// executing in the context of the death test child process.  Tools such as
// Valgrind heap checkers may need this to modify their behavior in death
// tests.  IMPORTANT: This is an internal utility.  Using it may break the
// implementation of death tests.  User code MUST NOT use it.
GTEST_API_ bool InDeathTestChild();

}  // namespace internal

// The following macros are useful for writing death tests.

// 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>

// included by any test program that uses Google Test.
//
// IMPORTANT NOTE: Due to limitation of the C++ language, we have to
// leave some internal implementation details in this header file.
// They are clearly marked by comments like this:
//
//   // INTERNAL IMPLEMENTATION - DO NOT USE IN A USER PROGRAM.
//
// Such code is NOT meant to be used by a user directly, and is subject

  // 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// Note that this is not expected to be speedy and may be superseded eventually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

// setting functional attributes of other composite ops e.g. control flow.
typedef struct TF_AbstractFunction TF_AbstractFunction;

// This allows the client to swap the implementation of the tracing engine.
// Any future call to TF_CreateFunction will use the implementation defined
// here.
void TF_SetTracingImplementation(const char* name, TF_Status*);

// Creates a new TensorFlow function. A Function is an execution context, and as

// access the assets of the original model. `saved_model_tags` uniquely
// identifies the `MetaGraphDef`. `quantization_config` determines the behavior
// of StableHLO Quantizer. `quantization_py_function_lib` contains python
// implementations of certain APIs that are required for calibration.
// `module_op` is the input graph to be quantized and it should contain
// StableHLO ops.
//
// Returns a quantized `ModuleOp` in StableHLO, potentially wrapped inside a

//     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

//     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;