %add1, %add2 : tensor<*xi32>, tensor<*xi32>
        }
        tf_executor.fetch %island1#0, %island1#1 : tensor<*xi32>, tensor<*xi32>

    %one:2 = tf_executor.island wraps "tf.Const"() { value = dense<1> : tensor<i32> } : () -> tensor<i32>
    %add2:2 = tf_executor.island wraps "tf.Add"(%arg0, %one#0) : (tensor<i32>, tensor<i32>) -> tensor<i32>
    tf_executor.fetch %add2#0, %arg1, %stack_push2#1 : tensor<i32>, tensor<f32>, !tf_executor.control
  }
  func.return %graph#0, %graph#1 : tensor<i32>, tensor<f32>
}

          activation_fn: The activation function to be used. No activation
            function if None.
          use_biasadd: If True, use BiasAdd for adding bias, else use AddV2.
        """
        self.bias_size = bias_size
        self.activation_fn = activation_fn
        self.use_biasadd = use_biasadd
        self.filters = np.random.uniform(low=-1.0, high=1.0, size=weight_shape)

		ssa.OpPPC64LoweredAtomicAdd64:
		// LWSYNC
		// LDAR/LWAR    (Rarg0), Rout
		// ADD		Rarg1, Rout
		// STDCCC/STWCCC Rout, (Rarg0)
		// BNE         -3(PC)
		// MOVW		Rout,Rout (if Add32)
		ld := ppc64.ALDAR
		st := ppc64.ASTDCCC
		if v.Op == ssa.OpPPC64LoweredAtomicAdd32 {
			ld = ppc64.ALWAR
			st = ppc64.ASTWCCC
		}
		r0 := v.Args[0].Reg()
		r1 := v.Args[1].Reg()
		out := v.Reg0()

// GOPPC64 values indicate power8, power9, etc.
// That means the code is compiled for that target,
// and will not run on earlier targets.
//
(Add(Ptr|64|32|16|8) ...) => (ADD ...)
(Add64F ...) => (FADD ...)
(Add32F ...) => (FADDS ...)

(Sub(Ptr|64|32|16|8) ...) => (SUB ...)
(Sub32F ...) => (FSUBS ...)
(Sub64F ...) => (FSUB ...)

(Min(32|64)F x y) && buildcfg.GOPPC64 >= 9 => (XSMINJDP x y)