cellmap_flow.finetune.job_manager.restart
=========================================

.. py:module:: cellmap_flow.finetune.job_manager.restart

.. autoapi-nested-parse::

   Asking a finetune job that waits for a restart to train again.

   The trainer's inference server, in the same process as its training loop,
   takes ``POST <server>/__control__/restart`` with the job's restart token
   (written into the run's directory at submit; serving.restart_token) in the
   ``X-Restart-Token`` header. The body is ``{"restart": true, "timestamp",
   "params"}``, ``params`` being the settings to change. When the server cannot
   be reached, or has no URL yet, the same body goes into the run's
   ``restart_signal.json``, which the trainer also watches (finetune.session_loop).
   It is written whole or not at all (``finetune.json_files.write_json_atomically``): the
   trainer reads it as soon as it exists, and ends the job if it is not JSON.
   Jobs outlive dashboard upgrades, so both ways are a protocol.



Attributes
----------

.. autoapisummary::

   cellmap_flow.finetune.job_manager.restart.logger


Functions
---------

.. autoapisummary::

   cellmap_flow.finetune.job_manager.restart.request_restart


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

.. py:data:: logger

.. py:function:: request_restart(job: cellmap_flow.finetune.job_manager.state.FinetuneJob, updated_params: Optional[Dict[str, Any]] = None) -> None

   Ask ``job``'s trainer to train again, with ``updated_params`` changed.

   The job is then RUNNING a new iteration from epoch 0, its server not
   ready until the iteration completes, and ``job.params`` updated.
   Raises ValueError, and sends nothing, unless the job can take a restart
   (state.can_restart).