let summary = "Serializes StableHLO functions from top-level module into `tf.XlaCallModule`'s `module` attribute";

  let description = [{
    This pass collects StableHLO functions referenced from `tf.XlaCallModule`'s
    `_entry_function` attribute into a module, serializes the module into MLIR
    bytecode, and embed the bytecode to `tf.XlaCallModule`'s `module` attribute.

  // TODO(b/154065712): Remove propagate_caller_callee_constants once using
  // SCCP pass instead.
  bool propagate_caller_callee_constants_;

  // XlaCallModule loader, which is used to deserialize the StableHLO module in
  // each `XlaCallModule` op. Uses its own MLIRContext since the loader needs to
  // load additional dialects, which is not allowed for the main context since
  // shape inference may be called from a pass.

      # This is to verify the invocation of StableHLO quantizer works. More
      # thorough functional tests are in StableHLO quantizer directory.
      self.assertTrue(self._contains_op(output_graphdef, 'XlaCallModule'))
    else:
      self.assertTrue(self._contains_quantized_function_call(output_graphdef))
    self.assertFalse(self._contains_op(output_graphdef, 'FusedBatchNormV3'))

  @parameterized.named_parameters(

void XlaCallModuleOp::getEffects(
    SmallVectorImpl<SideEffects::EffectInstance<MemoryEffects::Effect>>
        &effects) {
  if (!getFunctionList().empty()) {
    // The StableHLO module embedded in XlaCallModule contains
    // `stablehlo.custom_call` calling TF host callback functions.
    // `stablehlo.custom_call` will be lowered to `stablehlo.send` and
    // `stablehlo.recv`.