neuralset.extractors.base.Pulse¶

pydantic model neuralset.extractors.base.Pulse[source][source]¶

Constant-one extractor — returns a single 1.0 scalar for every event.

Useful as a bias term or baseline feature in models that expect at least one extractor per event type.

Fields:

event_types (str | tuple[str, ...])

field event_types: str | tuple[str, ...] = 'Event'[source]¶

get_static(event: Event) → Tensor[source][source]¶

Return a single feature vector for the given event.

Override this method in subclasses to produce a static (non-temporal) embedding for one event. The returned tensor should have no time dimension — temporal wrapping is handled by BaseStatic automatically.

Parameters:: event (Event) – The event to extract a feature from.
Returns:: A tensor of shape (*feature_shape,) (no time axis).
Return type:: torch.Tensor

requirements: tp.ClassVar[tuple[str, ...]] = ()[source]¶

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