// if no trim_funcs_allowlist_ is specified, this pass is a no-op.
  if (trim_funcs_allowlist_.empty()) return false;

  llvm::SmallVector<func::FuncOp, 4> funcs_to_trim;
  for (auto func : getOperation().getOps<func::FuncOp>()) {
    if (llvm::is_contained(trim_funcs_allowlist_, func.getName())) {
      // If no main is specified in the allowlist, use the 1st func
      // in trim_funcs_allowlist as the main.

  temp_file.os().flush();

  // Replace filename constant ops to use the temporary file.
  MLIRContext* context = &getContext();

  for (func::FuncOp func : module.getOps<func::FuncOp>()) {
    llvm::SmallVector<arith::ConstantOp, 4> constant_ops(
        func.getOps<arith::ConstantOp>());
    for (auto op : constant_ops) {
      ShapedType shaped_type =
          RankedTensorType::get({1}, StringType::get(context));

  TF::LoadResourceDataflowAnalysis(solver);
  if (failed(solver.initializeAndRun(module))) return signalPassFailure();

  DenseSet<GlobalTensorOp> remaining_global_tensor_ops;
  {
    auto ops = module.getOps<GlobalTensorOp>();
    remaining_global_tensor_ops.insert(ops.begin(), ops.end());
  }

  for (auto global_tensor : remaining_global_tensor_ops) {
    // This pass assumes that all global tensors as immutable (e.g. by a

}

static LogicalResult convertTFGlobals(ModuleOp module) {
  OpBuilder globalBuilder(module.getBodyRegion());
  DenseMap<Operation *, std::string> opToName;
  for (auto globalTensor : module.getOps<tf_saved_model::GlobalTensorOp>()) {
    auto exportedNames = tf_saved_model::GetExportedNames(globalTensor);
    std::string name;
    if (exportedNames.empty()) {
      name = "global_ml_" + globalTensor.getSymName().str();

  }
  void runOnOperation() override {
    auto module = getOperation();
    TensorArraySideEffectAnalysis tensor_array_side_effect_analysis(module);

    for (auto func_op : module.getOps<mlir::func::FuncOp>()) {
      func_op.emitRemark() << "HasAtMostTensorArrayEffect: "
                           << tensor_array_side_effect_analysis
                                  .HasAtMostTensorArrayEffect(func_op);
    }

    }


    @Test
    public void resolveDC () throws CIFSException {
        CIFSContext context = withAnonymousCredentials();
        DfsResolver dfs = context.getDfs();

        try ( SmbTransport dc = dfs.getDc(context, getTestDomain()) ) {
            Address addr = dc.getRemoteAddress();
            String remoteHostName = dc.getRemoteHostName();
            assertNotNull(addr);

    return failure();
  }

  // Fetch all VarHandleOp.
  llvm::StringSet<> variable_names;
  llvm::SmallVector<TF::VarHandleOp, 4> var_ops;
  for (auto func_op : module.getOps<func::FuncOp>()) {
    for (auto var_handle_op : func_op.getOps<TF::VarHandleOp>()) {
      auto variable_name = GetVariableName(var_handle_op);
      if (variable_names.count(variable_name)) continue;
      var_ops.emplace_back(var_handle_op);

 public:
  // void runOnOperation() override;
  void runOnOperation() override {
    // Strip the "tf._noinline" attribute from top-level functions.
    for (auto func_op : getOperation().getOps<func::FuncOp>())
      func_op->removeAttr("tf._noinline");
  }
};

}  // namespace

std::unique_ptr<OperationPass<ModuleOp>> CreateStripNoinlineAttributePass() {

          mlir::cast<FlatSymbolRefAttr>(initializer).getValue());
      RewriteFunction(symbol_table, func);
    }

    // Clean up unused asset ops.
    for (auto asset : llvm::make_early_inc_range(module.getOps<AssetOp>())) {
      if (symbol_table.symbolKnownUseEmpty(asset, module)) {
        asset.erase();
      }
    }
  }

 private:
  // Replaces bounded-input arguments of the function with constant ops in the

 public:
  void runOnOperation() override;
};

void InferenceMetricsPass::runOnOperation() {
  bool has_tpu_partitioned_call = false;
  ModuleOp module = getOperation();

  for (auto func_op : module.getOps<func::FuncOp>()) {
    func_op->walk(
        [&](TF::TPUPartitionedCallOp op) { has_tpu_partitioned_call = true; });

    if (has_tpu_partitioned_call) break;
  }

  std::string has_tpu_partitioned_call_str =