#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
};

  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

  // Build an ExecutionContext from the HostContext.
  auto builder = RequestContextBuilder(host_context_.get(), &resource_context_);

  // Get tensorflow::EagerContext for the kernel fallback.
  auto* eager_context_resource =
      resource_context_
          .GetOrCreateResource<tensorflow::tfd::EagerContextResource>(
              tensorflow::tfd::kEagerContextResourceName);