spaCy/spacy/strings.pxd

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from cymem.cymem cimport Pool
from libc.stdint cimport int64_t
from libcpp.set cimport set
from libcpp.vector cimport vector
from murmurhash.mrmr cimport hash64
from preshed.maps cimport PreshMap
from .typedefs cimport attr_t, hash_t
cpdef hash_t hash_string(str string) except 0
cdef hash_t hash_utf8(char* utf8_string, int length) nogil
cdef str decode_Utf8Str(const Utf8Str* string)
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ctypedef union Utf8Str:
unsigned char[8] s
unsigned char* p
cdef class StringStore:
cdef Pool mem
cdef vector[hash_t] keys
cdef public PreshMap _map
Support 'memory zones' for user memory management (#13621) Add a context manage nlp.memory_zone(), which will begin memory_zone() blocks on the vocab, string store, and potentially other components. Example usage: ``` with nlp.memory_zone(): for text in nlp.pipe(texts): do_something(doc) # do_something(doc) <-- Invalid ``` Once the memory_zone() block expires, spaCy will free any shared resources that were allocated for the text-processing that occurred within the memory_zone. If you create Doc objects within a memory zone, it's invalid to access them once the memory zone is expired. The purpose of this is that spaCy creates and stores Lexeme objects in the Vocab that can be shared between multiple Doc objects. It also interns strings. Normally, spaCy can't know when all Doc objects using a Lexeme are out-of-scope, so new Lexemes accumulate in the vocab, causing memory pressure. Memory zones solve this problem by telling spaCy "okay none of the documents allocated within this block will be accessed again". This lets spaCy free all new Lexeme objects and other data that were created during the block. The mechanism is general, so memory_zone() context managers can be added to other components that could benefit from them, e.g. pipeline components. I experimented with adding memory zone support to the tokenizer as well, for its cache. However, this seems unnecessarily complicated. It makes more sense to just stick a limit on the cache size. This lets spaCy benefit from the efficiency advantage of the cache better, because we can maintain a (bounded) cache even if only small batches of documents are being processed.
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cdef const Utf8Str* intern_unicode(self, str py_string, bint allow_transient)
cdef const Utf8Str* _intern_utf8(self, char* utf8_string, int length, hash_t* precalculated_hash, bint allow_transient)
cdef vector[hash_t] _transient_keys
cdef Pool _non_temp_mem