Upload backend/venv/lib/python3.10/site-packages/diskcache/recipes.py with huggingface_hub

backend/venv/lib/python3.10/site-packages/diskcache/recipes.py

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+"""Disk Cache Recipes
+"""
+
+import functools
+import math
+import os
+import random
+import threading
+import time
+
+from .core import ENOVAL, args_to_key, full_name
+
+
+class Averager:
+    """Recipe for calculating a running average.
+
+    Sometimes known as "online statistics," the running average maintains the
+    total and count. The average can then be calculated at any time.
+
+    Assumes the key will not be evicted. Set the eviction policy to 'none' on
+    the cache to guarantee the key is not evicted.
+
+    >>> import diskcache
+    >>> cache = diskcache.FanoutCache()
+    >>> ave = Averager(cache, 'latency')
+    >>> ave.add(0.080)
+    >>> ave.add(0.120)
+    >>> ave.get()
+    0.1
+    >>> ave.add(0.160)
+    >>> ave.pop()
+    0.12
+    >>> print(ave.get())
+    None
+
+    """
+
+    def __init__(self, cache, key, expire=None, tag=None):
+        self._cache = cache
+        self._key = key
+        self._expire = expire
+        self._tag = tag
+
+    def add(self, value):
+        """Add `value` to average."""
+        with self._cache.transact(retry=True):
+            total, count = self._cache.get(self._key, default=(0.0, 0))
+            total += value
+            count += 1
+            self._cache.set(
+                self._key,
+                (total, count),
+                expire=self._expire,
+                tag=self._tag,
+            )
+
+    def get(self):
+        """Get current average or return `None` if count equals zero."""
+        total, count = self._cache.get(self._key, default=(0.0, 0), retry=True)
+        return None if count == 0 else total / count
+
+    def pop(self):
+        """Return current average and delete key."""
+        total, count = self._cache.pop(self._key, default=(0.0, 0), retry=True)
+        return None if count == 0 else total / count
+
+
+class Lock:
+    """Recipe for cross-process and cross-thread lock.
+
+    Assumes the key will not be evicted. Set the eviction policy to 'none' on
+    the cache to guarantee the key is not evicted.
+
+    >>> import diskcache
+    >>> cache = diskcache.Cache()
+    >>> lock = Lock(cache, 'report-123')
+    >>> lock.acquire()
+    >>> lock.release()
+    >>> with lock:
+    ...     pass
+
+    """
+
+    def __init__(self, cache, key, expire=None, tag=None):
+        self._cache = cache
+        self._key = key
+        self._expire = expire
+        self._tag = tag
+
+    def acquire(self):
+        """Acquire lock using spin-lock algorithm."""
+        while True:
+            added = self._cache.add(
+                self._key,
+                None,
+                expire=self._expire,
+                tag=self._tag,
+                retry=True,
+            )
+            if added:
+                break
+            time.sleep(0.001)
+
+    def release(self):
+        """Release lock by deleting key."""
+        self._cache.delete(self._key, retry=True)
+
+    def locked(self):
+        """Return true if the lock is acquired."""
+        return self._key in self._cache
+
+    def __enter__(self):
+        self.acquire()
+
+    def __exit__(self, *exc_info):
+        self.release()
+
+
+class RLock:
+    """Recipe for cross-process and cross-thread re-entrant lock.
+
+    Assumes the key will not be evicted. Set the eviction policy to 'none' on
+    the cache to guarantee the key is not evicted.
+
+    >>> import diskcache
+    >>> cache = diskcache.Cache()
+    >>> rlock = RLock(cache, 'user-123')
+    >>> rlock.acquire()
+    >>> rlock.acquire()
+    >>> rlock.release()
+    >>> with rlock:
+    ...     pass
+    >>> rlock.release()
+    >>> rlock.release()
+    Traceback (most recent call last):
+      ...
+    AssertionError: cannot release un-acquired lock
+
+    """
+
+    def __init__(self, cache, key, expire=None, tag=None):
+        self._cache = cache
+        self._key = key
+        self._expire = expire
+        self._tag = tag
+
+    def acquire(self):
+        """Acquire lock by incrementing count using spin-lock algorithm."""
+        pid = os.getpid()
+        tid = threading.get_ident()
+        pid_tid = '{}-{}'.format(pid, tid)
+
+        while True:
+            with self._cache.transact(retry=True):
+                value, count = self._cache.get(self._key, default=(None, 0))
+                if pid_tid == value or count == 0:
+                    self._cache.set(
+                        self._key,
+                        (pid_tid, count + 1),
+                        expire=self._expire,
+                        tag=self._tag,
+                    )
+                    return
+            time.sleep(0.001)
+
+    def release(self):
+        """Release lock by decrementing count."""
