%arg1: tensor<!tf_type.resource<tensor<f32>>> {tf_saved_model.bound_input = @w},
    %arg2: tensor<!tf_type.resource<tensor<f32>>> {tf_saved_model.bound_input = @v},
    %arg3: tensor<!tf_type.resource<tensor<f32>>> {tf_saved_model.bound_input = @x},
    %arg4: tensor<!tf_type.resource<tensor<f32>>> {tf_saved_model.bound_input = @v}
  ) attributes {tf_saved_model.exported_names = ["f"]} {

# CHECK-SAME:   %[[ARG0:.*]]: tensor<3x5xf32> {tf_saved_model.index_path = ["a"]}
# CHECK-SAME:                  tensor<5x5xf32> {tf_saved_model.index_path = ["d"]}
# CHECK-SAME:                  tensor<3x3xf32> {tf_saved_model.index_path = ["c"]}
# CHECK-SAME: attributes {{.*}} tf_saved_model.exported_names = ["key2"]
# CHECK-DAG: %[[MUL1:.*]] = "tf.MatMul"(%[[ARG0]], %[[ARG1]])

// CHECK-LABEL: module @asset
module @asset attributes {tf_saved_model.semantics} {
  "tf_saved_model.session_initializer"() {initializers = [@init]} : () -> ()

  // CHECK-NOT: "tf_saved_model.asset"
  "tf_saved_model.asset"() {filename = "assets/test0.txt", sym_name = "asset0"} : () -> ()
  "tf_saved_model.asset"() {filename = "assets/test1.txt", sym_name = "asset1"} : () -> ()

  // CHECK: func @init()

  }
}

// -----

module attributes {tf_saved_model.semantics} {

  "tf_saved_model.asset"() {filename = "assets/table.txt", sym_name = "v"} : () -> ()
  "tf_saved_model.asset"() {filename = "assets/table2.txt", sym_name = "w"} : () -> ()

  // CHECK: func @f()
  func.func @f(%arg0: tensor<!tf_type.string> {tf_saved_model.bound_input = @v}, %arg1: tensor<!tf_type.string> {tf_saved_model.bound_input = @w})

// RestoreV2 op created for a single VarHandleOp.

module attributes {tf_saved_model.semantics} {
  "tf_saved_model.session_initializer"() {initializers = [@init_func_restore_op]} : () -> ()

  func.func @init_func_restore_op() -> () attributes {
      tf_saved_model.initializer_type = "restore_op",
      tf_saved_model.exported_names = ["tf_saved_model.session_initializer_restore_op"]} {

// CHECK-LABEL: module
// CHECK-NOT: tf_saved_model
module attributes {tf_saved_model.semantics} {
  // CHECK: tf_saved_model.global_tensor
  // CHECK-NOT: tf_saved_model
  "tf_saved_model.global_tensor"() { is_mutable, sym_name = "v", type = tensor<?xf32>, value = dense<1.> : tensor<1xf32> } : () -> ()
  func.func @f(%arg0: tensor<!tf_type.resource<tensor<?xf32>>> {tf_saved_model.bound_input = @v})

  func.return %2 : tensor<1x3xf32>
}

// CHECK-LABEL: func @main
func.func @main(%arg0: tensor<1x3xf32> {tf_saved_model.index_path = ["input"]}) -> (tensor<*xf32> {tf_saved_model.index_path = ["r"]})
  attributes {tf_saved_model.exported_names = ["main"]} {
  // CHECK: tf.VarHandleOp

  # CHECK-SAME:   %arg0: tensor<f32> {tf._user_specified_name = "x", tf_saved_model.index_path = [0]},
  # CHECK-SAME:   %arg1: tensor<!tf_type.resource<{{.*}}>>
  # CHECK-SAME: ) -> (
  # CHECK-SAME:   tensor<f32> {tf_saved_model.index_path = [0]},
  # CHECK-SAME:   tensor<f32> {tf_saved_model.index_path = [1]})
  # CHECK-SAME: attributes{{.*}}tf_saved_model.exported_names = ["callee"]

    module attributes {tf_saved_model.semantics} {
      "tf_saved_model.session_initializer"() <{initializers = []}> : () -> ()
      "tf_saved_model.asset"() <{filename = "assets/vocab_file.txt", sym_name = "__tf_saved_model_asset0_vocab_file.txt"}> : () -> ()

// Test that no ops are added to @main when @tf_quant__save function does
// not exist.

module attributes {tf_saved_model.semantics} {
  func.func @main(%arg: tensor<!tf_type.string> {tf_saved_model.index_path = ["__tf_file_prefix"]}) -> ()
      attributes {tf.entry_function = {inputs = "tf_file_prefix:0", outputs = ""}, tf_saved_model.exported_names = ["main"]} {
    tf_executor.graph {
      tf_executor.fetch
    }
    return
  }
}