dacapo.blockwise.predict_worker

Attributes

logger

read_write_conflict

fit

path

Functions

cli(log_level)

CLI for running the predict worker.

start_worker(run_name, iteration, input_container, ...)

start_worker_fn(run_name, iteration, input_container, ...)

Start a worker to apply a trained model to a dataset.

spawn_worker(run_name, iteration, ...)

Spawn a worker to predict on a given dataset.

Module Contents

dacapo.blockwise.predict_worker.logger
dacapo.blockwise.predict_worker.read_write_conflict: bool = False
dacapo.blockwise.predict_worker.fit: str = 'valid'
dacapo.blockwise.predict_worker.path
dacapo.blockwise.predict_worker.cli(log_level)

CLI for running the predict worker.

The predict worker is used to apply a trained model to a dataset.

Parameters:

log_level (str) – The log level to use for logging.

dacapo.blockwise.predict_worker.start_worker(run_name: str, iteration: int | None, input_container: upath.UPath | str, input_dataset: str, output_container: upath.UPath | str, output_dataset: str, return_io_loop: bool | None = False)
dacapo.blockwise.predict_worker.start_worker_fn(run_name: str, iteration: int | None, input_container: upath.UPath | str, input_dataset: str, output_container: upath.UPath | str, output_dataset: str, return_io_loop: bool | None = False)

Start a worker to apply a trained model to a dataset.

Parameters:

  • run_name (str) – The name of the run to apply.

  • iteration (int or None) – The training iteration of the model to use for prediction.

  • input_container (Path | str) – The input container.

  • input_dataset (str) – The input dataset.

  • output_container (Path | str) – The output container.

  • output_dataset (str) – The output dataset.

dacapo.blockwise.predict_worker.spawn_worker(run_name: str, iteration: int | None, input_array_identifier: dacapo.store.array_store.LocalArrayIdentifier, output_array_identifier: dacapo.store.array_store.LocalArrayIdentifier)

Spawn a worker to predict on a given dataset.

Parameters:

  • run_name (str) – The name of the run to apply.

  • iteration (int or None) – The training iteration of the model to use for prediction.

  • input_array_identifier (LocalArrayIdentifier) – The raw data to predict on.

  • output_array_identifier (LocalArrayIdentifier) – The identifier of the prediction array.

Returns:

The function to run the worker.

Return type:

Callable