Source code for oumi.core.feature_generators.base_feature_generator

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from abc import ABC, abstractmethod
from typing import NamedTuple, Optional

from oumi.core.types.conversation import Conversation


[docs] class FeatureGeneratorOptions(NamedTuple): """Options for the feature generator.""" allow_feature_reshape: bool = True """Whether to allow reshaping of the model input features. For example, whether the generator can drop the first dummy dimension. """
[docs] class BaseConversationFeatureGenerator(ABC): """Applies `processor` to generate model inputs from an input `Conversation`."""
[docs] @abstractmethod def transform_conversation( self, conversation: Conversation, options: Optional[FeatureGeneratorOptions] ) -> dict: """Transforms a single Oumi conversation into a dictionary of model inputs. Args: conversation: An input conversation. options: Options for the feature generator. Returns: dict: A dictionary of inputs for a model. """ raise NotImplementedError
[docs] @abstractmethod def transform_conversations( self, conversations: list[Conversation], options: Optional[FeatureGeneratorOptions], ) -> dict: """Transforms a list of Oumi conversations into a dictionary of model inputs. Args: conversations: A list of input conversations. options: Options for the feature generator. Returns: dict: A dictionary of inputs for a model. """ raise NotImplementedError