out->resize(bytes_transferred, n);
  }
  return status.status;
}

TEST(RamFileBlockCacheTest, IsCacheEnabled) {
  auto fetcher = [](const string& filename, size_t offset, size_t n,
                    char* buffer, TF_Status* status) -> int64_t {
    // Do nothing.
    TF_SetStatus(status, TF_OK, "");
    return 0;
  };
  tf_gcs_filesystem::RamFileBlockCache cache1(0, 0, 0, fetcher);

  // Returns the device ID which created the handle.
  virtual int DeviceId(Status* status) const = 0;
  // Returns a tensor for the handle. If tensor is remote, it will be copied.
  virtual AbstractTensorInterface* Resolve(Status* status) = 0;

  std::string DebugString() const override;

  // Returns a Boolean hint indicating whether callers should prefer
  // `SummarizeValue` to resolving this handle and formatting the tensor.

      ::tensorflow::Set_TF_Status_from_Status(C_STATUS, _s);      \
      TF_OpKernelContext_Failure(CTX, C_STATUS);                  \
      TF_DeleteStatus(C_STATUS);                                  \
      return;                                                     \
    }                                                             \
  } while (0)

#define TF_CLEANUP_AND_RETURN_IF_ERROR(C_STATUS, BUFFER, __VA_ARGS__) \

  return parent_op_->DeviceName();
}
Status TapeOperation::SetDeviceName(const char* name) {
  return parent_op_->SetDeviceName(name);
}
Status TapeOperation::AddInput(AbstractTensorHandle* input) {
  TF_RETURN_IF_ERROR(parent_op_->AddInput(input));
  forward_op_.inputs.push_back(input);
  return OkStatus();
}
Status TapeOperation::AddInputList(
    absl::Span<AbstractTensorHandle* const> inputs) {

      return TF_SetStatus(status, TF_INTERNAL,
                          "Block cache contents are inconsistent.");
    }
  }

  Trim();

  return TF_SetStatus(status, TF_OK, "");
}

void RamFileBlockCache::MaybeFetch(const Key& key,
                                   const std::shared_ptr<Block>& block,
                                   TF_Status* status) {
  bool downloaded_block = false;

                  api_def_overwrites.size(), status);
  EXPECT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TF_DeleteStatus(status);

  string op_name = "TestCApi";
  status = TF_NewStatus();
  auto* api_def_buf =
      TF_ApiDefMapGet(api_def_map, op_name.c_str(), op_name.size(), status);
  EXPECT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TF_DeleteStatus(status);

  tensorflow::ApiDef api_def;

#include "tensorflow/core/platform/status.h"
#include "tensorflow/core/protobuf/rewriter_config.pb.h"

namespace tensorflow {
namespace grappler {

// Plugin initialization function that a device plugin
// must define.
typedef void (*TFInitGraphPluginFn)(TP_OptimizerRegistrationParams* const,
                                    TF_Status* const);

// Registers Graph optimizers.
Status InitGraphPlugin(void* dso_handle);

  void GetTensor(const string& name,
                 std::unique_ptr<tensorflow::Tensor>* out_tensor,
                 TF_Status* out_status) const;

 private:
  // Uses "v2_reader_" to build "var name -> shape" and "var name -> data type"
  // maps; both owned by caller.
  // REQUIRES: "v2_reader_ != nullptr && v2_reader_.status().ok()".
  std::pair<std::unique_ptr<TensorSliceReader::VarToShapeMap>,

#include "tensorflow/c/eager/c_api.h"
#include "tensorflow/c/eager/c_api_experimental.h"
#include "tensorflow/c/tf_status.h"

void RegisterLoggingDevice(TFE_Context* context, const char* name,
                           bool strict_scope_placement, bool* arrived_flag,
                           bool* executed_flag, TF_Status* status);
void AllocateLoggingDevice(const char* name, bool* arrived_flag,

                                           TF_Status* status);

void RecordMutation(TF_Graph* graph, const TF_Operation& op,
                    const char* mutation_type)
    TF_EXCLUSIVE_LOCKS_REQUIRED(graph->mu);

bool ExtendSessionGraphHelper(TF_Session* session, TF_Status* status)
    TF_LOCKS_EXCLUDED(session->graph->mu, session->mu);