: error_node_(error_node), error_device_(error_device) {}
  absl::Status Run(const std::string& function_name,
                   const tensorflow::DeviceSet& device_set,
                   const tensorflow::ConfigProto& config_proto,
                   const FunctionOptions& function_options,
                   std::unique_ptr<tensorflow::Graph>* graph,

    return result
  }

  override fun toString(): String = "$tagClass/$tag"

  companion object {
    const val TAG_CLASS_UNIVERSAL = 0b0000_0000
    const val TAG_CLASS_APPLICATION = 0b0100_0000
    const val TAG_CLASS_CONTEXT_SPECIFIC = 0b1000_0000
    const val TAG_CLASS_PRIVATE = 0b1100_0000

    const val TAG_END_OF_CONTENTS = 0L
  }

	V2     = ptwo.G()
)

// Variables with conversions:
var (
	StrConv  = string("foo")
	ByteConv = []byte("foo")
)

var ChecksumError = ptwo.NewError("gzip checksum error")

const B0 = 2
const StrConst = "foo"
const FloatConst = 1.5

type myInt int

type MyInt int

type Time struct{}

type S struct {
	// Deprecated: use PublicTime.
	Public     *int
	private    *int
	PublicTime Time
}

  // Returns the device which created the handle.
  virtual const char* DeviceName(absl::Status* status) const = 0;
  // Returns the device where the tensor was placed.
  virtual const char* BackingDeviceName(absl::Status* status) const = 0;
  // Returns the device type which created the handle.
  virtual const char* DeviceType(absl::Status* status) const = 0;

 */
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

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

  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;

package cmd

import "time"

const (
	peerRESTVersion       = "v39" // add more flags to speedtest API
	peerRESTVersionPrefix = SlashSeparator + peerRESTVersion
	peerRESTPrefix        = minioReservedBucketPath + "/peer"
	peerRESTPath          = peerRESTPrefix + peerRESTVersionPrefix
)

const (
	peerRESTMethodHealth                = "/health"

  // 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());
  }

  {

      } 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);