return nil
	}
}

// DialContext is a function to make custom Dial for internode communications
type DialContext func(ctx context.Context, network, address string) (net.Conn, error)

// NewInternodeDialContext setups a custom dialer for internode communication
func NewInternodeDialContext(dialTimeout time.Duration, opts TCPOptions) DialContext {
	return func(ctx context.Context, network, addr string) (net.Conn, error) {

  FrozenRewritePatternSet frozen_patterns(std::move(patterns));
  // Propagation can happen recursively with multiple functions so keep this
  // module level.
  for (auto func : module_op.getOps<func::FuncOp>()) {
    if (failed(applyPatternsAndFoldGreedily(func, frozen_patterns))) {
      func.emitError() << "quant-propagate-quantize-type failed.";
      signalPassFailure();
    }
  }
}

  auto func_arg_types = llvm::to_vector<4>(func_type.getInputs());
  llvm::SmallDenseMap<llvm::StringRef, int> var_arg_index_by_name;
  for (auto var_handle_op :
       llvm::make_early_inc_range(block.getOps<TF::VarHandleOp>())) {
    if (add_validation && failed(ValidateVarHandle(var_handle_op)))
      return failure();
    // In the case of variables that are not initialized at graph creation

  MLIRContext* ctx = module_op.getContext();

  auto func_op_quant_spec = GetStableHloOpQuantSpec;
  auto func_op_quant_scale_spec = GetStableHloQuantConstraints;

  for (auto func_op : module_op.getOps<func::FuncOp>()) {
    // The function might contain more stats ops than required, and it will
    // introduce requantize if the calibration stats have conflicts. This tries
    // to remove all the redundant stats ops.

}

}  // namespace

ResourceAnalyzer::ResourceAnalyzer(ModuleOp module, bool skip_session_init) {
  auto session_init_func = GetSessionInitializerFunc(module);
  for (auto func : module.getOps<func::FuncOp>()) {
    if (skip_session_init && func == session_init_func) continue;
    (void)AnalyzeRegion(func.getRegion());
  }
}

void ResourceAnalyzer::SetPotentiallyWritten(Value resource) {

    signalPassFailure();
    return;
  }
  TF::SideEffectAnalysis side_effect_analysis(module_op,
                                              op_to_parallel_ids_map);
  for (auto func : module_op.getOps<func::FuncOp>()) {
    if (func.isExternal()) continue;
    const auto& analysis_for_func =
        side_effect_analysis.GetAnalysisForFunc(func);
    if (failed(UpdateAllControlDependencies(func, analysis_for_func))) {

  if (tac_filter.has_function_filter()) {
    llvm::Regex func_regex(
        tac_filter.function_filter().function_name_pattern());
    for (auto func : module.getOps<func::FuncOp>()) {
      if (!func_regex.match(func.getName())) {
        continue;
      }

      ApplyFunctionTacFilter(func, tac_filter.function_filter().filter_type(),
                             builder);

      return false;
    }
  }
  return true;
}

void FoldConstantsToSubgraphPass::runOnOperation() {
  auto module = getOperation();

  for (auto fn : module.getOps<func::FuncOp>()) {
    fn.walk([&](Operation* op) {
      if (!llvm::isa<TFL::ConstOp, TFL::QConstOp, arith::ConstantOp>(op))
        return;

      // We only fold int32/int64 for Const and i32 for QConst if not specify

      const SymbolTable symbol_table(module_op);
      auto entry_func_op =
          dyn_cast_or_null<func::FuncOp>(symbol_table.lookup(function_name));
      auto dot_general_op = *entry_func_op.getOps<DotGeneralOp>().begin();
      if (auto optional_dim = GetDotGeneralQuantizationDim(dot_general_op);
          optional_dim) {
        spec->coeff_op_quant_dim[1] = optional_dim.value();
      } else {

    }
  }
}

void ClusterFormationPass::runOnOperation() {
  auto module = getOperation();
  auto& side_effect_analysis = getAnalysis<TF::SideEffectAnalysis>();

  for (auto func : module.getOps<func::FuncOp>()) {
    if (func.isExternal()) continue;
    OpBuilder builder(func.getContext());
    const TF::SideEffectAnalysis::Info& info =
        side_effect_analysis.GetAnalysisForFunc(func);