return %updated_list : tensor<!tf_type.variant<tensor<64x1xbf16>>>
    }
  })";

  auto compilation_result = CompileMlirModule(
      kTensorListSetItemDimensionTooLarge,
      ConfigProto::Experimental::MLIR_BRIDGE_ROLLOUT_UNSPECIFIED);

  // Ensure that it compile

func.func @main(tensor<4x5xbf16>) -> tensor<4x5xbf16> {
^bb0(%arg0: tensor<4x5xbf16>):
  // CHECK-LABEL: @main
  // CHECK:  (tensor<4x5xbf16>) -> tensor<4x5xf32>
  // CHECK-NEXT:  (tensor<4x5xf32>) -> tensor<4x5xbf16>
  %0 = "tfl.cast" (%arg0) : (tensor<4x5xbf16>) -> tensor<4x5xf32> loc("cast1")
  %1 = "tfl.cast" (%0) : (tensor<4x5xf32>) -> tensor<4x5xbf16> loc("cast2")
  func.return %1 : tensor<4x5xbf16>

// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -emit-custom-ops -o - | flatbuffer_to_string - | FileCheck %s

func.func @main(tensor<4x5xbf16>) -> tensor<4x5xbf16> {
^bb0(%arg0: tensor<4x5xbf16>):

// CHECK:  {
// CHECK-NEXT:      version: 3,
// CHECK-NEXT:      operator_codes: [ {
// CHECK-NEXT:        deprecated_builtin_code: 53,
// CHECK-NEXT:        version: 7,
// CHECK-NEXT:        builtin_code: CAST
// CHECK-NEXT:      } ],

    %1 = "tf.Cast"(%0) <{truncate = false}> : (tensor<3x1xf32>) -> tensor<3x1xbf16>
    %2 = "tf.VarHandleOp"() <{container = "", shared_name = "y"}> : () -> tensor<!tf_type.resource<tensor<3x1xbf16>>>
    "tf.AssignVariableOp"(%2, %1) : (tensor<!tf_type.resource<tensor<3x1xbf16>>>, tensor<3x1xbf16>) -> ()
    return
  }

  // CHECK: %[[RESULT:.*]] = mhlo.reshape %[[CAST_BACK]] : (tensor<4xf16>) -> tensor<4x1xf16>
  // CHECK: return %[[RESULT]] : tensor<4x1xf16>
  %dimension = "tf.Const"() { value = dense<1> : tensor<1xi64> } : () -> tensor<1xi64>
  %0 = "tf.Mean"(%arg0, %dimension) { keep_dims = true }: (tensor<4x8xf16>, tensor<1xi64>) -> tensor<4x1xf16>
  func.return %0 : tensor<4x1xf16>
}

// -----

// CHECK-LABEL: func @mean_scalar_dim

}

func.func @matmul_batchv3_unknown_dim_bf16(%arg0: tensor<?x4x5xbf16>, %arg1: tensor<5x6xf32>) -> tensor<?x4x6xbf16> {
  %0 = "tf.Cast"(%arg0) : (tensor<?x4x5xbf16>) -> tensor<?x4x5xf32>
  %1 = "tf.BatchMatMulV3"(%0, %arg1) {Ta = "tfdtype$DT_FLOAT", Tb = "tfdtype$DT_FLOAT", device = "/device:CPU:0", name = "MatMul", adj_x = false, adj_y = false} :

// CHECK-LABEL: func @testValidMatrixBandPartOp
func.func @testValidMatrixBandPartOp(%arg0: tensor<64x64xbf16>, %arg1: tensor<i64>, %arg2: tensor<i64>) -> tensor<64x64xbf16> {
  %0 = "tf.MatrixBandPart"(%arg0, %arg1, %arg2) : (tensor<64x64xbf16>, tensor<i64>, tensor<i64>) -> tensor<64x64xbf16>
  func.return %0 : tensor<64x64xbf16>
}

// -----

// Test valid tf.MatrixBandPart