AbstractOpAttrsKind getKind() const { return kind_; }
  virtual ~AbstractOpAttrs() = default;

  // Returns the AbstractFunction as a FunctionDef.
  virtual void GetNameAttrList(
      tensorflow::NameAttrList* name_and_attrs) const = 0;

  virtual bool GetInt(absl::string_view, int64_t* result) const = 0;
  virtual bool GetFloat(absl::string_view attr_name, float* result) const = 0;

pkg debug/elf, const R_LARCH_CFA R_LARCH #63725
pkg debug/elf, const R_LARCH_DELETE = 101 #63725
pkg debug/elf, const R_LARCH_DELETE R_LARCH #63725
pkg debug/elf, const R_LARCH_PCREL20_S2 = 103 #63725
pkg debug/elf, const R_LARCH_PCREL20_S2 R_LARCH #63725
pkg debug/elf, const R_LARCH_SUB6 = 106 #63725
pkg debug/elf, const R_LARCH_SUB6 R_LARCH #63725
pkg debug/elf, const R_LARCH_SUB_ULEB128 = 108 #63725

    companion object {
        const val REPOSITORY_CONTEXT_KEY = "binaryCompatibilityRepository"
    }

    /**
     * Each param is a `Set<String>`.
     */
    object Params {
        const val sourceRoots = "sourceRoots"
        const val sourceCompilationClasspath = "sourceCompilationClasspath"
    }

    @Suppress("unchecked_cast")

 */
object Punycode {
  val PREFIX_STRING = "xn--"
  val PREFIX = PREFIX_STRING.encodeUtf8()

  private const val BASE = 36
  private const val TMIN = 1
  private const val TMAX = 26
  private const val SKEW = 38
  private const val DAMP = 700
  private const val INITIAL_BIAS = 72
  private const val INITIAL_N = 0x80

  /**
   * Returns null if any label is oversized so much that the encoder cannot encode it without

#include "tensorflow/c/eager/tfe_monitoring_reader_internal.h"

template <typename... LabelType>
int64_t TFE_MonitoringCounterReader::Read(const LabelType&... labels) {
  return counter->Read(labels...);
}

TFE_MonitoringCounterReader* TFE_MonitoringNewCounterReader(const char* name) {
  auto* result = new TFE_MonitoringCounterReader(name);

  return result;
}

      } else {
        EXPECT_EQ(dltensor_out->strides[i],
                  dltensor_out->shape[i + 1] * dltensor_out->strides[i + 1]);
      }
    }
  }
  const float* data_in = static_cast<const float*>(dltensor_in->data);
  const float* data_out = static_cast<const float*>(dltensor_out->data);
  for (size_t j = 0; j < num_elements; ++j) {
    EXPECT_EQ(data_out[j], data_in[j]);
  }

  TFE_CallDLManagedTensorDeleter(dlm_out);

  // FunctionDef. The name is in fdef.signature.name.
  virtual absl::Status RemoveFunction(const string& func) = 0;

 private:
  const AbstractContextKind kind_;
};

namespace internal {
struct AbstractContextDeleter {
  void operator()(AbstractContext* p) const {
    if (p != nullptr) {
      p->Release();
    }
  }
};
}  // namespace internal

using AbstractContextPtr =

  // Remote device on `worker2`.
  const char remote_device[] = "/job:localhost/replica:0/task:2/device:CPU:0";
  // `ctx_0`, `ctx_1` contains `remote_device`.
  {
    const std::vector<std::string>& device_names = ListDeviceNames(ctx_0);
    ASSERT_TRUE(std::find(device_names.begin(), device_names.end(),
                          remote_device) != device_names.end());
  }

  {

                                           const int64_t** shapes,
                                           const int* ranks,
                                           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);

  EXPECT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());

  const char* first_device = "/job:worker/replica:0/task:1/device:CPU:0";
  const char* second_device = "/job:worker/replica:0/task:2/device:CPU:0";
  const char* device_name = "/job:localhost/replica:0/task:0/device:CUSTOM:0";
  std::array<const char*, 2> underlying_devices{first_device, second_device};