// CHECK-LABEL: func @parallel_execute_with_tiled_input
  // CHECK-SAME: (%[[ARG_0:[a-z0-9]*]]: tensor<128x10xf32>, %[[ARG_1:[a-z0-9]*]]: tensor<128x10xf32>, %[[ARG_2:[a-z0-9]*]]: tensor<*xi32>, %[[ARG_3:[a-z0-9]*]]: tensor<*xi32>)
  func.func @parallel_execute_with_tiled_input(%arg0: tensor<128x10xf32>, %arg1: tensor<128x10xf32>, %arg2: tensor<*xi32>, %arg3: tensor<*xi32>) -> (tensor<*xi32>, tensor<*xi1>) {
    // CHECK: tf_device.replicate

func.func @invalidSelect(%arg0: tensor<1x8xi1>, %arg1: tensor<1x8x8xi32>, %arg2: tensor<1x8x8xi32>) -> tensor<1x8x8xi32> {
  // expected-error @+1 {{requires that pred is a scalar OR has the same rank as t and e OR is a vector}}
  %0 = "tf.Select"(%arg0, %arg1, %arg2) : (tensor<1x8xi1>, tensor<1x8x8xi32>, tensor<1x8x8xi32>) -> tensor<1x8x8xi32>
  func.return %0: tensor<1x8x8xi32>
}

// -----

}

func.func @concat_v2_i64_axis(%arg0: tensor<2x1xi32>, %arg1: tensor<2x1xi32>, %arg2: tensor<2x1xi32>) -> tensor<2x3xi32> {
  %0 = "tf.Const"() { value = dense<-1> : tensor<i64> } : () -> tensor<i64>
  %1 = "tf.ConcatV2"(%arg0, %arg1, %arg2, %0) : (tensor<2x1xi32>, tensor<2x1xi32>, tensor<2x1xi32>, tensor<i64>) -> tensor<2x3xi32>

    %3:2 = "tf.Split"(%0, %1) {device = ""} : (tensor<i32>, tensor<*xf32>) -> (tensor<*xf32>, tensor<*xf32>)
    %4 = tensor.cast %1 : tensor<*xf32> to tensor<?x?x?xf32>
    func.return %3#0, %3#1 : tensor<*xf32>, tensor<*xf32>
  }

  // CHECK-LABEL: infer_device_cluster
  func.func @infer_device_cluster(%arg0: tensor<1x8x2xi32>) -> (tensor<*xf32>, tensor<*xf32>) {

  %4 = "tf.Const"() {value = dense<2.000000e+00> : tensor<f32>} : () -> tensor<f32>
  %5 = "tf.Const"() {value = dense<0> : tensor<i32>} : () -> tensor<i32>
  %6 = "tf.Const"() {value = dense<[[0], [16]]> : tensor<2x1xi32>} : () -> tensor<2x1xi32>
  %7 = "tf.Const"() {value = dense<[32, 1]> : tensor<2xi32>} : () -> tensor<2xi32>
  %8 = "tf.Const"() {value = dense<4> : tensor<i32>} : () -> tensor<i32>

  cf.br ^exit
^exit:
  func.return %1: tensor<8x16x32x64xf32>

  // CHECK: return %arg0
}

// CHECK-LABEL: testConcatCanonicalization
func.func @testConcatCanonicalization(%arg0: tensor<2x1xi32>, %arg1: tensor<2x1xi32>) -> tensor<2x2xi32> {
  // CHECK: %[[AXIS:.*]] = "tf.Const"
  %0 = "tf.Const"() { value = dense<1> : tensor<i32> } : () -> tensor<i32>

  // expected-error @+1 {{op inferred type(s) 'tensor<2xi32>', 'tensor<2xi32>', 'tensor<2xi32>' are incompatible with return type(s) of operation 'tensor<2xi32>', 'tensor<2x1xi32>', 'tensor<2xi32>'}}
  %0:3 = "tfl.unpack"(%arg0) {axis = 1 : i32, num = 3 : i32} : (tensor<2x3xi32>) -> (tensor<2xi32>, tensor<2x1xi32>, tensor<2xi32>)
  func.return %0#0 : tensor<2xi32>
}

// -----