NVIDIA Clara Train 4.1

automl.components.handlers package

class Handler

Bases: object

This class defines the abstract behavior required of a Handler.

A handler is an object that listens to certain AutoML workflow events and takes actions on such events.

end_automl(ctx: automl.defs.Context)

AUTOML process has ended. Called from the engine thread. :param ctx: the main context

Returns:

end_job(ctx: automl.defs.Context)

The job execution has ended. Called from the job thread. See notes in start_job method. You can check the job status from prop ContextKey.JOB_STATUS in the ctx.

NOTE: if the start_job is called, it is guaranteed that end_job will be called.

Parameters

ctx – the job context

Returns:

handle_event(event: str, ctx: automl.defs.Context)

The default event handler that calls a predefined method for each event type.

Parameters
  • event – event to be handled

  • ctx – context for cross-component data sharing

Returns:

recommendations_available(ctx: automl.defs.Context)

The recommendations are available. Called from the main thread. You can get recommendations from prop ContextKey.RECOMMENDATIONS in the ctx.

Parameters

ctx – main context

Returns:

search_space_available(ctx: automl.defs.Context)

The search space is available. Called from the main thread. You can get the search space from prop ContextKey.SEARCH_SPACE in the ctx.

Parameters

ctx – main context

Returns:

shutdown(ctx: automl.defs.Context)

The handler is being shutdown. Use this method to clean up the handler.

NOTE: this method is called in the reverse order of handler chain. If your handler depends on other handlers, your handler will be shutdown before the handlers you depend on.

Parameters

ctx

Returns:

start_automl(ctx: automl.defs.Context)

AUTOML process is about to start. Called from the engine thread.

Parameters

ctx – the main context

Returns:

start_job(ctx: automl.defs.Context)

The job execution is about to start. Called from the job thread.

NOTE: this method could be called from multiple job threads at the same time. If you want to store across-job state data in the handler, you should ensure thread safety when updating such state data.

NOTE: the ctx is a per-job context, hence it is not subject to multi-thread access. Consider using the ctx to store per-job state data.

Parameters

ctx – the job context

Returns:

startup(ctx: automl.defs.Context)

The handler is being started up. Use this method to initialize the handler based on info in the context.

NOTE: this method is called in the order of handler chain. If your handler depends on some info provided by previous handlers, you can get such info from the ctx.

Parameters

ctx – main context

Returns:

fire_event(event: str, handlers: list, ctx: automl.defs.Context)

Fires the specified event and invokes the list of handlers.

Parameters
  • event – the event to be fired

  • handlers – handlers to be invoked

  • ctx – context for cross-component data sharing

Returns:

class StatsHandler

Bases: automl.components.handlers.handler.Handler

Defines a simple stats handler that collects job execution stats.

For each worker, it computes things like the number of jobs started, number of jobs finished and unfinished, and total amount of time the worker worked. It also shows the total amount of time used by the whole workflow.

end_automl(ctx: automl.defs.Context)

Print worker stats and overall stats

Parameters

ctx – main context

Returns:

end_job(ctx: automl.defs.Context)

Update job stats of the worker

Parameters

ctx – job context

Returns:

start_automl(ctx: automl.defs.Context)

Record the start time of AutoML

Parameters

ctx – AutoML main context

Returns:

start_job(ctx: automl.defs.Context)

Record the start time of the job in ctx; count total number of jobs started

Parameters

ctx – job context

Returns:

class WorkerStats

Bases: object

Define a simple stats structure for workers: only keep job count and total work time of a worker

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