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

    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 os, const ModeDir FileMode
pkg os, const ModeExclusive FileMode
pkg os, const ModeIrregular FileMode
pkg os, const ModeNamedPipe FileMode
pkg os, const ModePerm FileMode
pkg os, const ModeSetgid FileMode
pkg os, const ModeSetuid FileMode
pkg os, const ModeSocket FileMode
pkg os, const ModeSticky FileMode
pkg os, const ModeSymlink FileMode
pkg os, const ModeTemporary FileMode
pkg os, const ModeType = 2399141888

    TFE_MonitoringStringGauge2* gauge, const char* label1, const char* label2) {
  return static_cast<TFE_MonitoringStringGaugeCell*>(
      static_cast<void*>(gauge->gauge->GetCell(label1, label2)));
}

TFE_MonitoringStringGauge3* TFE_MonitoringNewStringGauge3(
    const char* name, TF_Status* status, const char* description,
    const char* label1, const char* label2, const char* label3) {

				this.mem.setUint32(addr, id, true);
			}

			const loadSlice = (addr) => {
				const array = getInt64(addr + 0);
				const len = getInt64(addr + 8);
				return new Uint8Array(this._inst.exports.mem.buffer, array, len);
			}

			const loadSliceOfValues = (addr) => {
				const array = getInt64(addr + 0);
				const len = getInt64(addr + 8);
				const a = new Array(len);
				for (let i = 0; i < len; i++) {

pkg debug/elf, const R_LARCH_SOP_SR R_LARCH #46229
pkg debug/elf, const R_LARCH_SOP_SUB = 32 #46229
pkg debug/elf, const R_LARCH_SOP_SUB R_LARCH #46229
pkg debug/elf, const R_LARCH_SUB16 = 53 #46229
pkg debug/elf, const R_LARCH_SUB16 R_LARCH #46229
pkg debug/elf, const R_LARCH_SUB24 = 54 #46229
pkg debug/elf, const R_LARCH_SUB24 R_LARCH #46229
pkg debug/elf, const R_LARCH_SUB32 = 55 #46229

                          const char* name = "feed",
                          TF_DataType dtype = TF_INT32,
                          const std::vector<int64_t>& dims = {});

TF_Operation* Const(TF_Tensor* t, TF_Graph* graph, TF_Status* s,
                    const char* name = "const");

TF_Operation* ScalarConst(bool v, TF_Graph* graph, TF_Status* s,
                          const char* name = "scalar");

                                  const char* label1, const char* label2);

// APIs for String Gauge with 3 labels.
typedef struct TFE_MonitoringStringGauge3 TFE_MonitoringStringGauge3;
TF_CAPI_EXPORT extern TFE_MonitoringStringGauge3* TFE_MonitoringNewStringGauge3(
    const char* name, TF_Status* out_status, const char* description,
    const char* label1, const char* label2, const char* label3);

                       GradientFunction* gradient_function,
                       const string& op_name = "");
  // Returns whether any tensor in a list of tensors is being watched and has
  // a trainable dtype.
  bool ShouldRecord(
      absl::Span<const AbstractTensorHandle* const> tensors) const;
  // Unwatches this tensor on the tape. Mainly used for cleanup when deleting
  // eager tensors.

        node.style.display = "block";
        new Termynal(node, {
            lineDelay: 500
        });
    });
    const progressLiteralStart = "---> 100%";
    const promptLiteralStart = "$ ";
    const customPromptLiteralStart = "# ";
    const termynalActivateClass = "termy";
    let termynals = [];

    function createTermynals() {
        document