logitorch.pipelines.proof_qa_pipelines
======================================

.. py:module:: logitorch.pipelines.proof_qa_pipelines


Attributes
----------

.. autoapisummary::

   logitorch.pipelines.proof_qa_pipelines.FLD_COMPATIBLE_MODELS
   logitorch.pipelines.proof_qa_pipelines.PROOFWRITER_COMPATIBLE_MODELS


Functions
---------

.. autoapisummary::

   logitorch.pipelines.proof_qa_pipelines.fld_pipeline
   logitorch.pipelines.proof_qa_pipelines.proofwriter_pipeline


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

.. py:function:: fld_pipeline(model: torch.nn.Module, dataset_name: str, task: str = 'proof_generation_all', saved_model_path: str = '/', saved_model_name: str = 'best_model', batch_size: int = 4, accum_steps: int = 16, epochs: int = 40, accelerator: str = 'cpu', gpus: int = 0)

   Executes the fld pipeline for training a proof generation model.

   Args:
       model (nn.Module): The proof generation model.
       dataset_name (str): The name of the dataset.
       task (str, optional): The task to perform. Defaults to "proof_generation_all".
       saved_model_path (str, optional): The path to save the trained model. Defaults to "/".
       saved_model_name (str, optional): The name of the saved model. Defaults to "best_model".
       batch_size (int, optional): The batch size for training. Defaults to 4.
       accum_steps (int, optional): The number of accumulation steps. Defaults to 16.
       epochs (int, optional): The number of training epochs. Defaults to 40.
       accelerator (str, optional): The accelerator to use (e.g., "cpu", "gpu"). Defaults to "cpu".
       gpus (int, optional): The number of GPUs to use. Defaults to 0.

   Raises:
       ModelNotCompatibleError: If the provided model is not compatible with the fld pipeline.



.. py:function:: proofwriter_pipeline(model: torch.nn.Module, dataset_name: str, task: str = 'proof_generation_all', open_world_assumption: bool = False, saved_model_path: str = '/', saved_model_name: str = 'best_model', batch_size: int = 1, epochs: int = 1, accelerator: str = 'cpu', gpus: int = 0)

   Executes the proofwriter pipeline for training a proof generation model.

   Args:
       model (nn.Module): The proof generation model.
       dataset_name (str): The name of the dataset.
       task (str, optional): The task to perform. Defaults to "proof_generation_all".
       open_world_assumption (bool, optional): Whether to use open world assumption. Defaults to False.
       saved_model_path (str, optional): The path to save the trained model. Defaults to "/".
       saved_model_name (str, optional): The name of the saved model. Defaults to "best_model".
       batch_size (int, optional): The batch size for training. Defaults to 1.
       epochs (int, optional): The number of training epochs. Defaults to 1.
       accelerator (str, optional): The accelerator to use (e.g., "cpu", "gpu"). Defaults to "cpu".
       gpus (int, optional): The number of GPUs to use. Defaults to 0.

   Raises:
       ModelNotCompatibleError: If the provided model is not compatible with the proofwriter pipeline.



.. py:data:: FLD_COMPATIBLE_MODELS

.. py:data:: PROOFWRITER_COMPATIBLE_MODELS