dacapo.blockwise.segment_worker
Attributes
Functions
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CLI for running the segment worker. |
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Start a worker to run a segment function on a given dataset. |
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Spawn a worker to predict on a given dataset. |
Module Contents
- dacapo.blockwise.segment_worker.logger
- dacapo.blockwise.segment_worker.cli(log_level)
CLI for running the segment worker.
- Parameters:
log_level (str) – The log level to use.
- dacapo.blockwise.segment_worker.fit = 'shrink'
- dacapo.blockwise.segment_worker.read_write_conflict = True
- dacapo.blockwise.segment_worker.path
- dacapo.blockwise.segment_worker.start_worker(input_container: str | upath.UPath, input_dataset: str, output_container: str | upath.UPath, output_dataset: str, tmpdir: str | upath.UPath, function_path: str | upath.UPath, return_io_loop: bool = False)
- dacapo.blockwise.segment_worker.start_worker_fn(input_container: str | upath.UPath, input_dataset: str, output_container: str | upath.UPath, output_dataset: str, tmpdir: str | upath.UPath, function_path: str | upath.UPath, return_io_loop: bool = False)
Start a worker to run a segment function on a given dataset.
- Parameters:
input_container (str) – The input container.
input_dataset (str) – The input dataset.
output_container (str) – The output container.
output_dataset (str) – The output dataset.
tmpdir (str) – The temporary directory.
function_path (str) – The path to the segment function.
return_io_loop (bool) – Whether to return the io loop or run it.
- dacapo.blockwise.segment_worker.spawn_worker(input_array_identifier: dacapo.store.array_store.LocalArrayIdentifier, output_array_identifier: dacapo.store.array_store.LocalArrayIdentifier, tmpdir: str, function_path: str)
Spawn a worker to predict on a given dataset.
- Parameters:
model (Model) – The model to use for prediction.
raw_array (Array) – The raw data to predict on.
prediction_array_identifier (LocalArrayIdentifier) – The identifier of the prediction array.
- Returns:
The function to run the worker.
- Return type:
Callable