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kamil-kaczmarek avatar kamil-kaczmarek commented on June 16, 2024

Hi @tankz0r you in this case it is the same.

In larger pipelines we use it is this way:

pipeline = PIPELINES[pipeline_name](config=cfg.SOLUTION_CONFIG, train_mode=True)
pipeline.clean_cache()
logger.info('Start pipeline fit and transform')
pipeline.fit_transform(train_data)
pipeline.clean_cache()

So we make sure that we have clean cache directory before we run experiment :)

Also, we are going to change it in such a way, that cache will be in memory. For example interface like: Step.cache that will contain output from transformer.

from steppy.

kamil-kaczmarek avatar kamil-kaczmarek commented on June 16, 2024

seems like question is covered. Closing this :)

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