spaCy/spacy/structs.pxd
Matthew Honnibal 793430aa7a Get spaCy train command working with neural network
* Integrate models into pipeline
* Add basic serialization (maybe incorrect)
* Fix pickle on vocab
2017-05-17 12:04:50 +02:00

77 lines
1.4 KiB
Cython

from libc.stdint cimport uint8_t, uint32_t, int32_t, uint64_t
from .typedefs cimport flags_t, attr_t, hash_t
from .parts_of_speech cimport univ_pos_t
cdef struct LexemeC:
float* vector
flags_t flags
attr_t lang
attr_t id
attr_t length
attr_t orth
attr_t lower
attr_t norm
attr_t shape
attr_t prefix
attr_t suffix
attr_t cluster
float prob
float sentiment
float l2_norm
cdef struct SerializedLexemeC:
unsigned char[4*13 + 8] data
# sizeof(flags_t) # flags
# + sizeof(attr_t) # lang
# + sizeof(attr_t) # id
# + sizeof(attr_t) # length
# + sizeof(attr_t) # orth
# + sizeof(attr_t) # lower
# + sizeof(attr_t) # norm
# + sizeof(attr_t) # shape
# + sizeof(attr_t) # prefix
# + sizeof(attr_t) # suffix
# + sizeof(attr_t) # cluster
# + sizeof(float) # prob
# + sizeof(float) # cluster
# + sizeof(float) # l2_norm
cdef struct Entity:
hash_t id
int start
int end
int label
cdef struct TokenC:
const LexemeC* lex
uint64_t morph
univ_pos_t pos
bint spacy
int tag
int idx
int lemma
int sense
int head
int dep
bint sent_start
uint32_t l_kids
uint32_t r_kids
uint32_t l_edge
uint32_t r_edge
int ent_iob
int ent_type # TODO: Is there a better way to do this? Multiple sources of truth..
hash_t ent_id