if (!main) return;
  if (failed(DecomposeStackOps(&main.front(), module))) {
    signalPassFailure();
  }
}

}  // namespace

namespace TF {
std::unique_ptr<OperationPass<ModuleOp>> CreateStackOpsDecompositionPass() {
  return std::make_unique<StackOpsDecompositionPass>();
}

}  // namespace TF

// removed by resource lifting. Requires known maximum sizes of stacks and
// known element shapes of push ops.
std::unique_ptr<OperationPass<ModuleOp>> CreateStackOpsDecompositionPass();

// Creates a pass to strip the "tf._noinline" attribute from the functions in
// the module.
std::unique_ptr<OperationPass<ModuleOp>> CreateStripNoinlineAttributePass();

  // legalization passes.
  pm.addPass(mlir::createSCCPPass());

  if (lower_to_xla_hlo) {
    pm.addPass(mlir::TF::CreateTensorListOpsDecompositionPass());
  }
  pm.addPass(mlir::TF::CreateStackOpsDecompositionPass());
  if (lower_to_xla_hlo) {
    pm.addPass(mlir::TF::CreateTensorArrayOpsDecompositionPass());
  }
  pm.addNestedPass<mlir::func::FuncOp>(
      mlir::TFDevice::CreateDecomposeResourceOpsPass());

def StackOpsDecompositionPass : Pass<"tf-stack-ops-decomposition", "ModuleOp"> {
  let summary = "Decompose stack operations into local variable operations. Needs "
           "static shapes.";
  let constructor = "TF::CreateStackOpsDecompositionPass()";
  let description = [{
    A pass that converts stack operations to tensor operations and read/assign
    ops on local variables. A later resource lifting pass can further remove the
    local variables.