logitorch.pl_models.ruletaker
=============================

.. py:module:: logitorch.pl_models.ruletaker


Classes
-------

.. autoapisummary::

   logitorch.pl_models.ruletaker.PLRuleTaker


Module Contents
---------------

.. py:class:: PLRuleTaker(learning_rate: float = 1e-05, weight_decay: float = 0.1, num_labels: int = 2)

   Bases: :py:obj:`lightning.pytorch.LightningModule`


   
   Initializes the PLRuleTaker module.

   Args:
       learning_rate (float): The learning rate for the optimizer. Default is 1e-5.
       weight_decay (float): The weight decay for the optimizer. Default is 0.1.
       num_labels (int): The number of labels for the RuleTaker model. Default is 2.


   .. py:method:: configure_optimizers()

      Configures the optimizer and scheduler for training.

      Returns:
          The optimizer and scheduler.



   .. py:method:: forward(x, y)

      Performs a forward pass of the PLRuleTaker module.

      Args:
          x: The input data.
          y: The target labels.

      Returns:
          The output of the model.



   .. py:method:: predict(context: str, question: str, device: str = 'cpu') -> int

      Predicts the label for a given context and question.

      Args:
          context (str): The context.
          question (str): The question.
          device (str): The device to use for prediction. Default is "cpu".

      Returns:
          The predicted label.



   .. py:method:: training_step(train_batch: Tuple[Dict[str, torch.Tensor], torch.Tensor], batch_idx: int) -> torch.Tensor

      Performs a training step.

      Args:
          train_batch: The batch of training data.
          batch_idx (int): The index of the batch.

      Returns:
          The training loss.



   .. py:method:: validation_step(val_batch: Tuple[Dict[str, torch.Tensor], torch.Tensor], batch_idx: int) -> None

      Performs a validation step.

      Args:
          val_batch: The batch of validation data.
          batch_idx (int): The index of the batch.



   .. py:attribute:: learning_rate
      :value: 1e-05



   .. py:attribute:: model


   .. py:attribute:: weight_decay
      :value: 0.1