using mlir::Operation;
using mlir::ShapedType;
using mlir::Value;

// Returns true if all tensor value in `values` has static shape and same shape.
inline bool OpHasSameStaticShapes(Operation* op) {
  auto values = op->getOperands();
  int operand_num = 0;
  ArrayRef<int64_t> shape;
  for (Value value : values) {
    auto shaped_type = value.getType().dyn_cast<ShapedType>();
    if (!shaped_type || !shaped_type.hasStaticShape()) {

             llvm::Twine(calib_opts_.calibration_method()))
                .str());
      }
    } else {
      // Quantize output of fully quantizable composite functions.
      for (Value input : op->getOperands()) {
        auto defining_op = input.getDefiningOp();
        std::optional<StringRef> composite_function_name =
            GetCompsiteFunctionName(defining_op);
        if (!composite_function_name.has_value()) continue;

      }

      rewriter.setInsertionPoint(cloned_func.getBody().front().getTerminator());
      rewriter.create<TF::_XlaSendFromHostOp>(
          func.getLoc(),
          cloned_func.getBody().front().getTerminator()->getOperands(),
          /*dynamic_key=*/dynamic_key, op.getRecvKeyAttr(),
          /*device_ordinal=*/rewriter.getI64IntegerAttr(0),
          rewriter.getStringAttr("TPU"));
    }

// The current implementation is based on the number of operands.
static bool PreferResultScale(Operation* op) {
  int float_operands = 0;
  for (auto operand : op->getOperands()) {
    if (auto operand_type = dyn_cast<ShapedType>(operand.getType())) {
      if (isa<FloatType>(operand_type.getElementType())) {
        if (++float_operands > 1) return true;
      }
    }
  }

  // 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())) {

  std::string custom_option_buffer;
  CreateFlexOpCustomOptions(op_name, node_def_str, custom_option_buffer);
  auto flex_op = builder.create<TFL::CustomOp>(
      op->getLoc(), op->getResultTypes(), op->getOperands(), flex_op_name,
      CustomOptionForFlexOp(&builder, custom_option_buffer));
  op->replaceAllUsesWith(flex_op);
  op->erase();
  return true;
}

// Sets the "no_fallback" attribute.

    auto walk_res = func_op.walk([&](Operation* op) {
      if (auto while_op = dyn_cast<WhileOp>(op)) {
        if (failed(propagate_operands_to_callee_arguments(
                while_op, while_op.getOperands(),
                {while_op.body_function(), while_op.cond_function()},
                func_res)))
          return WalkResult::interrupt();
      } else if (auto if_op = dyn_cast<IfOp>(op)) {

  if (num_cores_per_replica != 1) return success();

  llvm::SetVector<Value> bcasts;
  cluster->walk([&](Operation* op) {
    if (op == cluster) return WalkResult::advance();
    for (auto operand : op->getOperands()) {
      Operation* scope = operand.getParentBlock()->getParentOp();
      if (scope->isProperAncestor(replicate)) {
        bcasts.insert(operand);
      }
    }
    return WalkResult::advance();
  });

    return RefineTypeForPassThroughOperands(
        op, iter_sink.getOperands().drop_front().take_front(),
        iter_source.getResults());
  }
  if (auto launch_op = dyn_cast<tf_device::LaunchOp>(op)) {
    auto terminator = launch_op.GetBody().getTerminator();
    return RefineTypeForPassThroughOperands(op, terminator->getOperands(),
                                            op->getResults());
  }

  //
  func.walk([&](quantfork::QuantizeCastOp q_op) {
    // If up with end up with
    auto dq_op = dyn_cast_or_null<quantfork::DequantizeCastOp>(
        q_op.getOperand().getDefiningOp());
    if (!dq_op) {
      return;
    }
    auto dq_arg = dq_op.getOperand();

    if (!dq_arg.hasOneUse()) {
      // The initial quantization is used someplace else ... so it might be