2023-06-14 15:48:41 +00:00
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from cymem.cymem cimport Pool
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2016-10-09 10:24:24 +00:00
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from libc.stdint cimport int64_t
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2017-11-11 00:11:27 +00:00
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from libcpp.set cimport set
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2023-06-14 15:48:41 +00:00
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from libcpp.vector cimport vector
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2014-12-19 20:41:08 +00:00
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from murmurhash.mrmr cimport hash64
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2023-06-14 15:48:41 +00:00
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from preshed.maps cimport PreshMap
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2015-07-18 20:39:57 +00:00
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2016-10-09 10:24:24 +00:00
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from .typedefs cimport attr_t, hash_t
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2014-12-19 19:42:01 +00:00
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2015-01-11 23:26:22 +00:00
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2021-09-13 15:02:17 +00:00
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cpdef hash_t hash_string(str string) except 0
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2017-05-28 10:36:27 +00:00
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cdef hash_t hash_utf8(char* utf8_string, int length) nogil
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2021-09-13 15:02:17 +00:00
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cdef str decode_Utf8Str(const Utf8Str* string)
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2014-12-19 20:41:08 +00:00
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2015-07-20 10:06:10 +00:00
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ctypedef union Utf8Str:
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unsigned char[8] s
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unsigned char* p
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2014-12-19 19:42:01 +00:00
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cdef class StringStore:
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cdef Pool mem
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2017-05-28 10:36:27 +00:00
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cdef vector[hash_t] keys
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2015-11-05 11:32:19 +00:00
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cdef public PreshMap _map
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2014-12-19 19:42:01 +00:00
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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.
2024-09-09 09:19:39 +00:00
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cdef const Utf8Str* intern_unicode(self, str py_string, bint allow_transient)
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cdef const Utf8Str* _intern_utf8(self, char* utf8_string, int length, hash_t* precalculated_hash, bint allow_transient)
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cdef vector[hash_t] _transient_keys
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cdef Pool _non_temp_mem
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