: region_(&region) {
  if (region.empty()) return;

  assert(llvm::hasSingleElement(region.getBlocks()));

  auto results = region.front().getTerminator()->getOperands();
  if (results.empty()) return;

  backtracked_values_.reserve(results.size());
  for (auto result : results)
    backtracked_values_.push_back(backtrack_analysis.BacktrackValue(result));
}

  // UniformQuantized Ops are considered legal if its qint operands and
  // results are connected to TF CastOp.
  return op && llvm::all_of(op->getResults(), IsQintValueQintToIntCast) &&
         llvm::all_of(op->getOperands(), IsQintValueDefinedByIntToQintCast);
}

bool IsCastOpLegal(TF::CastOp cast_op) {
  // Consider qint <-> qint casts illegal.
  if (IsIllegalType(cast_op.getSrcT()) && IsIllegalType(cast_op.getDstT())) {

    func_metadata.original_name = func_op.getName();
    func_metadata.insertion_point = ++Block::iterator(func_op);
    func_metadata.ops.push_back(op);

    for (Value value : op->getOperands()) {
      std::string value_device = "";

      // If the value is defined as an argument of the func_op, adds it to
      // the argument list of the function that uses this op.

      }

      write_op.erase();
    }
  }

  const int64_t num_results_before = function.getNumResults();
  auto return_operands = llvm::to_vector<4>(return_op.getOperands());
  auto result_types = llvm::to_vector<4>(return_op.getOperandTypes());
  llvm::SmallVector<std::pair<int64_t, llvm::StringRef>, 4>
      output_only_resources;

    const OpSetVector& cluster_dependent_ops) {
  Operation* other_op = nullptr;
  op->walk([&](Operation* inner_op) {
    ValueRange values = incoming ? ValueRange(inner_op->getOperands())
                                 : ValueRange(inner_op->getResults());
    llvm::SmallVector<Operation*, 4> candidates;
    for (Value value : values) {
      if (incoming) {

  // so this op can be quantized. This is only applied on the returned result
  // because the error will not be accumulated.

  func.walk([&](func::ReturnOp ret) {
    int i = 0;
    for (Value returned : ret.getOperands()) {
      llvm::SmallVector<Value, 4> quantized;
      for (auto user : returned.getUsers()) {
        if (auto q = Quantized(user)) {
          quantized.push_back(q);
        }
      }

  // so this op can be quantized. This is only applied on the returned result
  // because the error will not be accumulated.

  func.walk([&](func::ReturnOp ret) {
    int i = 0;
    for (Value returned : ret.getOperands()) {
      llvm::SmallVector<Value, 4> quantized;
      for (auto user : returned.getUsers()) {
        if (auto q = Quantized(user)) {
          quantized.push_back(q);
        }
      }

}
// Gets the predecessors of an op wrapped in tf_executor.island.
llvm::SmallVector<Operation*> GetPredecessors(Operation* op) {
  llvm::SmallVector<Operation*> predecessors;
  for (auto operand : op->getOperands()) {
    if (Operation* pred = operand.getDefiningOp()) {
      pred->walk([&](mlir::Operation* opinexecutor) {
        predecessors.push_back(opinexecutor);
      });
    }
  }
  return predecessors;
}

      // inputs.
      SmallVector<Value, 4> inputs;
      inputs.reserve(quantizing_op->getNumOperands());
      for (auto operand : quantizing_op->getOperands()) {
        Type operand_type = operand.getType();
        if (operand_type.isa<NoneType>()) {
          inputs.push_back(operand);
          continue;
        }

    std::vector<tensorflow::Tensor>& tensors,
    std::vector<tensorflow::TensorValue>& inputs) {
  // Prepare the list of Tensor inputs for the kernel.
  for (auto it : llvm::enumerate(op_->getOperands())) {
    Value operand = it.value();
    size_t idx = it.index();

    tensorflow::XlaExpression expr = GetExprForOperand(operand, op_, idx);
    tensorflow::XlaExpression::Kind kind = expr.kind();