func.func @listPopBack(%arg0: tensor<!tf_type.variant<tensor<2xi32>>>, %arg1: tensor<1xi32>) -> (tensor<!tf_type.variant<tensor<2xi32>>>, tensor<2xi32>)  {
  %0, %1 = "tf.TensorListPopBack"(%arg0, %arg1) : (tensor<!tf_type.variant<tensor<2xi32>>>, tensor<1xi32>) -> (tensor<!tf_type.variant<tensor<2xi32>>>, tensor<2xi32>)

// CHECK-SAME:                                        %[[RNG:.*]]: tensor<2xui32>) -> tuple<tensor<3x4xf32>> {
// CHECK:           %[[VAL_0:.*]] = stablehlo.constant dense<[3, 4]> : tensor<2xi32>
// CHECK:           %[[VAL_1:.*]] = "tfl.custom"(%[[VAL_0]]) <{custom_code = "RandomStandardNormal", custom_option = #tfl<const_bytes : "0x">}> : (tensor<2xi32>) -> tensor<3x4xf32>

#loc3])\0Amodule {\0A  func.func @host_func(%arg0: tensor<3360x?xi32> loc(fused[#loc1, #loc2, #loc3]), %arg1: tensor<3xi32> loc(fused[#loc1, #loc2, #loc3]), %arg2: tensor<i32> loc(fused[#loc1, #loc2, #loc3]), %arg3: tensor<2xi32> loc(fused[#loc1, #loc2, #loc3])) -> (tensor<1x1120x?xi32>, tensor<1x1120x?xi32>, tensor<1120x?xi32>, tensor<2xi32>) {\0A    %0 = \22tf.Reshape\22(%arg0, %arg1) {_xla_outside_compilation = \220\22} : (tensor<3360x?xi32>, tensor<3xi32>) -> tensor<3x1120x?xi32> loc(#loc9)\0A    %1:3 = ...

func.func @foldDivI32() -> tensor<2xi32> {
  %0 = stablehlo.constant dense<[9, 3]> : tensor<2xi32>
  %1 = stablehlo.constant dense<[4, 6]> : tensor<2xi32>
  %2 = stablehlo.divide %0, %1 : tensor<2xi32>
  return %2 : tensor<2xi32>
}

// CHECK-LABEL: foldDivI32
// CHECK: stablehlo.constant dense<[2, 0]> : tensor<2xi32>

// -----

func.func @divideToMulReciprocalSplat(%arg0: tensor<2xf32>) -> tensor<2xf32> {

  return %0 : tensor<1x1600x1x1xf32>
}

//CHECK:func.func private @custom_tf_op(%arg0: tensor<1x320x1x1xf32>, %arg1: tensor<2xi32>) -> tensor<1x1600x1x1xf32> {
//CHECK: %0 = "vhlo.custom_call_v1"(%arg0, %arg1) <{

  %cst = arith.constant dense<[1, 2]> : tensor<2xi32>
  %0 = "tfl.mean"(%arg0, %cst) {keep_dims = false} : (tensor<1x48x48x512xf32>, tensor<2xi32>) -> tensor<1x512xf32>
  func.return %0 : tensor<1x512xf32>
}

// CHECK:       func @mean_4d_no_keepdim([[VAL_0:%.*]]: tensor<1x48x48x512xf32>) -> tensor<1x512xf32> {
// CHECK:           [[VAL_1:%.*]] = "tfl.pseudo_const"(){{.*}}dense<[1, 512]> : tensor<2xi32>

func.func @main(%arg0 : tensor<!tf_type.variant<tensor<2xi32>>>, %arg1: tensor<!tf_type.variant<tensor<*xi32>>>) -> tensor<!tf_type.variant<tensor<2xi32>>> {
  func.return %arg0 : tensor<!tf_type.variant<tensor<2xi32>>>
}

// CHECK:          func.func @main(%[[ARG0:.*]]: tensor<!tf_type.variant<tensor<2xi32>>>, %[[ARG1:.*]]: tensor<!tf_type.variant<tensor<*xi32>>>) -> tensor<!tf_type.variant<tensor<2xi32>>>

  // CHECK: %{{.*}} = "tfl.reshape"(%{{.*}}, %[[cst]]) : (tensor<4xf32>, tensor<2xi32>) -> tensor<2x2xf32>
  %cst = arith.constant dense<[2, 2]> : tensor<2xi32>
  %0 = "tfl.pseudo_const" () {value = dense<1.0> : tensor<4xf32>} : () -> tensor<4xf32> loc("Const")
  %1 = "tfl.reshape" (%0, %cst) : (tensor<4xf32>, tensor<2xi32>) -> tensor<2x2xf32> loc("reshape")

      %0  = "tf.Const"() {value = dense<[56, 904]> : tensor<2xi32>} : () -> tensor<2xi32>
      // CHECK: %{{.*}} = stablehlo.custom_call @tf.ResizeBilinear(%arg0, %{{.*}}) {align_corners = false, device = "", half_pixel_centers = true} : (tensor<1x32x32x128xf32>, tensor<2xi32>) -> tensor<1x64x64x128xf32>

// RUN: json_to_flatbuffer %p/test_schema.fbs %s | flatbuffer_translate --tflite-flatbuffer-to-mlir -o - | FileCheck %s

// CHECK: %0 = "tfl.pseudo_const"() <{value = dense<2> : tensor<2xi32>}> : () -> tensor<2xi32>
// CHECK: %1 = "tfl.reshape"(%arg0, %0) : (tensor<1x4xf32>, tensor<2xi32>) -> tensor<2x2xf32>

{
  "version": 3,
  "operator_codes": [
    {
      "builtin_code": "RESHAPE"
    }
  ],
  "subgraphs": [
    {
      "tensors": [