flip.nvflare.executors.trainer
==============================

.. py:module:: flip.nvflare.executors.trainer

.. autoapi-nested-parse::

   RUN_TRAINER Executor.

   This module provides the RUN_TRAINER executor that wraps user-provided
   FLIP_TRAINER classes with error handling.



Classes
-------

.. autoapisummary::

   flip.nvflare.executors.trainer.RUN_TRAINER


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

.. py:class:: RUN_TRAINER(train_task_name=AppConstants.TASK_TRAIN, submit_model_task_name=AppConstants.TASK_SUBMIT_MODEL, exclude_vars=None, project_id='', query='')

   Bases: :py:obj:`nvflare.apis.executor.Executor`


   Wrapper executor that runs user-provided FLIP_TRAINER implementations.

   This executor handles:
   - Dynamic importing of the user's FLIP_TRAINER class
   - Error handling and exception logging
   - Lazy initialization of the trainer instance

   Initialize the RUN_TRAINER executor.

   :param train_task_name: Task name for train task. Defaults to "train".
   :param submit_model_task_name: Task name for submit model. Defaults to "submit_model".
   :param exclude_vars: List of variables to exclude during model loading.
   :param project_id: The ID of the project the model belongs to.
   :param query: The cohort query that is associated with the project.


   .. py:method:: execute(task_name: str, shareable: nvflare.apis.shareable.Shareable, fl_ctx: nvflare.apis.fl_context.FLContext, abort_signal: nvflare.apis.signal.Signal) -> nvflare.apis.shareable.Shareable

      Execute the training task.

      This method:
      1. Lazily imports and initializes the user's FLIP_TRAINER
      2. Delegates execution to the user's trainer
      3. Catches and reports any exceptions

      :param task_name: The name of the task to execute
      :param shareable: The input shareable data
      :param fl_ctx: The FL context
      :param abort_signal: Signal for aborting the task

      :returns: *Shareable* -- The result of the training task