%2 = "tfl.conv_2d"(%arg0, %0, %1) {dilation_h_factor = 1 : i32, dilation_w_factor = 1 : i32, fused_activation_function = "NONE", padding = "SAME", stride_h = 1 : i32, stride_w = 1 : i32} : (tensor<1x32x32x8xf32>, tensor<16x1x1x8x!quant.uniform<i8:f32, 1.0>>, tensor<16x!quant.uniform<i32:f32, 1.0>>) -> tensor<1x32x32x16x!quant.uniform<i8:f32,...

                   i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32,
                   i32, i32, i32, i32, i32, i32, i32],
      Tout = [i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32,

  %2 = "tfl.pseudo_qconst"() {qtype = tensor<32x!quant.uniform<i32:f32, 1.7052092479439231E-4>>, value = dense<0> : tensor<32xi32>} : () -> tensor<32x!quant.uniform<i32:f32, 1.7052092479439231E-4>>

  %0 = "arith.constant"() {value = 42 : i32} : () -> i32
  %1 = "arith.constant"() {value = 41 : i32} : () -> i32
  %2 = "tfr.build_list"(%0, %1) : (i32, i32) -> !tfr.attr
  func.return %2 : !tfr.attr
}

// -----

// CHECK-LABEL: build_high_dim_const_list
func.func @build_high_dim_const_list() -> !tfr.attr {
  %0 = "arith.constant"() {value = 42 : i32} : () -> i32

  %max_iter = "tf.Const"() {__op_key = 1, value = dense<2> : tensor<i32>} : () -> tensor<i32>
  // CHECK: tf_mlrt.map_fn
  %result = "tf_mlrt.tf_map_fn"(%max_iter, %input2, %2) { operandSegmentSizes = array<i32: 1, 1, 1>, body_fn = @NopMapFnBody, num_tensor_list_or_flow_in = 1 : i32} : (tensor<i32>, tensor<!tf_type.variant<tensor<*xf32>>>, tensor<i32>) -> tensor<i32>
  return %result : tensor<i32>
}

// CHECK-LABEL: @NopMapFnBody

      %outputs_22, %control_23 = tf_executor.island wraps "tf.Const"() {device = "/device:CPU:0", value = dense<3> : tensor<i32>} : () -> tensor<i32>
      %outputs_24, %control_25 = tf_executor.island wraps "tf.LessEqual"(%outputs_0, %outputs_22) {device = "/device:CPU:0"} : (tensor<i32>, tensor<i32>) -> tensor<*xi1>

      %3 = "tf.opB"(%2, %arg0) : (tensor<i32>, tensor<i32>) -> tensor<i32>
      tf_executor.yield %3 : tensor<i32>
    }
    %4:2 = tf_executor.island {
      %5 = "tf.opC"(%1#0, %arg1) : (tensor<i32>, tensor<i32>) -> tensor<i32>
      %6 = "tf.opD"(%5, %arg0) : (tensor<i32>, tensor<i32>) -> tensor<i32>
      tf_executor.yield %6 : tensor<i32>
    }

    // core_tpu ops:
    %res_t = "tf.Identity"(%res_f) {_replication_info = "repl_info"} : (tensor<i32>) -> tensor<i32>

    // non_tpu_ops
    %res_n = "tf.Const"() {value = dense<2> : tensor<i32>} : () -> tensor<i32>

    return %res_n : tensor<i32>
  }
  func.func private @while_cond(%arg0: tensor<i32>) -> tensor<i1> {

    %outputs_7, %control_7 = tf_executor.island wraps "tf.AddV2"(%outputs_5, %outputs) {_xla_compile_device_type = "TPU", _replication_info = "cluster1"} : (tensor<i32>, tensor<i32>) -> tensor<i32>
    %outputs_8, %control_8 = tf_executor.island wraps "tf.AddV2"(%outputs_0, %outputs_3) {_xla_compile_device_type = "TPU"} : (tensor<i32>, tensor<i32>) -> tensor<i32>
    tf_executor.fetch
  }

  %zps2 = "tf.Const"() { value = dense<2> : tensor<i32> } : () -> tensor<i32>
  %zps4 = "tf.Const"() { value = dense<4> : tensor<i32> } : () -> tensor<i32>
  %one = "tf.Const"() { value = dense<1> : tensor<i32> } : () -> tensor<i32>

  // CHECK: %[[QUANT0:.*]] = mhlo.uniform_quantize %[[ARG:.*]] : (tensor<2x2xf32>) -> tensor<2x2x!quant.uniform<i8:f32, 1.000000e+00:2>>