consistent = false
				continue
			}
			ver := vers[0]
			if len(tops) == 0 {
				consistent = true
				topSig = ver.header
			} else {
				consistent = consistent && ver.header == topSig
			}
			tops = append(tops, vers[0])
		}

		// Check if done...
		if len(tops) < quorum {
			// We couldn't gather enough for quorum
			break
		}

	h.mutex.RLock()
	defer h.mutex.RUnlock()
	// background heal never ends
	if h.clientToken == bgHealingUUID {
		return false
	}
	return !h.endTime.IsZero()
}

// stops the heal sequence - safe to call multiple times.
func (h *healSequence) stop() {
	h.cancelCtx()
}

// pushHealResultItem - pushes a heal result item for consumption in
// the heal-status API. It blocks if there are

* menggunakan <abbr title="an HTTP GET method">operasi <code>get</code></abbr>

/// info | `@decorator` Info

Sintaksis `@sesuatu` di Python disebut "dekorator".

Dekorator ditempatkan di atas fungsi. Seperti sebuah topi cantik (Saya pikir istilah ini berasal dari situ).

"dekorator" memanggil dan bekerja dengan fungsi yang ada di bawahnya

      threshold = buffer[k - 1];
    }
    // Up to bufferSize, all elements of buffer are real Ts (not null unless T includes null)
    T[] topK = Arrays.copyOf(castBuffer, bufferSize);
    // we have to support null elements, so no ImmutableList for us
    return unmodifiableList(asList(topK));
  }

ILIYA <******@****.***> 1748359143 +0900

/// info

<a href="https://docs.python.org/3/library/enum.html" class="external-link" target="_blank">Enumerasi (atau enum) tersedia di Python</a> sejak versi 3.4.

///

/// tip | Tips

"AlxexNet", "ResNet", dan "LeNet" adalah nama <abbr title="Secara teknis, arsitektur model Deep Learning">model</abbr> *Machine Learning*.

///

### Mendeklarasikan *parameter path*

import importlib
import inspect as _inspect
import os as _os
import site as _site
import sys as _sys
import sysconfig

# pylint: disable=g-bad-import-order,protected-access,g-import-not-at-top
from tensorflow.python import pywrap_tensorflow  # pylint: disable=unused-import
from tensorflow.python.tools import module_util as _module_util
from tensorflow.python.platform import tf_logging as _logging

//
// Scanning stops if the function returns an error, in which case some of
// the input may be discarded. If that error is [ErrFinalToken], scanning
// stops with no error. A non-nil token delivered with [ErrFinalToken]
// will be the last token, and a nil token with [ErrFinalToken]
// immediately stops the scanning.
//

            thread.setDaemon(true);
            thread.start();
            if (logger.isDebugEnabled()) {
                logger.debug("TimeoutManager started.");
            }
        }
    }

    /**
     * Stops the process.
     */
    public synchronized void stop() {
        if (thread != null) {
            thread.interrupt();
            thread = null;
            if (logger.isDebugEnabled()) {

Klaus Post <******@****.***> 1756435188 +0200