ads.opctl.backend package

Submodules

ads.opctl.backend.ads_dataflow module

class ads.opctl.backend.ads_dataflow.DataFlowBackend(config: Dict)

Bases: Backend

Initialize a MLJobBackend object given config dictionary.

Parameters:

config (dict) – dictionary of configurations

apply()

Create DataFlow and DataFlow Run from YAML.

cancel()

Cancel DataFlow Run from OCID.

delete()

Delete DataFlow or DataFlow Run from OCID.

run() → None

Create DataFlow and DataFlow Run from OCID or cli parameters.

watch()

Watch DataFlow Run from OCID.

ads.opctl.backend.ads_ml_job module

class ads.opctl.backend.ads_ml_job.MLJobBackend(config: Dict)

Bases: Backend

Initialize a MLJobBackend object given config dictionary.

Parameters:

config (dict) – dictionary of configurations

apply() → None

Create Job and Job Run from YAML.

cancel()

Cancel Job Run from OCID.

delete()

Delete Job or Job Run from OCID.

init_operator()
run() → None

Create Job and Job Run from OCID or cli parameters.

watch()

Watch Job Run from OCID.

class ads.opctl.backend.ads_ml_job.MLJobDistributedBackend(config: Dict)

Bases: MLJobBackend

Initialize a MLJobDistributedBackend object given config dictionary.

Parameters:

config (dict) – dictionary of configurations

DIAGNOSTIC_COMMAND = 'python -m ads.opctl.diagnostics -t distributed'
static generate_worker_name(worker_jobrun_conf, i)
prepare_job_config(cluster_info)
run(cluster_info, dry_run=False) → None

  • Creates Job Definition and starts main and worker jobruns from that job definition

  • The Job Definition will contain all the environment variables defined at the cluster/spec/config level, environment variables defined by the user at runtime/spec/env level and OCI__ derived from the yaml specification

  • The Job Run will have overrides provided by the user under cluster/spec/{main|worker}/config section and `OCI__MODE`={MASTER|WORKER} depending on the run type

run_diagnostics(cluster_info, dry_run=False, **kwargs)

Implement Diagnostics check appropriate for the backend

ads.opctl.backend.ads_ml_pipeline module

class ads.opctl.backend.ads_ml_pipeline.PipelineBackend(config: Dict)

Bases: Backend

Initialize a MLPipeline object given config dictionary.

Parameters:

config (dict) – dictionary of configurations

apply() → None

Create Pipeline and Pipeline Run from YAML.

cancel() → None

Cancel Pipeline Run from OCID.

delete() → None

Delete Pipeline or Pipeline Run from OCID.

run() → None

Create Pipeline and Pipeline Run from OCID.

watch() → None

Watch Pipeline Run from OCID.

ads.opctl.backend.base module

class ads.opctl.backend.base.Backend(config: Dict)

Bases: object

Interface for backend

apply() → None

Initiate Data Science service from YAML.

Return type:

None

cancel() → None

Cancel a remote run.

Return type:

None

delete() → None

Delete a remote run.

Return type:

None

abstract run() → Dict

Initiate a run.

Return type:

None

run_diagnostics()

Implement Diagnostics check appropriate for the backend

watch() → None

Stream logs from a remote run.

Return type:

None

ads.opctl.backend.local module

Module contents