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Grid search:
save data (per algo detect what frames need to be saved)
save params
enable model checkpointing
On crash:
reload data
reload trained models
restart gridsearch with same params (grid will auto continue where we left off)
Proposed roadmap:
Stage 1 (this jira, end of January 2021):
• Introduce a generic API for automatic checkpointing and resuming from a checkpoint in H2O-3 - this would utilize existing building blocks in h2o
• SW will need to be able H2O cluster failure, dispose of the cluster, start anew one and ask H2O to resume from a checkpoint
• This solution will work for Grid Search and for algos that currently support checkpointing, for algos that do not support checkpointing (GLM) - the work will be seamlessly restarted from scratch
Stage 2 (Q1 2021):
• Add support for AutoML
• Add support for checkpointing to algos that do not currently support it (GLM, CoxPH, …) - based on booking preference
The text was updated successfully, but these errors were encountered:
Grid search:
save data (per algo detect what frames need to be saved)
save params
enable model checkpointing
On crash:
reload data
reload trained models
restart gridsearch with same params (grid will auto continue where we left off)
Proposed roadmap:
Stage 1 (this jira, end of January 2021):
• Introduce a generic API for automatic checkpointing and resuming from a checkpoint in H2O-3 - this would utilize existing building blocks in h2o
• SW will need to be able H2O cluster failure, dispose of the cluster, start anew one and ask H2O to resume from a checkpoint
• This solution will work for Grid Search and for algos that currently support checkpointing, for algos that do not support checkpointing (GLM) - the work will be seamlessly restarted from scratch
Stage 2 (Q1 2021):
• Add support for AutoML
• Add support for checkpointing to algos that do not currently support it (GLM, CoxPH, …) - based on booking preference
The text was updated successfully, but these errors were encountered: