#include "tensorflow/compiler/mlir/lite/utils/arithmetic_count_util.h"

namespace mlir {
namespace TFL {
namespace tac {

bool SimpleHardware::IsOpSupported(mlir::Operation* op) const {
  if (IsNotSupportedOp(op)) {
    return false;
  }
  const TargetHardware* cpu = GetTargetHardware("CPU");
  return cpu->IsOpSupported(op);
}

double SimpleHardware::GetHardwareSwitchingCost(const TargetHardware* from,

  mlir::RewritePatternSet GetTransformations(
      MLIRContext* context) const override;

  mlir::TypeID GetTypeId() const override {
    return mlir::TypeID::get<ExampleHardware>();
  }

  bool IsNotSupportedOp(mlir::Operation* op) const override { return false; }

  float AdvantageOverCPU() const override { return 5.0; }
};

}  // namespace tac
}  // namespace TFL
}  // namespace mlir

  mlir::RewritePatternSet GetTransformations(
      MLIRContext* context) const override;

  mlir::TypeID GetTypeId() const override {
    return mlir::TypeID::get<NNAPIHardware>();
  }

  bool IsNotSupportedOp(mlir::Operation* op) const override { return false; }

  float AdvantageOverCPU() const override { return 5.0; }
};

}  // namespace tac
}  // namespace TFL
}  // namespace mlir

class SimpleHardware : public TargetHardware {
 public:
  // This is essentially a denylist.
  // TODO(renjieliu): Consider whether we want an allowlist for custom op as
  // well.
  virtual bool IsNotSupportedOp(mlir::Operation* op) const = 0;

  // The larger the value is, the more preferrable over CPU.
  // If the value > 1, means the hardware has advantage over CPU.
  // If the value < 1, means CPU is more preferred.

    return patterns;
  }

  mlir::TypeID GetTypeId() const override {
    return mlir::TypeID::get<FooHardware>();
  }

  // We can specify what ops are not supported here.
  bool IsNotSupportedOp(mlir::Operation* op) const override { return false; }

  // This is basically saying how fast are we comparing to CPU.
  // The larger the value the better.
  float AdvantageOverCPU() const override { return 5.0; }
};