spaCy/spacy/tokens/doc.pxd
Daniël de Kok b71c6043bc Store activations in Doc when store_activations is enabled
This change adds the new `activations` attribute to `Doc`. This
attribute can be used by trainable pipes to store their activations,
probabilities, and guesses for downstream users.

As an example, this change modifies the `tagger` and `senter` pipes to
add an `store_activations` option. When this option is enabled, the
probabilities and guesses are stored in `set_annotations`.
2022-06-22 10:03:26 +02:00

74 lines
1.7 KiB
Cython

from cymem.cymem cimport Pool
cimport numpy as np
from ..vocab cimport Vocab
from ..structs cimport TokenC, LexemeC, SpanC
from ..typedefs cimport attr_t
from ..attrs cimport attr_id_t
cdef attr_t get_token_attr(const TokenC* token, attr_id_t feat_name) nogil
cdef attr_t get_token_attr_for_matcher(const TokenC* token, attr_id_t feat_name) nogil
ctypedef const LexemeC* const_Lexeme_ptr
ctypedef const TokenC* const_TokenC_ptr
ctypedef fused LexemeOrToken:
const_Lexeme_ptr
const_TokenC_ptr
cdef int set_children_from_heads(TokenC* tokens, int start, int end) except -1
cdef int _set_lr_kids_and_edges(TokenC* tokens, int start, int end, int loop_count) except -1
cdef int token_by_start(const TokenC* tokens, int length, int start_char) except -2
cdef int token_by_end(const TokenC* tokens, int length, int end_char) except -2
cdef int [:,:] _get_lca_matrix(Doc, int start, int end)
cdef class Doc:
cdef readonly Pool mem
cdef readonly Vocab vocab
cdef public object _vector
cdef public object _vector_norm
cdef public object tensor
cdef public object cats
cdef public object user_data
cdef readonly object spans
cdef TokenC* c
cdef public float sentiment
cdef public dict activations
cdef public dict user_hooks
cdef public dict user_token_hooks
cdef public dict user_span_hooks
cdef public bint has_unknown_spaces
cdef public object _context
cdef int length
cdef int max_length
cdef public object noun_chunks_iterator
cdef object __weakref__
cdef int push_back(self, LexemeOrToken lex_or_tok, bint has_space) except -1
cpdef np.ndarray to_array(self, object features)