Source code for nemo_rl.models.interfaces

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from abc import ABC, abstractmethod
from typing import Any, Dict

from nemo_rl.algorithms.interfaces import LossFunction
from nemo_rl.distributed.batched_data_dict import BatchedDataDict
from nemo_rl.models.generation.interfaces import GenerationDatumSpec




class PolicyInterface(ABC):
    """Abstract base class defining the interface for RL policies."""



    @abstractmethod
    def get_logprobs(
        self, data: BatchedDataDict[GenerationDatumSpec]
    ) -> BatchedDataDict:
        """Get logprobs of actions from observations.

        Args:
            data: BatchedDataDict containing rollouts (tokens)

        Returns:
            BatchedDataDict containing:
                - logprobs: Tensor of logprobs of actions
        """
        pass




    @abstractmethod
    def get_reference_policy_logprobs(
        self, data: BatchedDataDict[GenerationDatumSpec]
    ) -> BatchedDataDict:
        """Get logprobs of actions from observations.

        Args:
            data: BatchedDataDict containing rollouts (tokens)

        Returns:
            BatchedDataDict containing:
                - logprobs: Tensor of logprobs of actions
        """
        pass




    @abstractmethod
    def train(self, data: BatchedDataDict, loss_fn: LossFunction) -> Dict[str, Any]:
        """Train the policy on a global batch of data.

        Args:
            data: BatchedDataDict containing rollouts (tokens)
        """
        pass




    @abstractmethod
    def prepare_for_training(self, *args, **kwargs):
        pass




    @abstractmethod
    def finish_training(self, *args, **kwargs):
        pass