nested_module->emitOpError("unexpected already present outlined module.");
    return signalPassFailure();
  }
  ModuleOp outlined_module = ModuleOp::create(getOperation().getLoc());
  outlined_module->setAttrs(getOperation()->getAttrDictionary());
  outlined_module->setAttr(SymbolTable::getSymbolAttrName(),
                           StringAttr::get(ctx, kNestedModule));
  symbol_table.insert(outlined_module);

	Field               fields.Selector
	GetAttrs            AttrFunc
	IndexLabels         []string
	IndexFields         []string
	Limit               int64
	Continue            string
	AllowWatchBookmarks bool
}

// Matches returns true if the given object's labels and fields (as
// returned by s.GetAttrs) match s.Label and s.Field. An error is
// returned if s.GetAttrs fails.

  auto operands = llvm::to_vector<4>(op->getOperands());
  operands.push_back(operand);
  auto new_op = builder->create<OpT>(op->getLoc(), op->getResultTypes(),
                                     operands, attr.getAttrs());
  op->replaceAllUsesWith(new_op.getOperation()->getResults());
  op->erase();
  return new_op;
}

// Returns success if the function has at most one op of the template type and

      return failure();
    }
    res.push_back(signed_lhs_val / signed_rhs_val);
  }

  auto res_attr = DenseElementsAttr::get(
      const_oprs[0].getType().cast<RankedTensorType>(), res);
  rewriter.replaceOpWithNewOp<stablehlo::ConstantOp>(adaptor.value().Op(),
                                                     res_attr);
  return success();
}

  builder->setInsertionPoint(cluster_op);
  auto cluster_func_op = builder->create<tf_device::ClusterFuncOp>(
      cluster_op.getLoc(), outlined_func.getFunctionType().getResults(),
      live_ins.getArrayRef(), cluster_op->getAttrs());
  cluster_op.replaceAllUsesWith(cluster_func_op);
  cluster_op.erase();
}

// Outlines body of `tf_device.launch` into a function and create a

                 StringAttr::get(func_.getContext(), kCustomSSDPostprocessing));

  OpBuilder builder(func_.getBody());
  std::string custom_option_buffer;
  if (failed(CreateNMSCustomOptions(func_, attr_.getAttrs(),
                                    custom_option_buffer))) {
    return failure();
  }
  auto op = builder.create<CustomOp>(
      func_.getLoc(), func_.getFunctionType().getResults(),

    }
  }
  OpBuilder builder(op);
  builder.setInsertionPointAfter(op);
  OperationState state(op->getLoc(), op->getName().getStringRef(),
                       op->getOperands(), result_types, op->getAttrs());
  for (int i = 0; i < op->getNumRegions(); ++i) {
    state.addRegion();
  }
  Operation* new_op = builder.create(state);
  for (const auto& indexed_regions : llvm::enumerate(op->getRegions())) {

    }
  });
  return entry_funcs;
}

LogicalResult GetCallees(SymbolUserOpInterface op, SymbolTable &symtab,
                         llvm::SmallVector<func::FuncOp> &callees) {
  for (auto attr : op->getAttrs()) {
    auto sym = mlir::dyn_cast<SymbolRefAttr>(attr.getValue());
    if (!sym) continue;
    auto callee = symtab.lookup<func::FuncOp>(sym.getRootReference());
    if (!callee) {

    return func_.emitWarning()
           << "Invalid number of results from " << kMaxUnpooling << ": "
           << func_.getFunctionType().getNumResults();
  }

  auto attrs = attr_.getAttrs();

  if (failed(HasIntegerArrayWithSize(&func_, attrs, "pool_size", 2))) {
    return failure();
  }

  if (failed(HasIntegerArrayWithSize(&func_, attrs, "strides", 2))) {
    return failure();
  }

        op.getLoc(),
        /*result=*/
        mlir::cast<TensorType>(op.getResult().getType())
            .clone(builder.getI4Type()),
        /*operand=*/op.getOperands(), op->getAttrs());
    rewriter.replaceAllUsesWith(op.getResult(), new_gather_op.getResult());

    return success();
  }
};

class ReduceTypePrecisionPass