public:
  virtual ~DeathTestFactory() { }
  virtual bool Create(const char* statement, const RE* regex,
                      const char* file, int line, DeathTest** test) = 0;
};

// A concrete DeathTestFactory implementation for normal use.
class DefaultDeathTestFactory : public DeathTestFactory {
 public:
  virtual bool Create(const char* statement, const RE* regex,
                      const char* file, int line, DeathTest** test);
};

    mutable scoped_ptr<const T> value_;
  };  // class ValuesInIteratorRangeGenerator::Iterator

  // No implementation - assignment is unsupported.
  void operator=(const ValuesInIteratorRangeGenerator& other);

  const ContainerType container_;
};  // class ValuesInIteratorRangeGenerator

// INTERNAL IMPLEMENTATION - DO NOT USE IN USER CODE.
//
// Stores a parameter value and later creates tests parameterized with that

  // running calibration.
  absl::StatusOr<ModuleOp> ImportCalibratedSavedModel(
      absl::string_view calibrated_saved_model_path);

  absl::Nonnull<MLIRContext*> ctx_;

  // Contains function implementations from the python layer. Should be injected
  // from the python level using pybind11.
  absl::Nonnull<const tensorflow::quantization::PyFunctionLibrary*>
      py_function_lib_;

  // Path to the pre-calibrated SavedModel.

// Determines whether Google Test's own tr1 tuple implementation
// should be used.
#ifndef GTEST_USE_OWN_TR1_TUPLE
// The user didn't tell us, so we need to figure it out.

// We use our own TR1 tuple if we aren't sure the user has an
// implementation of it already.  At this time, libstdc++ 4.0.0+ and
// MSVC 2010 are the only mainstream standard libraries that come
// with a TR1 tuple implementation.  NVIDIA's CUDA NVCC compiler

    typename T6 = void, typename T7 = void, typename T8 = void,
    typename T9 = void>
class tuple;

// Anything in namespace gtest_internal is Google Test's INTERNAL
// IMPLEMENTATION DETAIL and MUST NOT BE USED DIRECTLY in user code.
namespace gtest_internal {

// ByRef<T>::type is T if T is a reference; otherwise it's const T&.
template <typename T>

  // Will be nullptr if conversion is not supported.
  const Type expressed_type;
};

// Reference implementation of converting between real numbers and values
// represented by a UniformQuantizedType.
// Note that this is not expected to be speedy and may be superseded eventually
// by a more optimal implementation.
// Also, the interface assumes that quantization is done per-layer and will

//     non-static members of the current object.
//   - 'statement' cannot return a value.
//   - You cannot stream a failure message to this macro.
//
// Note that even though the implementations of the following two
// macros are much alike, we cannot refactor them to use a common
// helper macro, due to some peculiarity in how the preprocessor
// works.  The AcceptsMacroThatExpandsToUnprotectedComma test in

#include "tensorflow/core/protobuf/meta_graph.pb.h"

namespace tensorflow::quantization {

// Declares pure virtual member functions for a python-side derived class to
// override. This allows calling python implementations from the C++ layer.
// Member functions should be pure not stateful; they should not access or rely
// on member fields.
class PyFunctionLibrary {
 public:
  virtual ~PyFunctionLibrary() = default;

  //
  // Unlike wcscasecmp(), this function can handle NULL argument(s).
  // A NULL C string is considered different to any non-NULL wide C string,
  // including the empty string.
  // NB: The implementations on different platforms slightly differ.
  // On windows, this method uses _wcsicmp which compares according to LC_CTYPE
  // environment variable. On GNU platform this method uses wcscasecmp

// `tsl::Env::Default` is used to generate the name.
absl::StatusOr<std::string> GetLocalTmpFileName();

// Creates a temporary directory on an environment defined by the implementation
// of `tsl::Env` and returns its path. Returns an InternalError status if
// failed.
absl::StatusOr<std::string> CreateTmpDir(tsl::Env* env);