func @outside_compilation() -> tensor<f32> {
      %0 = "tf_device.cluster"() ( {
        %1 = "tf.Const"() {_xla_outside_compilation = "0", value = dense<1.0> : tensor<f32>} : () -> (tensor<f32>)
        %2 = "tf.Identity"(%1) {_xla_outside_compilation = "0"} : (tensor<f32>) -> (tensor<f32>)
        %3 = "tf.AddV2"(%1, %2) : (tensor<f32>, tensor<f32>) -> (tensor<f32>)
        tf_device.return %3 : tensor<f32>

  %0 = "tf.XlaAllReduce"(%input, %group_assignment) {reduce_op = "Add", mode = "CrossReplica"} : (tuple<tensor<f32>, tensor<f32>>, tensor<2x1xi32>) -> tuple<tensor<f32>, tensor<f32>>
  func.return %0 : tuple<tensor<f32>, tensor<f32>> 
}


// -----

// CHECK: module attributes

@testUnidirectionalSequenceLstmWithIntermediates(%arg0: tensor<? x ? x ? x f32>, %arg1: tensor<? x ? x f32>, %arg2: tensor<? x ? x f32>, %arg3: tensor<? x ? x f32>, %arg4: tensor<? x ? x f32>, %arg5: tensor<? x ? x f32>, %arg6: tensor<? x ? x f32>, %arg7: tensor<? x ? x f32>, %arg8: tensor<? x ? x f32>, %arg9: tensor<? x f32>, %arg10: tensor<? x f32>, %arg11: tensor<? x f32>, %arg12: tensor<? x f32>, %arg13: tensor<? x f32>, %arg14: tensor<? x f32>, %arg15: tensor<? x f32>, %arg16: tensor<? x ? x f32>, %arg17:...

}

func.func @branch0(%arg0: tensor<f32>, %arg1: tensor<f32>) -> tensor<f32> {
  %0 = "tf.Add" (%arg0, %arg1) {device = "/device:CPU:0"}  : (tensor<f32>, tensor<f32>) -> tensor<f32>
  func.return %0 : tensor<f32>
}

func.func @branch1(%arg0: tensor<f32>, %arg1: tensor<f32>) -> tensor<f32> {
  %0 = "tf.Add" (%arg0, %arg1) {device = "/device:CPU:0"}  : (tensor<f32>, tensor<f32>) -> tensor<f32>

// WHOLE-PASSES-DAG:  %[[rv2:.*]] = "tfl.read_variable"({{.*}}) : (tensor<*x!tf_type.resource<tensor<1x2x3x!quant.uniform<u8:f32, {{.*}}>>>>) -> tensor<1x2x3x!quant.uniform<u8:f32, {{.*}}>>

  func.return %6 : tensor<1x112x112x32x!quant.uniform<u8:f32, 0.023528476789885875>>
}

// DEBUG-LABEL: QuantizeSplit
func.func @QuantizeSplit(%arg: tensor<4x!quant.uniform<u8:f32, 1.0>>, %cst: tensor<i32>) -> (tensor<2x!quant.uniform<u8:f32, 1.0>>,tensor<2x!quant.uniform<u8:f32, 1.0>>) {
  %0 = "tfl.dequantize"(%arg) : (tensor<4x!quant.uniform<u8:f32, 1.0>>) -> tensor<4xf32>

      %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>>):