%3 = "tf.StringToNumber"(%arg1) {out_type = f32} : (tensor<!tf_type.string>) -> tensor<f32>
      "tf.Yield"(%3) : (tensor<f32>) -> ()
     },  {
      %4 = "tf.Const"() {value = dense<1.0> : tensor<f32>} : () -> tensor<f32>
      "tf.Yield"(%4) : (tensor<f32>) -> ()
    }) {is_stateless = true} : (tensor<i1>) -> (tensor<f32>)
    %5 = "tf.Identity"(%2) : (tensor<f32>) -> tensor<f32>
    tf_device.return %5 : tensor<f32>

         none, none, none,
         tensor<20x!quant.uniform<i8:f32, 0.006:-34>>, tensor<20x!quant.uniform<i8:f32, 0.006:-34>>, tensor<20x!quant.uniform<i8:f32, 0.006:-34>>, tensor<20x!quant.uniform<i8:f32, 0.006:-34>>,
         none, none,
         tensor<1x20x!quant.uniform<i8:f32, 0.006:-34>>, tensor<1x20x!quant.uniform<i16:f32, 0.006:-34>>,

  %0 = "tfl.pseudo_qconst"() { qtype = tensor<3x3x!quant.uniform<i32:f32:0, {1.0, 0.5:1, 0.25:1}>>, value = dense<1> : tensor<3x3xi32>} : () -> tensor<3x3x!quant.uniform<i32:f32:0, {1.0, 0.5:1, 0.25:1}>>
  func.return %0 : tensor<3x3x!quant.uniform<i32:f32:0, {1.0, 0.5:1, 0.25:1}>>
}

func.func @qu8() -> tensor<3x!quant.uniform<u8<1:255>:f32, 1.0>> {
  // CHECK-LABEL: @qu8

^bb0(%arg0: tensor<1x56x56x24x!quant.uniform<u8:f32, 0.27583434161017922:119>>, %arg1: tensor<1x56x56x24x!quant.uniform<u8:f32, 0.40149296779258581:136>>):

    %1 = "quantfork.dcast"(%0) : (tensor<2x2x3x2x!quant.uniform<i8<-127:127>:f32:3, {4.000000e-03,5.000000e-03}>>) -> tensor<*xf32>
    %2 = "quantfork.qcast"(%arg0) : (tensor<1x2x2x3xf32>) -> tensor<1x2x2x3x!quant.uniform<i8:f32, 8.000000e-03>>
    %3 = "quantfork.dcast"(%2) : (tensor<1x2x2x3x!quant.uniform<i8:f32, 8.000000e-03>>) -> tensor<*xf32>

    // CHECK: })
    %push = "tf.TensorListPushBack"(%arg0, %elem) : (tensor<!tf_type.variant<tensor<f32>>>, tensor<f32>) -> tensor<!tf_type.variant<tensor<f32>>>
    "tf.Yield"(%push, %sub) : (tensor<!tf_type.variant<tensor<f32>>>, tensor<i32>) -> ()
  }) : (tensor<!tf_type.variant<tensor<f32>>>, tensor<i32>) -> (tensor<!tf_type.variant<tensor<f32>>>, tensor<i32>)
  // CHECK: "tf.Slice"
  // CHECK-NOT: tf.TensorListPopBack

      "tf.AssignVariableOp"(%arg18, %9#0) : (tensor<*x!tf_type.resource<tensor<f32>>>, tensor<f32>) -> ()
      "tf.AssignVariableOp"(%arg19, %9#1) : (tensor<*x!tf_type.resource<tensor<f32>>>, tensor<f32>) -> ()

  %5 = "tfl.add"(%4, %arg3) {tac.device = "CPU", tac.inference_type = "QUANTIZED_INT8", fused_activation_function = "NONE"} : (tensor<1x384x128x!quant.uniform<i8:f32, 0.3:3>>, tensor<128x!quant.uniform<i8:f32, 0.2:-4>>) -> tensor<1x384x128x!quant.uniform<i8:f32, 0.3:-3>>
  func.return %5 : tensor<1x384x128x!quant.uniform<i8:f32, 0.3:-3>>
}

  %0 = stablehlo.constant dense<0xFF800000> : tensor<f32>  // -inf
  %1 = stablehlo.transpose %arg0, dims = [0, 3, 1, 2] : (tensor<1x16x16x4xf32>) -> tensor<1x4x16x16xf32>
  %2 = "stablehlo.reduce_window"(%1, %0) ({
  ^bb0(%arg1: tensor<f32>, %arg2: tensor<f32>):
      %3 = stablehlo.maximum %arg1, %arg2 : tensor<f32>
      stablehlo.return %3 : tensor<f32>

  %min = arith.constant dense<0.0> : tensor<f32>
  %max = arith.constant dense<255.0> : tensor<f32>
  %mini = "tf.Identity"(%min) : (tensor<f32>) -> tensor<f32>
  %maxi = "tf.Identity"(%max) : (tensor<f32>) -> tensor<f32>
  %minc = "tf.Cast"(%mini) : (tensor<f32>) -> tensor<f32>
  %maxc = "tf.Cast"(%maxi) : (tensor<f32>) -> tensor<f32>