`dacapo.blockwise.scheduler`

Module Contents

Functions

`run_blockwise`(worker_file, total_roi, read_roi, write_roi)	Run a function in parallel over a large volume.
`segment_blockwise`(segment_function_file, context, ...)	Run a segmentation function in parallel over a large volume.

Attributes

logger

dacapo.blockwise.scheduler.logger

dacapo.blockwise.scheduler.run_blockwise(worker_file: str | pathlib.Path, 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.

Parameters:

worker_file (str or Path) – 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.
total_roi (Roi) – The ROI to process.
read_roi (Roi) – The ROI to read from for a block.
write_roi (Roi) – The ROI to write to for a block.
num_workers (int) – The number of workers to use.
max_retries (int) – The maximum number of times a task will be retried if failed (either due to failed post check or application crashes or network failure)
*args – Additional positional arguments to pass to worker_function.
**kwargs – Additional keyword arguments to pass to worker_function.

Returns:

Bool.

dacapo.blockwise.scheduler.segment_blockwise(segment_function_file: str | pathlib.Path, 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, *args, **kwargs)

Run a segmentation function in parallel over a large volume.