// Enable an optimization pass that transforms FC to BatchMatmul only when
    // `unfold_batch_matmul=false`.
    pass_manager.addNestedPass<mlir::func::FuncOp>(
        mlir::TFL::CreateOptimizeBatchMatmulPass());
  }
  pass_manager.addNestedPass<mlir::func::FuncOp>(
      mlir::TFL::CreateOptimizePass(/*enable_canonicalization=*/true));
}

std::unique_ptr<OperationPass<func::FuncOp>> CreateOptimizePass();

// Creates an instance of the Tensorflow Lite batch matmul Optimize pass.
std::unique_ptr<OperationPass<func::FuncOp>> CreateOptimizeBatchMatmulPass();

// Creates an instance of the TensorFlow Lite dialect PrepareTF pass.
std::unique_ptr<OperationPass<func::FuncOp>> CreatePrepareTFPass(
    bool unfold_batch_matmul, bool allow_bf16_and_f16_type_legalization,

  TFL::populateWithGenerated(patterns);
  (void)applyPatternsAndFoldGreedily(func, std::move(patterns));
}
}  // namespace

std::unique_ptr<OperationPass<func::FuncOp>> CreateOptimizeBatchMatmulPass() {
  return std::make_unique<OptimizeBatchMatmulPass>();
}

static PassRegistration<OptimizeBatchMatmulPass> pass;

}  // namespace TFL

  ];
}

def OptimizeBatchMatmulPass : Pass<"tfl-optimize-batch-matmul", "mlir::func::FuncOp"> {
  let summary = "Optimize FC with BatchMatmul within the TensorFlow Lite dialect";
  let constructor = "CreateOptimizeBatchMatmulPass()";
  let dependentDialects = ["TFL::TensorFlowLiteDialect"];
}

def OptimizeFunctionalOpsPass : Pass<"tfl-optimize-functional-ops", "mlir::ModuleOp"> {
  let summary = "Optimize TensorFlow functional op";