func.return %0 : tensor<*xi32>
}

// CHECK-LABEL: @ScatterNd
func.func @ScatterNd(%arg0: tensor<4x1xi32>, %arg1: tensor<4xf32>) -> tensor<8xf32> {
  // CHECK: %[[ZERO:.*]] = "tf.Const"() <{value = dense<0.000000e+00> : tensor<8xf32>}> : () -> tensor<8xf32>
  // CHECK: "tf.TensorScatterAdd"(%[[ZERO]], %arg0, %arg1) : (tensor<8xf32>, tensor<4x1xi32>, tensor<4xf32>) -> tensor<8xf32>

func.func @scatter_nd_add(%arg0: tensor<7xi64>, %arg1: tensor<1x1xi32>, %arg2: tensor<1xi64>) -> tensor<7xi64> {
  %0 = "tf.TensorScatterAdd"(%arg0, %arg1, %arg2) : (tensor<7xi64>, tensor<1x1xi32>, tensor<1xi64>) -> tensor<7xi64>
  func.return %0 : tensor<7xi64>

  // CHECK-LABEL: scatter_nd_add
  // CHECK:  %[[GATHER:.*]] = "tf.GatherNd"(%arg0, %arg1) <{bad_indices_policy = ""}> : (tensor<7xi64>, tensor<1x1xi32>) -> tensor<1xi64>

    %9 = "tf.BatchMatMulV2"(%6, %8) {adj_x = false, adj_y = false, device = ""} : (tensor<2x1x1024xi32>, tensor<1024x3xi32>) -> tensor<2x1x3xi32>
    %10 = "tf.AddV2"(%9, %cst_2) {device = ""} : (tensor<2x1x3xi32>, tensor<3xi32>) -> tensor<2x1x3xi32>
    %11 = "tf.Cast"(%10) {Truncate = false, device = ""} : (tensor<2x1x3xi32>) -> tensor<2x1x3xf32>
    %12 = "tf.Mul"(%11, %cst) {device = ""} : (tensor<2x1x3xf32>, tensor<f32>) -> tensor<2x1x3xf32>