#include "tensorflow/compiler/tf2xla/xla_compiler.h"
#include "tensorflow/core/platform/statusor.h"

namespace tensorflow {

class ProcessFunctionLibraryRuntime;
class Device;
class Tensor;
class TensorHandle;
class EagerContext;

enum class IrExportStage {
  HLO,
  HLO_NO_METADATA,
  HLO_SERIALIZED,
  OPTIMIZED_HLO,
  OPTIMIZED_HLO_SERIALIZED,
  OPTIMIZED_HLO_PROTO_SERIALIZED,
  OPTIMIZED_HLO_DOT
};

#include "tensorflow/core/platform/types.h"

namespace tensorflow {
namespace testing {

// Creates a DeviceMgr suitable for local tests.
std::unique_ptr<StaticDeviceMgr> CreateTestingDeviceMgr();

// Creates an EagerContext suitable for local tests. Does not take ownership
// of `device_mgr`.
EagerContextPtr CreateTestingEagerContext(DeviceMgr* device_mgr);

// Converts a tensorflow::DatatypeSet to std::vector<DataType>.

  }
  return absl::OkStatus();
}

absl::StatusOr<std::vector<XlaCompiler::Argument>> PrepareXlaCompilerArgs(
    FunctionLibraryRuntime* flr, const NameAttrList& function,
    EagerContext* context, Device* dev,
    absl::Span<const ArgShapeAndDType> input_arg_shape_and_dtype,
    absl::Span<const TensorHandle* const> input_handles,
    CompilerArgSource compiler_arg_source) {

  auto r = tsl::core::RefCountPtr<tensorflow::IntraProcessRendezvous>(
      new tensorflow::IntraProcessRendezvous(device_mgr.get()));
  tensorflow::EagerContext* eager_context = new tensorflow::EagerContext(
      opts->session_options.options,
      static_cast<tensorflow::ContextDevicePlacementPolicy>(
          opts->device_placement_policy),
      opts->async, device_mgr.release(),

  LOG_FIRST_N(INFO, 1) << "Run Node Expansion Passes";

  // Get the FunctionDef and insert that into the context
  const NodeDef& ndef = orig_op->MutableAttrs()->BuildNodeDef();
  auto& ctx = orig_op->EagerContext();
  Fprint128 cache_key =
      orig_op->MutableAttrs()->CacheKey(orig_op->DeviceName());
  // Include soft placement policy in cache key since the placement strategy
  // can change and thus affect which kernel is picked.

        options, "/job:localhost/replica:0/task:0", &devices));
    device_mgr_ = absl::make_unique<StaticDeviceMgr>(std::move(devices));
    ctx_ = testing::CreateTestingEagerContext(device_mgr_.get());
  }

  EagerContext* context() { return ctx_.get(); }

 private:
  std::unique_ptr<StaticDeviceMgr> device_mgr_;
  EagerContextPtr ctx_;
};

// Sanity check that constructing a tensorflow::Variable from a SavedVariable

}

class RestoreOpsTest : public ::testing::Test {
 public:
  RestoreOpsTest()
      : device_mgr_(testing::CreateTestingDeviceMgr()),
        ctx_(testing::CreateTestingEagerContext(device_mgr_.get())) {}

  EagerContext* context() { return ctx_.get(); }

 private:
  std::unique_ptr<StaticDeviceMgr> device_mgr_;
  EagerContextPtr ctx_;
};

// One way of obtaining the checkpointa checkpoint's tensor names is:

 public:
  ConstantTest()
      : device_mgr_(testing::CreateTestingDeviceMgr()),
        ctx_(testing::CreateTestingEagerContext(device_mgr_.get())) {}

  EagerContext* context() { return ctx_.get(); }

 private:
  std::unique_ptr<StaticDeviceMgr> device_mgr_;
  EagerContextPtr ctx_;
};

// Basic sanity check that roundtripping a Tensor->Tensorproto->Constant

  return std::make_unique<StaticDeviceMgr>(
      DeviceFactory::NewDevice("CPU", {}, "/job:localhost/replica:0/task:0"));
}

EagerContextPtr CreateTestingEagerContext(DeviceMgr* device_mgr) {
  return EagerContextPtr(new EagerContext(
      SessionOptions(),
      tensorflow::ContextDevicePlacementPolicy::DEVICE_PLACEMENT_SILENT,
      /* async= */ false, device_mgr,
      /* device_mgr_owned= */ false, /* rendezvous= */ nullptr,

  auto* gpu_options = config.mutable_gpu_options();
  gpu_options->set_allow_growth(gpu_memory_allow_growth);

  (*config.mutable_device_count())["CPU"] = num_cpu_devices;

  // TODO(b/113217601): This is needed for EagerContext::runner_ to use a
  // threadpool, so that we avoid the possibility of running the runner_ in the
  // threadpool of GPU event mgr, as that can trigger more callbacks to be