%0 = stablehlo.convert %arg0 : (tensor<1x2xf32>) -> tensor<1x2xi8>
    return %0 : tensor<1x2xi8>
  }
// CHECK: @uniform_quantize_0
  func.func private @uniform_quantize_1(%arg0: tensor<1x3xf32>, %arg1: tensor<1x1xf32>, %arg2: tensor<1x1xi8>) -> tensor<1x3xi8> {
    %0 = stablehlo.convert %arg0 : (tensor<1x3xf32>) -> tensor<1x3xi8>
    return %0 : tensor<1x3xi8>
  }

func.func @CheckLegacyQuantizeAdd() -> tensor<1x2x!quant.uniform<i8:f32, 0.0078431372549019607:-128>> {
  %cst = arith.constant dense<[[1.000000e+00, 2.000000e+00]]> : tensor<1x2xf32>
  %0 = "tfl.quantize"(%cst) {qtype = tensor<1x2x!quant.uniform<i8:f32, 0.0078431372549019607:-128>>, volatile} : (tensor<1x2xf32>) -> tensor<1x2x!quant.uniform<i8:f32, 0.0078431372549019607:-128>>
  func.return %0 : tensor<1x2x!quant.uniform<i8:f32, 0.0078431372549019607:-128>>

  // CHECK: %[[WHILE_RESULT:.*]]:2 = mhlo.while(%[[ARG0:.*]] = %[[INT0]], %[[ARG1:.*]] = %[[INT1]])
  // CHECK-SAME: tensor<2x2xi8>, tensor<2x2xi8>

  // CHECK: cond

  // CHECK: do
  // CHECK: mhlo.return %[[ARG0]], %[[ARG1]] : tensor<2x?xi8>, tensor<?x2xi8>

  %2:2 = "tf.WhileRegion"(%0, %1) ({
  ^bb0(%carg0: tensor<2x2x!tf_type.qint8>, %carg1: tensor<2x2x!tf_type.qint8>):

// WHOLE-PASSES-DAG:  %[[rv1:.*]] = "tfl.read_variable"({{.*}}) : (tensor<*x!tf_type.resource<tensor<1x2x3x!quant.uniform<u8:f32, {{.*}}>>>>) -> tensor<1x2x3x!quant.uniform<u8:f32, {{.*}}>>

  %0 = "tfl.pseudo_sparse_qconst"() {compressed_data = dense<[1, 2, 3, 4, -1, -2, -3, -4]> : tensor<8xi8>, qtype = tensor<3x2x!quant.uniform<u8<1:255>:f32, 1.0>>, s_param = #tfl.sparsity_parameter<traversal_order = [0, 1, 2, 3], block_map...

  %0 = "tfl.pseudo_sparse_qconst"() {compressed_data = dense<[1, 2, 3, 4, -1, -2, -3, -4]> : tensor<8xi8>, qtype = tensor<3x2x!quant.uniform<u8<1:255>:f32, 1.0>>, s_param = #tfl.sparsity_parameter<traversal_order = [0, 1, 2, 3], block_map...

    %cst_1 = "tfl.pseudo_qconst"() {qtype = tensor<1x20x!quant.uniform<i8:f32, 0.006:-34>>, value = dense<1> : tensor<1x20xi8>} : () -> tensor<1x20x!quant.uniform<i8:f32, 0.006:-34>>
    %cst_2 = "tfl.no_value"() {value = unit} : () -> none

// CHECK-SAME: tensor<1x3xf32>, tensor<1x3xf32>,
// CHECK-SAME: none, none, none, none)
// CHECK-SAME: -> tensor<1x2x3xf32>
// CHECK: "tfl.quantize"(%[[lstm]]) <{qtype = tensor<1x2x3x!quant.uniform<i16:f32, {{.*}}>>}> {volatile} : (tensor<1x2x3xf32>) -> tensor<1x2x3x!quant.uniform<i16:f32, {{.*}}>>

}

// CHECK-LABEL: QuantizeUnidirectionalLstmFullPerAxis

  %0 = "tfl.pseudo_const"() {value = dense<0> : tensor<1x2xi32>} : () -> tensor<1x2xi32>
  %1 = "tfl.pad"(%arg0, %0) : (tensor<15600xf32>, tensor<1x2xi32>) -> tensor<15600xf32>
  func.return %1 : tensor<15600xf32>
  // CHECK:  return %arg0
}

func.func @ConstFoldPadV2(%arg0: tensor<15600xf32>) -> tensor<15600xf32> {
  %0 = "tfl.pseudo_const"() {value = dense<0> : tensor<1x2xi32>} : () -> tensor<1x2xi32>

        }) : () -> tensor<f32>
        "tf_device.cluster"() ({
          %group = "tf.Const"() <{value = dense<[[0, 1]]> : tensor<1x2xi32>}> : () -> tensor<1x2xi32>
          %arg1_reduced = "tf.XlaAllReduce"(%arg1_id, %group) <{mode = "CrossReplica", reduce_op = "Add"}> : (tensor<f32>, tensor<1x2xi32>) -> tensor<f32>
          "tf.OpA"(%arg1_reduced) : (tensor<f32>) -> ()
          tf_device.return
        }) : () -> ()