mirror of
https://github.com/explosion/spaCy.git
synced 2025-11-03 01:17:52 +03:00
74 lines
2.4 KiB
Python
74 lines
2.4 KiB
Python
from typing import Any, Callable, Dict, Iterable, List, Optional, Tuple
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from ..tokens import Doc, Span
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from .alignment import Alignment
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def annotations_to_doc(
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vocab,
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tok_annot,
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doc_annot,
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) -> Doc: ...
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def validate_examples(
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examples: Iterable[Example],
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method: str,
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) -> None: ...
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def validate_get_examples(
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get_examples: Callable[[], Iterable[Example]],
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method: str,
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): ...
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class Example:
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x: Doc
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y: Doc
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def __init__(
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self,
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predicted: Doc,
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reference: Doc,
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*,
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alignment: Optional[Alignment] = None,
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): ...
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def __len__(self) -> int: ...
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@property
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def predicted(self) -> Doc: ...
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@predicted.setter
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def predicted(self, doc: Doc) -> None: ...
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@property
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def reference(self) -> Doc: ...
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@reference.setter
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def reference(self, doc: Doc) -> None: ...
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def copy(self) -> Example: ...
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@classmethod
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def from_dict(cls, predicted: Doc, example_dict: Dict) -> Example: ...
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@property
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def alignment(self) -> Alignment: ...
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def _get_aligned_vectorized(self, align, gold_values): ...
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def _get_aligned_non_vectorized(self, align, gold_values): ...
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def get_aligned(self, field, as_string=False): ...
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def get_aligned_parse(self, projectivize=True): ...
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def get_aligned_sent_starts(self): ...
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def get_aligned_spans_x2y(self, x_spans, allow_overlap=False): ...
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def get_aligned_spans_y2x(self, y_spans, allow_overlap=False): ...
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def _get_aligned_spans(self, doc, spans, align, allow_overlap): ...
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def get_aligned_ents_and_ner(self): ...
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def get_aligned_ner(self): ...
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def get_matching_ents(self, check_label: bool = True) -> List[Span]: ...
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def to_dict(self) -> Dict[str, Any]: ...
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def _spans_to_dict(self) -> Dict[str, List[Tuple[int, int, str, str]]]: ...
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def _links_to_dict(self) -> Dict[Tuple[int, int], Dict[str, float]]: ...
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def split_sents(self) -> List[Example]: ...
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@property
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def text(self) -> str: ...
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def __str__(self) -> str: ...
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def __repr__(self) -> str: ...
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def _annot2array(vocab, tok_annot, doc_annot): ...
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def _add_spans_to_doc(doc, spans_data): ...
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def _add_entities_to_doc(doc, ner_data): ...
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def _parse_example_dict_data(example_dict): ...
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def _fix_legacy_dict_data(example_dict): ...
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def _has_field(annot, field) -> bool: ...
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def _parse_ner_tags(biluo_or_offsets, vocab, words, spaces): ...
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def _parse_links(vocab, words, spaces, links): ...
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def _guess_spaces(text, words): ...
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