visibility = ["//tensorflow:internal"],
    deps = [
        ":conversion_macros",
        "//tensorflow/core:framework",
    ],
)

cc_library(
    name = "tf_status",
    srcs = ["tf_status.cc"],
    hdrs = ["tf_status.h"],
    copts = tf_copts(),
    visibility = ["//visibility:public"],
    deps = [
        ":c_api_macros_hdrs",
        ":tf_status_internal",
        "@xla//xla/tsl/c:tsl_status",

    tasks {
      key: 0
      value: "tpuserver:0"
    }
    tasks {
      key: 1
      value: "localhost:1"
    }
  }
}
job_name: "worker"
task_index: 1
protocol: "grpc"
)");

  TF_Status* status = TF_NewStatus();
  TF_Buffer* result = TFE_GetServerDef(expected_text_proto.c_str(), status);
  EXPECT_EQ(TF_GetCode(status), TF_OK);

  ServerDef actual;

  ~LoggedTensor() { TFE_DeleteTensorHandle(tensor); }
};

int64_t LoggedTensorDim(void* data, int dim_index, TF_Status* status) {
  return TFE_TensorHandleDim(reinterpret_cast<LoggedTensor*>(data)->tensor,
                             dim_index, status);
}

int LoggedTensorNumDims(void* data, TF_Status* status) {
  return TFE_TensorHandleNumDims(reinterpret_cast<LoggedTensor*>(data)->tensor,
                                 status);

// there are more than one), or "" otherwise.
std::string GPUDeviceName(TF_Session* session) {
  std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> status(
      TF_NewStatus(), TF_DeleteStatus);
  TF_Status* s = status.get();
  std::unique_ptr<TF_DeviceList, decltype(&TF_DeleteDeviceList)> list(
      TF_SessionListDevices(session, s), TF_DeleteDeviceList);

  cp bazel-bin/tensorflow/tensorflow.lib ${LIB_PKG}/lib/tensorflow.lib
  cp tensorflow/c/c_api.h \
    tensorflow/c/tf_attrtype.h \
    tensorflow/c/tf_buffer.h  \
    tensorflow/c/tf_datatype.h \
    tensorflow/c/tf_status.h \
    tensorflow/c/tf_tensor.h \
    tensorflow/c/tf_tensor_helper.h \
    tensorflow/c/tf_tstring.h \
    tensorflow/c/tf_file_statistics.h \
    tensorflow/c/tensor_interface.h \
    tensorflow/c/c_api_macros.h \

#include "tensorflow/core/util/tensor_bundle/tensor_bundle.h"

namespace tensorflow {
namespace checkpoint {

class TensorSliceReader;

CheckpointReader::CheckpointReader(const string& filename, TF_Status* status)
    : reader_(nullptr),
      v2_reader_(nullptr),
      var_to_shape_map_(nullptr),
      var_to_data_type_map_(nullptr) {
  // Depending on whether this is a V2 ckpt, initializes "reader_" or

                                           const TF_DataType* types,
                                           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);

// other languages.
//
// The class currently only interacts with single-slice (i.e., non-partitioned)
// variables.
class CheckpointReader {
 public:
  CheckpointReader(const std::string& filename, TF_Status* status);

  bool HasTensor(const std::string& name) const;
  const std::string DebugString() const;

  // Returns a map from variable names to their shapes.  Slices of a partitioned

    ASSERT_TRUE(out_attr->ParseFromArray(attr_buf->data, attr_buf->length));
    TF_DeleteBuffer(attr_buf);
  }

  const char* func_name_ = "MyFunc";
  const char* func_node_name_ = "MyFunc_0";
  TF_Status* s_;
  TF_Graph* func_graph_;
  TF_Graph* host_graph_;
  TF_Function* func_;

  // Workaround for not being able to initialize empty map using {}
  std::unordered_set<std::string> empty_;
};

                        .filter(QueryBuilders.termsQuery(OpenSearchAccessResult.SESSION_ID, sessionIdList))
                        .filter(QueryBuilders.termQuery(OpenSearchAccessResult.STATUS, org.codelibs.fess.crawler.Constants.OK_STATUS));
                builder.setQuery(queryBuilder);
                builder.setFrom(0);
                final int maxDocumentCacheSize = fessConfig.getIndexerWebfsMaxDocumentCacheSizeAsInteger();