Torch lightning example for MLP logistic hazard model #66
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havakv
reviewed
Jan 28, 2021
havakv
reviewed
Jan 31, 2021
havakv
reviewed
Jan 31, 2021
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| standardize = [([col], StandardScaler()) for col in cols_standardize] | ||
| leave = [(col, None) for col in cols_leave] | ||
| x_mapper = DataFrameMapper(standardize + leave) |
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You don't have to use DataFrameMapper if you prefer some other way of preprocessing data. I tend to use it, but it is generally not that common.
havakv
reviewed
Jan 31, 2021
havakv
reviewed
Jan 31, 2021
| #Train model | ||
| trainer.fit(model,dat) | ||
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| #Load model from best checkpoint & freeze |
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Do you actually load from a checkpoint here? Isn't this just the final model?
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Yep you're right, that's just the final model. Fixed
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We should probably also change all indentation tabs to spaces to be consistent with the rest of pycox. I can do that for you if you want. |
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Thanks for the review! I'll refactor + address the comments and commit shortly |
…equirements.txt
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Traditionally the
test_stepfunction within thesurv_modelLightningModule class handles loading the data + calculating metrics for the test stage. Given the way the metrics are calculated I figured it's best to handle the test stage in vanilla pytorch.