// CHECK:           return %[[VAL_2]] : tensor<1x4xi8>
// CHECK:         }
func.func @bitwise_or_broadcast_chlo(%arg0: tensor<1xi8>, %arg1: tensor<1x4xi8>) -> tensor<1x4xi8> {
  %0 = "chlo.broadcast_or"(%arg0, %arg1) {broadcast_dimensions = array<i64: 1>} : (tensor<1xi8>, tensor<1x4xi8>) -> tensor<1x4xi8>
  func.return %0 : tensor<1x4xi8>
}

// CHECK-LABEL:   func @bitwise_or_dynamic(

  // CHECK: return %[[RESULT]] : tensor<1x4xi32>
  %sizes = "tf.Const"() {value = dense<[1, 4]> : tensor<2xi64>} : () -> (tensor<2xi64>)
  %0 = "tf.Slice"(%arg0, %arg1, %sizes) : (tensor<3x4xi32>, tensor<2xi64>, tensor<2xi64>) -> tensor<1x4xi32>
  func.return %0 : tensor<1x4xi32>
}

// -----

// CHECK-LABEL: slice_mhlo_sizes

  %cst_3 = arith.constant dense<[1, 0]> : tensor<2xi32>
  %79 = "tfl.pseudo_qconst"() {qtype = tensor<3x2x!quant.uniform<i8<-127:127>:f32:0, {2.378620e-03,2.848260e-03,2.545190e-03}>>, value = dense<10> : tensor<3x2xi8>} : () -> tensor<3x2x!quant.uniform<i8<-127:127>:f32:0, {2.378620e-03,2.848260e-03,2.545190e-03}>>