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Remove 'cleanup' of strings (#6007)
A long time ago we went to some trouble to try to clean up "unused" strings, to avoid the `StringStore` growing in long-running processes. This never really worked reliably, and I think it was a really wrong approach. It's much better to let the user reload the `nlp` object as necessary, now that the string encoding is stable (in v1, the string IDs were sequential integers, making reloading the NLP object really annoying.) The extra book-keeping does make some performance difference, and the feature is unsed, so it's past time we killed it.
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@ -1314,7 +1314,6 @@ class Language:
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as_tuples: bool = False,
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batch_size: int = 1000,
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disable: Iterable[str] = SimpleFrozenList(),
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cleanup: bool = False,
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component_cfg: Optional[Dict[str, Dict[str, Any]]] = None,
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n_process: int = 1,
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):
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@ -1326,8 +1325,6 @@ class Language:
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(doc, context) tuples. Defaults to False.
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batch_size (int): The number of texts to buffer.
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disable (List[str]): Names of the pipeline components to disable.
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cleanup (bool): If True, unneeded strings are freed to control memory
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use. Experimental.
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component_cfg (Dict[str, Dict]): An optional dictionary with extra keyword
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arguments for specific components.
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n_process (int): Number of processors to process texts. If -1, set `multiprocessing.cpu_count()`.
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@ -1378,35 +1375,9 @@ class Language:
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for pipe in pipes:
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docs = pipe(docs)
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# Track weakrefs of "recent" documents, so that we can see when they
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# expire from memory. When they do, we know we don't need old strings.
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# This way, we avoid maintaining an unbounded growth in string entries
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# in the string store.
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recent_refs = weakref.WeakSet()
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old_refs = weakref.WeakSet()
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# Keep track of the original string data, so that if we flush old strings,
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# we can recover the original ones. However, we only want to do this if we're
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# really adding strings, to save up-front costs.
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original_strings_data = None
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nr_seen = 0
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for doc in docs:
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yield doc
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if cleanup:
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recent_refs.add(doc)
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if nr_seen < 10000:
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old_refs.add(doc)
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nr_seen += 1
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elif len(old_refs) == 0:
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old_refs, recent_refs = recent_refs, old_refs
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if original_strings_data is None:
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original_strings_data = list(self.vocab.strings)
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else:
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keys, strings = self.vocab.strings._cleanup_stale_strings(
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original_strings_data
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)
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self.vocab._reset_cache(keys, strings)
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self.tokenizer._reset_cache(keys)
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nr_seen = 0
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def _multiprocessing_pipe(
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self,
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@ -23,7 +23,6 @@ cdef class StringStore:
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cdef Pool mem
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cdef vector[hash_t] keys
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cdef set[hash_t] hits
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cdef public PreshMap _map
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cdef const Utf8Str* intern_unicode(self, unicode py_string)
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@ -127,7 +127,6 @@ cdef class StringStore:
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return SYMBOLS_BY_INT[string_or_id]
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else:
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key = string_or_id
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self.hits.insert(key)
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utf8str = <Utf8Str*>self._map.get(key)
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if utf8str is NULL:
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raise KeyError(Errors.E018.format(hash_value=string_or_id))
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@ -198,7 +197,6 @@ cdef class StringStore:
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if key < len(SYMBOLS_BY_INT):
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return True
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else:
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self.hits.insert(key)
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return self._map.get(key) is not NULL
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def __iter__(self):
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@ -210,7 +208,6 @@ cdef class StringStore:
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cdef hash_t key
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for i in range(self.keys.size()):
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key = self.keys[i]
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self.hits.insert(key)
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utf8str = <Utf8Str*>self._map.get(key)
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yield decode_Utf8Str(utf8str)
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# TODO: Iterate OOV here?
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@ -269,41 +266,9 @@ cdef class StringStore:
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self.mem = Pool()
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self._map = PreshMap()
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self.keys.clear()
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self.hits.clear()
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for string in strings:
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self.add(string)
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def _cleanup_stale_strings(self, excepted):
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"""
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excepted (list): Strings that should not be removed.
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RETURNS (keys, strings): Dropped strings and keys that can be dropped from other places
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"""
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if self.hits.size() == 0:
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# If we don't have any hits, just skip cleanup
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return
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cdef vector[hash_t] tmp
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dropped_strings = []
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dropped_keys = []
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for i in range(self.keys.size()):
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key = self.keys[i]
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# Here we cannot use __getitem__ because it also set hit.
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utf8str = <Utf8Str*>self._map.get(key)
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value = decode_Utf8Str(utf8str)
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if self.hits.count(key) != 0 or value in excepted:
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tmp.push_back(key)
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else:
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dropped_keys.append(key)
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dropped_strings.append(value)
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self.keys.swap(tmp)
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strings = list(self)
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self._reset_and_load(strings)
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# Here we have strings but hits to it should be reseted
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self.hits.clear()
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return dropped_keys, dropped_strings
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cdef const Utf8Str* intern_unicode(self, unicode py_string):
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# 0 means missing, but we don't bother offsetting the index.
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cdef bytes byte_string = py_string.encode("utf8")
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@ -319,6 +284,5 @@ cdef class StringStore:
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return value
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value = _allocate(self.mem, <unsigned char*>utf8_string, length)
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self._map.set(key, value)
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self.hits.insert(key)
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self.keys.push_back(key)
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return value
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