// required by the TensorFlow Graph(Def) to MLIR module conversion. It is only
// intended to be included by binaries.

#include <string>

#include "llvm/Support/CommandLine.h"

// Please see the implementation file for documentation of these options.

// Import options.
extern llvm::cl::opt<std::string> input_arrays;
extern llvm::cl::opt<std::string> input_dtypes;
extern llvm::cl::opt<std::string> input_shapes;

// and at most 10 arguments in Combine. Please contact
// ******@****.*** if you need more.
// Please note that the number of arguments to Combine is limited
// by the maximum arity of the implementation of tr1::tuple which is
// currently set at 10.

#ifndef GTEST_INCLUDE_GTEST_INTERNAL_GTEST_PARAM_UTIL_GENERATED_H_
#define GTEST_INCLUDE_GTEST_INTERNAL_GTEST_PARAM_UTIL_GENERATED_H_

    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

// graph transformation logic on Tensorflow graphs before importing to MLIR. It
// serves as the source that provides the subgraphs requested by the savedmodel
// MLIR importer, and at the same time it allows the implementation of this
// class to transform the graph before feeding it to the importer.
class SavedModelMLIRImportInput {
 public:
  SavedModelMLIRImportInput(const MetaGraphDef* meta_graph_def,

//
// This header file defines the Message class.
//
// 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

// 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

struct TraceInfo;                      // Information about a trace point.
class ScopedTrace;                     // Implements scoped trace.
class TestInfoImpl;                    // Opaque implementation of TestInfo
class UnitTestImpl;                    // Opaque implementation of UnitTest

// How many times InitGoogleTest() has been called.
GTEST_API_ extern int g_init_gtest_count;

// The text used in failure messages to indicate the start of the

#include "tensorflow/core/platform/protobuf.h"
#include "tensorflow/core/platform/test.h"

namespace tensorflow::saved_model {

// TODO(b/229726259) Switch to OSS version after it's available.
// Simple implementation of a proto matcher comparing string representations.
// Only works as ShapeProto's textual representation is deterministic.
class ProtoStringMatcher {
 public:

#include <string>

#include "llvm/Support/CommandLine.h"

// The commandline options are defined in LLVM style, so the caller should
// use llvm::InitLLVM to initialize the options.
//
// Please see the implementation file for documentation of details of these
// options.
// TODO(jpienaar): Revise the command line option parsing here.
extern llvm::cl::opt<std::string> input_file_name;
extern llvm::cl::opt<std::string> output_file_name;

// TF_SessionRun will no longer extend the session on every call.
//
// We expose this here to allow fine-grained synchronization in multi-threaded
// workloads, which is required since the Python implementation depends on the
// above mutation methods. This allows us to prevent modifications to nodes in
// the graph after the session has been made aware of them.
void ExtendSession(TF_Session* session, TF_Status* status);