Black_lodge model/Production model template #37
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Copy pasted from src/utils in @xiaolong0728 blank_space. This script might be a good place to also do input data checks.
Getting error though, probably having issues with views6: TypeError: __init__() got an unexpected keyword argument 'from_loa'
Logic taken from viewsforecasting notebook
Adaoted from purple_alien
Not yet tested
Polichinel
requested review from
Polichinel,
angelicalmcgowan,
aatimlick and
xiaolong0728
xiaolong0728
reviewed
Jul 1, 2024
| "steps": [*range(1, 36 + 1, 1)], | ||
| "deployment_status": "production", | ||
| "creator": "Sara", | ||
| "preprocessing": "float_it", #new |
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where is the float_it function?
xiaolong0728
reviewed
Jul 1, 2024
| month_first = partitioner_dict['train'][0] | ||
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| if partition == 'forecasting': | ||
| month_last = partitioner_dict['train'][1] + 1 # no need to get the predict months as these are empty |
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To make the current stepshifter work, we still need the predict months even if they are empty (otherwise the predictions might have some problems)
xiaolong0728
reviewed
Jul 1, 2024
| from config_hyperparameters import get_hp_config | ||
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| def train(model_config, para_config): |
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You can refer to my new training function (I haven't merged the main so it's branch more_model and you can check orange_pasta). In short, we don't train three models together but train a specific one based on the arguments instead.
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[Not ready to be merged]
Let's use this PR to clean up the CM model code for replicating the production ensemble
To-dos are in the model readme