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")

                </mxCell>

with open('/etc/hosts', 'rb') as data:
    s3.meta.client.upload_fileobj(data,
                                  'testbucket',
                                  'hosts',
                                  ExtraArgs={'ServerSideEncryption': 'AES256'})

# Upload with server side encryption, using temporary credentials
s3.meta.client.upload_file('/etc/hosts',
                           'testbucket',

 */
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

  {{- end }}
  {{- if .Values.consoleIngress.tls }}
  tls:
    {{- range .Values.consoleIngress.tls }}
    - hosts:
      {{- range .hosts }}
        - {{ . | quote }}
      {{- end }}
      secretName: {{ .secretName }}
    {{- end }}
  {{- end }}
  rules:
    {{- range .Values.consoleIngress.hosts }}
    - http:
        paths:
          - path: {{ $ingressPath }}

  {{- end }}
  {{- if .Values.ingress.tls }}
  tls:
    {{- range .Values.ingress.tls }}
    - hosts:
      {{- range .hosts }}
        - {{ . | quote }}
      {{- end }}
      secretName: {{ .secretName }}
    {{- end }}
  {{- end }}
  rules:
    {{- range .Values.ingress.hosts }}
    - http:
        paths:
          - path: {{ $ingressPath }}

#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);