cf_engine¶

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.

Methods

submit

Pass through to imitate Dask’s Client API.

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.

Methods

`cancel`	Cancel the current computation.
`done`	returns Whether the computation is done.
`get_result`	Gets the computation result.
`is_cancelled`	returns 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.
Return type: bool

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: Returns whether computation was cancelled.
Return type: bool

class evalml.automl.engine.cf_engine.CFEngine(client)[source]¶

The concurrent.futures (CF) engine

Methods

`setup_job_log`
`submit_evaluation_job`	Send evaluation job to cluster.
`submit_scoring_job`	Send scoring job to cluster.
`submit_training_job`	Send training job to cluster.

static setup_job_log()¶

submit_evaluation_job(self, automl_config, pipeline, X, y) → evalml.automl.engine.engine_base.EngineComputation [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

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) → evalml.automl.engine.engine_base.EngineComputation [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

Returns

a 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) → evalml.automl.engine.engine_base.EngineComputation [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

engine dask_engine