dacapo.blockwise.scheduler
==========================

.. py:module:: dacapo.blockwise.scheduler


Attributes
----------

.. autoapisummary::

   dacapo.blockwise.scheduler.logger


Functions
---------

.. autoapisummary::

   dacapo.blockwise.scheduler.run_blockwise
   dacapo.blockwise.scheduler.segment_blockwise


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

.. py:data:: logger

.. py:function:: run_blockwise(worker_file: str | upath.UPath, total_roi: funlib.geometry.Roi, read_roi: funlib.geometry.Roi, write_roi: funlib.geometry.Roi, num_workers: int = 16, max_retries: int = 1, timeout=None, upstream_tasks=None, *args, **kwargs)

   Run a function in parallel over a large volume.

   :param worker_file: The path to the file containing the necessary worker functions:
                       ``spawn_worker`` and ``start_worker``.
                       Optionally, the file can also contain a ``check_function`` and an ``init_callback_fn``.
   :type worker_file: ``str`` or ``Path``
   :param total_roi: The ROI to process.
   :type total_roi: ``Roi``
   :param read_roi: The ROI to read from for a block.
   :type read_roi: ``Roi``
   :param write_roi: The ROI to write to for a block.
   :type write_roi: ``Roi``
   :param num_workers: The number of workers to use.
   :type num_workers: ``int``
   :param max_retries: The maximum number of times a task will be retried if failed
                       (either due to failed post check or application crashes or network
                       failure)
   :type max_retries: ``int``
   :param \*args: Additional positional arguments to pass to ``worker_function``.
   :param \*\*kwargs: Additional keyword arguments to pass to ``worker_function``.

   :returns: ``Bool``.

   .. rubric:: Examples

   >>> run_blockwise(worker_file, total_roi, read_roi, write_roi, num_workers, max_retries, timeout, upstream_tasks)


.. py:function:: segment_blockwise(segment_function_file: str | upath.UPath, context: funlib.geometry.Coordinate, total_roi: funlib.geometry.Roi, read_roi: funlib.geometry.Roi, write_roi: funlib.geometry.Roi, num_workers: int = 16, max_retries: int = 2, timeout=None, upstream_tasks=None, keep_tmpdir=False, *args, **kwargs)

   Run a segmentation function in parallel over a large volume.

   :param segment_function_file: The path to the file containing the necessary worker functions:
                                 ``spawn_worker`` and ``start_worker``.
                                 Optionally, the file can also contain a ``check_function`` and an ``init_callback_fn``.
   :type segment_function_file: ``str`` or ``Path``
   :param context: The context to add to the read and write ROI.
   :type context: ``Coordinate``
   :param total_roi: The ROI to process.
   :type total_roi: ``Roi``
   :param read_roi: The ROI to read from for a block.
   :type read_roi: ``Roi``
   :param write_roi: The ROI to write to for a block.
   :type write_roi: ``Roi``
   :param num_workers: The number of workers to use.
   :type num_workers: ``int``
   :param max_retries: The maximum number of times a task will be retried if failed
                       (either due to failed post check or application crashes or network
                       failure)
   :type max_retries: ``int``
   :param timeout: The maximum time in seconds to wait for a worker to complete a task.
   :type timeout: ``int``
   :param upstream_tasks: List of upstream tasks.
   :type upstream_tasks: ``List``
   :param keep_tmpdir: Whether to keep the temporary directory.
   :type keep_tmpdir: ``bool``
   :param \*args: Additional positional arguments to pass to ``worker_function``.
   :param \*\*kwargs: Additional keyword arguments to pass to ``worker_function``.

   :returns: ``Bool``.

   .. rubric:: Examples

   >>> segment_blockwise(segment_function_file, context, total_roi, read_roi, write_roi, num_workers, max_retries, timeout, upstream_tasks)