+        pid = os.getpid()
+        tid = threading.get_ident()
+        pid_tid = '{}-{}'.format(pid, tid)
+
+        with self._cache.transact(retry=True):
+            value, count = self._cache.get(self._key, default=(None, 0))
+            is_owned = pid_tid == value and count > 0
+            assert is_owned, 'cannot release un-acquired lock'
+            self._cache.set(
+                self._key,
+                (value, count - 1),
+                expire=self._expire,
+                tag=self._tag,
+            )
+
+    def __enter__(self):
+        self.acquire()
+
+    def __exit__(self, *exc_info):
+        self.release()
+
+
+class BoundedSemaphore:
+    """Recipe for cross-process and cross-thread bounded semaphore.
+
+    Assumes the key will not be evicted. Set the eviction policy to 'none' on
+    the cache to guarantee the key is not evicted.
+
+    >>> import diskcache
+    >>> cache = diskcache.Cache()
+    >>> semaphore = BoundedSemaphore(cache, 'max-cons', value=2)
+    >>> semaphore.acquire()
+    >>> semaphore.acquire()
+    >>> semaphore.release()
+    >>> with semaphore:
+    ...     pass
+    >>> semaphore.release()
+    >>> semaphore.release()
+    Traceback (most recent call last):
+      ...
+    AssertionError: cannot release un-acquired semaphore
+
+    """
+
+    def __init__(self, cache, key, value=1, expire=None, tag=None):
+        self._cache = cache
+        self._key = key
+        self._value = value
+        self._expire = expire
+        self._tag = tag
+
+    def acquire(self):
+        """Acquire semaphore by decrementing value using spin-lock algorithm."""
+        while True:
+            with self._cache.transact(retry=True):
+                value = self._cache.get(self._key, default=self._value)
+                if value > 0:
+                    self._cache.set(
+                        self._key,
+                        value - 1,
+                        expire=self._expire,
+                        tag=self._tag,
+                    )
+                    return
+            time.sleep(0.001)
+
+    def release(self):
+        """Release semaphore by incrementing value."""
+        with self._cache.transact(retry=True):
+            value = self._cache.get(self._key, default=self._value)
+            assert self._value > value, 'cannot release un-acquired semaphore'
+            value += 1
+            self._cache.set(
+                self._key,
+                value,
+                expire=self._expire,
+                tag=self._tag,
+            )
+
+    def __enter__(self):
+        self.acquire()
+
+    def __exit__(self, *exc_info):
+        self.release()
+
+
+def throttle(
+    cache,
+    count,
+    seconds,
+    name=None,
+    expire=None,
+    tag=None,
+    time_func=time.time,
+    sleep_func=time.sleep,
+):
+    """Decorator to throttle calls to function.
+
+    Assumes keys will not be evicted. Set the eviction policy to 'none' on the
+    cache to guarantee the keys are not evicted.
+
+    >>> import diskcache, time
+    >>> cache = diskcache.Cache()
+    >>> count = 0
+    >>> @throttle(cache, 2, 1)  # 2 calls per 1 second
+    ... def increment():
+    ...     global count
+    ...     count += 1
+    >>> start = time.time()
+    >>> while (time.time() - start) <= 2:
+    ...     increment()
+    >>> count in (6, 7)  # 6 or 7 calls depending on CPU load
+    True
+
+    """
+
+    def decorator(func):
+        rate = count / float(seconds)
+        key = full_name(func) if name is None else name
+        now = time_func()
+        cache.set(key, (now, count), expire=expire, tag=tag, retry=True)
+
+        @functools.wraps(func)
+        def wrapper(*args, **kwargs):
+            while True:
+                with cache.transact(retry=True):
+                    last, tally = cache.get(key)
+                    now = time_func()
+                    tally += (now - last) * rate
+                    delay = 0
+
+                    if tally > count:
+                        cache.set(key, (now, count - 1), expire)
+                    elif tally >= 1:
+                        cache.set(key, (now, tally - 1), expire)
+                    else:
+                        delay = (1 - tally) / rate
+
+                if delay:
+                    sleep_func(delay)
+                else:
+                    break
+
+            return func(*args, **kwargs)
+
+        return wrapper
+
+    return decorator
+
+
+def barrier(cache, lock_factory, name=None, expire=None, tag=None):
+    """Barrier to calling decorated function.
+
+    Supports different kinds of locks: Lock, RLock, BoundedSemaphore.
+
+    Assumes keys will not be evicted. Set the eviction policy to 'none' on the
+    cache to guarantee the keys are not evicted.
