cf_engine#

Custom CFClient API to match Dask’s CFClient and allow context management.

Module Contents#

Classes Summary#

`CFClient`	Custom CFClient API to match Dask's CFClient and allow context management.
`CFComputation`	A Future-like wrapper around jobs created by the CFEngine.
`CFEngine`	The concurrent.futures (CF) engine.

Contents#

class evalml.automl.engine.cf_engine.CFClient(pool)[source]#

Custom CFClient API to match Dask’s CFClient and allow context management.

Parameters: pool (cf.ThreadPoolExecutor or cf.ProcessPoolExecutor) – The resource pool to execute the futures work on.

Methods

`close`	Closes the underlying Executor.
`is_closed`	Property that determines whether the Engine's Client's resources are closed.
`submit`	Pass through to imitate Dask's Client API.

close(self)[source]#: Closes the underlying Executor.

property is_closed(self)#: Property that determines whether the Engine’s Client’s resources are closed.

submit(self, *args, **kwargs)[source]#: Pass through to imitate Dask’s Client API.

class evalml.automl.engine.cf_engine.CFComputation(future)[source]#

A Future-like wrapper around jobs created by the CFEngine.

Parameters: future (cf.Future) – The concurrent.futures.Future that is desired to be executed.

Methods

`cancel`	Cancel the current computation.
`done`	Returns whether the computation is done.
`get_result`	Gets the computation result. Will block until the computation is finished.
`is_cancelled`	Returns whether computation was cancelled.

cancel(self)[source]#

Cancel the current computation.

Returns

False if the call is currently being executed or finished running: and cannot be cancelled. True if the call can be canceled.

Return type

bool

done(self)[source]#: Returns whether the computation is done.

get_result(self)[source]#

Gets the computation result. Will block until the computation is finished.

Raises

Exception – If computation fails. Returns traceback.
cf.TimeoutError – If computation takes longer than default timeout time.
cf.CancelledError – If computation was canceled before completing.

Returns

The result of the requested job.

property is_cancelled(self)#: Returns whether computation was cancelled.

class evalml.automl.engine.cf_engine.CFEngine(client=None)[source]#

The concurrent.futures (CF) engine.

Parameters: client (None or CFClient) – If None, creates a threaded pool for processing. Defaults to None.

Methods

`close`	Function to properly shutdown the Engine's Client's resources.
`is_closed`	Property that determines whether the Engine's Client's resources are shutdown.
`setup_job_log`	Set up logger for job.
`submit_evaluation_job`	Send evaluation job to cluster.
`submit_scoring_job`	Send scoring job to cluster.
`submit_training_job`	Send training job to cluster.

close(self)[source]#: Function to properly shutdown the Engine’s Client’s resources.

property is_closed(self)#: Property that determines whether the Engine’s Client’s resources are shutdown.

static setup_job_log()#: Set up logger for job.

submit_evaluation_job(self, automl_config, pipeline, X, y, X_holdout=None, y_holdout=None)[source]#

Send evaluation job to cluster.

Parameters

automl_config – Structure containing data passed from AutoMLSearch instance.
pipeline (pipeline.PipelineBase) – Pipeline to evaluate.
X (pd.DataFrame) – Input data for modeling.
y (pd.Series) – Target data for modeling.
X_holdout (pd.Series) – Holdout input data for holdout scoring.
y_holdout (pd.Series) – Holdout target data for holdout scoring.

Returns

An object wrapping a reference to a future-like computation: occurring in the resource pool

Return type

CFComputation

submit_scoring_job(self, automl_config, pipeline, X, y, objectives, X_train=None, y_train=None)[source]#

Send scoring job to cluster.

Parameters

automl_config – Structure containing data passed from AutoMLSearch instance.
pipeline (pipeline.PipelineBase) – Pipeline to train.
X (pd.DataFrame) – Input data for modeling.
y (pd.Series) – Target data for modeling.
X_train (pd.DataFrame) – Training features. Used for feature engineering in time series.
y_train (pd.Series) – Training target. Used for feature engineering in time series.
objectives (list[ObjectiveBase]) – Objectives to score on.

Returns

An object wrapping a reference to a future-like computation: occurring in the resource pool.

Return type

CFComputation

submit_training_job(self, automl_config, pipeline, X, y)[source]#

Send training job to cluster.

Parameters

automl_config – Structure containing data passed from AutoMLSearch instance.
pipeline (pipeline.PipelineBase) – Pipeline to train.
X (pd.DataFrame) – Input data for modeling.
y (pd.Series) – Target data for modeling.

Returns

An object wrapping a reference to a future-like computation: occurring in the resource pool

Return type

CFComputation