lambeq.core¶

lambeq.core.globals¶

class lambeq.core.globals.VerbosityLevel(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)[source]¶

Bases: Enum

Level of verbosity for progress reporting.

Table 4 Available Options¶
Option	Value	Description
PROGRESS	`'progress'`	Use progress bar.
TEXT	`'text'`	Give text report.
SUPPRESS	`'suppress'`	No output.

All outputs are printed to stderr. Visual Studio Code does not always display progress bars correctly, use 'progress' level reporting in Visual Studio Code at your own risk.

PROGRESS = 'progress'¶

SUPPRESS = 'suppress'¶

TEXT = 'text'¶

classmethod has_value(value: str) → bool[source]¶

lambeq.core.types¶

Types¶

A standardised set of types that can be used with lambeq.

class lambeq.core.types.AtomicType(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)[source]¶

Bases: Ty, Enum

Standard pregroup atomic types.

CONJUNCTION = Ty(conj)¶

NOUN = Ty(n)¶

NOUN_PHRASE = Ty(n)¶

PREPOSITIONAL_PHRASE = Ty(p)¶

PUNCTUATION = Ty(punc)¶

SENTENCE = Ty(s)¶

__init__(name: str | None = None, objects: list[~typing.Self] = <factory>, z: int = 0) → None¶

apply_functor(functor: Functor) → Ty¶

category: ClassVar[Category] = Category(name='grammar', Ty=<class 'lambeq.backend.grammar.Ty'>, Box=<class 'lambeq.backend.grammar.Box'>, Layer=<class 'lambeq.backend.grammar.Layer'>, Diagram=<class 'lambeq.backend.grammar.Diagram'>)¶

count(other: Self) → int¶

classmethod from_json(data: Dict[str, Any] | str) → Self¶

Decode a JSON object or string into a Ty.

Returns:

Ty: The type generated from the JSON data.

insert(other: Self, index: int) → Self¶

Insert a type at the specified index in the complex type list.

Parameters:

otherTy: The type to insert. Can be atomic or complex.
indexint: The position where the type should be inserted.

property is_atomic: bool¶

property is_complex: bool¶

property is_empty: bool¶

property l: Self¶

name: str = None¶

objects: list[Self]¶

property r: Self¶

repeat(times: int) → Self¶

replace(other: Self, index: int) → Self¶

Replace a type at the specified index in the complex type list.

Parameters:

otherTy: The type to insert. Can be atomic or complex.
indexint: The position where the type should be inserted.

rotate(z: int) → Self¶: Rotate the type, changing the winding number.

tensor(other: Self | Iterable[Self], *rest: Self) → Self¶

to_diagram() → Diagram¶

to_json(is_top_level: bool = True) → Dict[str, Any]¶

Encode this type to a JSON object.

Parameters:

is_top_levelbool, optional: This flag indicates that this object is the top-most object and should have the global metadata (e.g. category). This should be set to False when calling to_json on attribute instances to avoid duplication of said global metadata.

unwind() → Self¶

z: int = 0¶

lambeq.core.utils¶

lambeq.core.utils.fast_deepcopy(obj: Any) → Any[source]¶: Fast deepcopy (faster than copy.deepcopy).

lambeq.core.utils.get_spacy_tokeniser(model: str = 'en_core_web_sm') → Language[source]¶

lambeq.core.utils.normalise_duration(duration_secs: float | None) → str[source]¶

Normalise a duration value in seconds into a more human-readable form.

>>> normalise_duration(4890.0)
'1h21m30s'
>>> normalise_duration(65.0)
'1m5s'
>>> normalise_duration(0.29182375)
'0.29s'
>>> normalise_duration(0.29682375)
'0.30s'
>>> normalise_duration(None)
'None'

Parameters:

duration_secsfloat: The duration value in seconds.

lambeq.core.utils.tokenised_batch_type_check(batch: List[str] | List[List[str]]) → bool[source]¶

lambeq.core.utils.tokenised_sentence_type_check(sentence: str | List[str]) → bool[source]¶

lambeq.core.utils.untokenised_batch_type_check(sentence: List[str] | List[List[str]]) → bool[source]¶