+
+    >>> import diskcache, time
+    >>> cache = diskcache.Cache()
+    >>> @barrier(cache, Lock)
+    ... def work(num):
+    ...     print('worker started')
+    ...     time.sleep(1)
+    ...     print('worker finished')
+    >>> import multiprocessing.pool
+    >>> pool = multiprocessing.pool.ThreadPool(2)
+    >>> _ = pool.map(work, range(2))
+    worker started
+    worker finished
+    worker started
+    worker finished
+    >>> pool.terminate()
+
+    """
+
+    def decorator(func):
+        key = full_name(func) if name is None else name
+        lock = lock_factory(cache, key, expire=expire, tag=tag)
+
+        @functools.wraps(func)
+        def wrapper(*args, **kwargs):
+            with lock:
+                return func(*args, **kwargs)
+
+        return wrapper
+
+    return decorator
+
+
+def memoize_stampede(
+    cache, expire, name=None, typed=False, tag=None, beta=1, ignore=()
+):
+    """Memoizing cache decorator with cache stampede protection.
+
+    Cache stampedes are a type of system overload that can occur when parallel
+    computing systems using memoization come under heavy load. This behaviour
+    is sometimes also called dog-piling, cache miss storm, cache choking, or
+    the thundering herd problem.
+
+    The memoization decorator implements cache stampede protection through
+    early recomputation. Early recomputation of function results will occur
+    probabilistically before expiration in a background thread of
+    execution. Early probabilistic recomputation is based on research by
+    Vattani, A.; Chierichetti, F.; Lowenstein, K. (2015), Optimal Probabilistic
+    Cache Stampede Prevention, VLDB, pp. 886-897, ISSN 2150-8097
+
+    If name is set to None (default), the callable name will be determined
+    automatically.
+
+    If typed is set to True, function arguments of different types will be
+    cached separately. For example, f(3) and f(3.0) will be treated as distinct
+    calls with distinct results.
+
+    The original underlying function is accessible through the `__wrapped__`
+    attribute. This is useful for introspection, for bypassing the cache, or
+    for rewrapping the function with a different cache.
+
+    >>> from diskcache import Cache
+    >>> cache = Cache()
+    >>> @memoize_stampede(cache, expire=1)
+    ... def fib(number):
+    ...     if number == 0:
+    ...         return 0
+    ...     elif number == 1:
+    ...         return 1
+    ...     else:
+    ...         return fib(number - 1) + fib(number - 2)
+    >>> print(fib(100))
+    354224848179261915075
+
+    An additional `__cache_key__` attribute can be used to generate the cache
+    key used for the given arguments.
+
+    >>> key = fib.__cache_key__(100)
+    >>> del cache[key]
+
+    Remember to call memoize when decorating a callable. If you forget, then a
+    TypeError will occur.
+
+    :param cache: cache to store callable arguments and return values
+    :param float expire: seconds until arguments expire
+    :param str name: name given for callable (default None, automatic)
+    :param bool typed: cache different types separately (default False)
+    :param str tag: text to associate with arguments (default None)
+    :param set ignore: positional or keyword args to ignore (default ())
+    :return: callable decorator
+
+    """
+    # Caution: Nearly identical code exists in Cache.memoize
+    def decorator(func):
+        """Decorator created by memoize call for callable."""
+        base = (full_name(func),) if name is None else (name,)
+
+        def timer(*args, **kwargs):
+            """Time execution of `func` and return result and time delta."""
+            start = time.time()
+            result = func(*args, **kwargs)
+            delta = time.time() - start
+            return result, delta
+
+        @functools.wraps(func)
+        def wrapper(*args, **kwargs):
+            """Wrapper for callable to cache arguments and return values."""
+            key = wrapper.__cache_key__(*args, **kwargs)
+            pair, expire_time = cache.get(
+                key,
+                default=ENOVAL,
+                expire_time=True,
+                retry=True,
+            )
+
+            if pair is not ENOVAL:
+                result, delta = pair
+                now = time.time()
+                ttl = expire_time - now
+
+                if (-delta * beta * math.log(random.random())) < ttl:
+                    return result  # Cache hit.
+
+                # Check whether a thread has started for early recomputation.
+
+                thread_key = key + (ENOVAL,)
+                thread_added = cache.add(
+                    thread_key,
+                    None,
+                    expire=delta,
+                    retry=True,
+                )
+
+                if thread_added:
+                    # Start thread for early recomputation.
+                    def recompute():
+                        with cache:
+                            pair = timer(*args, **kwargs)
+                            cache.set(
+                                key,
+                                pair,
+                                expire=expire,
+                                tag=tag,
+                                retry=True,
+                            )
+
+                    thread = threading.Thread(target=recompute)
+                    thread.daemon = True
+                    thread.start()
+
+                return result
+
+            pair = timer(*args, **kwargs)
+            cache.set(key, pair, expire=expire, tag=tag, retry=True)
+            return pair[0]
+
+        def __cache_key__(*args, **kwargs):
+            """Make key for cache given function arguments."""
+            return args_to_key(base, args, kwargs, typed, ignore)
+
+        wrapper.__cache_key__ = __cache_key__
+        return wrapper
+
+    return decorator