pkg archive/tar, const TypeChar ideal-char
pkg archive/tar, const TypeCont ideal-char
pkg archive/tar, const TypeDir ideal-char
pkg archive/tar, const TypeFifo ideal-char
pkg archive/tar, const TypeLink ideal-char
pkg archive/tar, const TypeReg ideal-char
pkg archive/tar, const TypeRegA ideal-char
pkg archive/tar, const TypeSymlink ideal-char
pkg archive/tar, const TypeXGlobalHeader ideal-char

  // that the argument need to be handled by a custom device.
  virtual bool HasCustomDeviceInput() const = 0;

  virtual const tensorflow::OpDef* OpDef() const = 0;

  virtual absl::Status InputLength(const char* input_name, int* length) = 0;
  virtual absl::Status OutputLength(const char* output_name, int* length) = 0;

  // Set stack trace to be used for potential async error reporting.

}

void TF_AttrBuilderSetTypeList(TF_AttrBuilder* builder, const char* attr_name,
                               const TF_DataType* values, int num_values) {
  auto iter = builder->attr_names.insert(attr_name).first;
  builder->Set(*iter, tensorflow::gtl::ArraySlice<const tensorflow::DataType>(
                          reinterpret_cast<const tensorflow::DataType*>(values),
                          num_values));
}

  virtual absl::Status SetAttrInt(const char* attr_name, int64_t value) = 0;
  virtual absl::Status SetAttrFloat(const char* attr_name, float value) = 0;
  virtual absl::Status SetAttrBool(const char* attr_name, bool value) = 0;
  virtual absl::Status SetAttrType(const char* attr_name, DataType value) = 0;
  virtual absl::Status SetAttrShape(const char* attr_name, const int64_t* dims,
                                    const int num_dims) = 0;

      const FunctionDef& fdef, const StackTracesMap& stack_traces) = 0;

  // Find and return a added function by its name.
  virtual const FunctionDef* FindFunctionDef(const string& name) const = 0;

  // Find and return a function record added by its name.
  virtual core::RefCountPtr<FunctionRecord> FindRecord(
      const string& name) const = 0;

0!==arguments[2]?arguments[2]:h;t&&t(e,null);let i=o.length;for(;i--;){let t=o[i];if("string"==typeof t){const e=r(t);e!==t&&(n(o)||(o[i]=e),t=e)}e[t]=!0}return e}function w(e){for(let t=0;t<e.length;t++){_(e,t)||(e[t]=null)}return e}function C(t){const n=l(null);for(const[o,r]of e(t)){_(t,o)&&(Array.isArray(r)?n[o]=w(r):r&&"object"==typeof r&&r.constructor===Object?n[o]=C(r):n[o]=r)}return n}function O(e,t){for(;null!==e;){const n=r(e,t);if(n){if(n.get)return D(n.get);if("function"==typeof n.value)return D(n.value)}e=o(e)}return...

TF_CAPI_EXPORT extern TF_CheckpointReader* TF_NewCheckpointReader(
    const char* filename, TF_Status* status);
TF_CAPI_EXPORT extern void TF_DeleteCheckpointReader(
    TF_CheckpointReader* reader);
TF_CAPI_EXPORT extern int TF_CheckpointReaderHasTensor(
    TF_CheckpointReader* reader, const char* name);
// Get the variable name at the given index
TF_CAPI_EXPORT extern const char* TF_CheckpointReaderGetVariable(

    const TF_Operation* const* opers, int ninputs, const TF_Output* inputs,
    int noutputs, const TF_Output* outputs, const char* const* output_names,
    int ncontrol_outputs, const TF_Operation* const* control_outputs,
    const char* const* control_output_names, const TF_FunctionOptions* opts,
    const char* description, TF_Status* status) {
  tensorflow::mutex_lock l(fn_body->mu);

  // Process inputs.

pkg log/syslog (netbsd-arm64), const LOG_ERR Priority
pkg log/syslog (netbsd-arm64), const LOG_FTP = 88
pkg log/syslog (netbsd-arm64), const LOG_FTP Priority
pkg log/syslog (netbsd-arm64), const LOG_INFO = 6
pkg log/syslog (netbsd-arm64), const LOG_INFO Priority
pkg log/syslog (netbsd-arm64), const LOG_KERN = 0
pkg log/syslog (netbsd-arm64), const LOG_KERN Priority
pkg log/syslog (netbsd-arm64), const LOG_LOCAL0 = 128

  }
}

bool CheckpointReader::HasTensor(const string& name) const {
  if (reader_ != nullptr) {
    return reader_->HasTensor(name, nullptr, nullptr);
  }
  return v2_reader_->Contains(name);
}

const TensorSliceReader::VarToShapeMap&
CheckpointReader::GetVariableToShapeMap() const {
  CHECK(var_to_shape_map_);
  return *var_to_shape_map_;
}

const TensorSliceReader::VarToDataTypeMap&