Unify interface and data handling of model training and generalization metrics #2367
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…n metrics (facebook#2367) Summary: This commit unifies the interface of and the loading of the model's training data in `_predict_on_cross_validation_data` and `_predict_on_training_data`. Previously, `_predict_on_training_data` would reload the data from the experiment, which could lead to differences in the number of observations to `_predict_on_cross_validation_data` if the model was not fit on all existing data. In addition, this commit introduces a `force_refit` option for `get_fitted_model_bridge` which forces a reloading of the data and a refitting of the model to the reloaded data, even if a fitted, potentially out-dated model is on the scheduler. Differential Revision: D56105161
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Codecov ReportAttention: Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## main #2367 +/- ##
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+ Coverage 94.91% 95.29% +0.38%
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Files 491 495 +4
Lines 47788 48126 +338
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+ Hits 45356 45863 +507
+ Misses 2432 2263 -169 ☔ View full report in Codecov by Sentry. |
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…n metrics (facebook#2367) Summary: This commit unifies the interface of and the loading of the model's training data in `_predict_on_cross_validation_data` and `_predict_on_training_data`. Previously, `_predict_on_training_data` would reload the data from the experiment, which could lead to differences in the number of observations to `_predict_on_cross_validation_data` if the model was not fit on all existing data. In addition, this commit introduces a `force_refit` option for `get_fitted_model_bridge` which forces a reloading of the data and a refitting of the model to the reloaded data, even if a fitted, potentially out-dated model is on the scheduler. Differential Revision: D56105161
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…n metrics (facebook#2367) Summary: This commit unifies the interface of and the loading of the model's training data in `_predict_on_cross_validation_data` and `_predict_on_training_data`. Previously, `_predict_on_training_data` would reload the data from the experiment, which could lead to differences in the number of observations to `_predict_on_cross_validation_data` if the model was not fit on all existing data. In addition, this commit introduces a `force_refit` option for `get_fitted_model_bridge` which forces a reloading of the data and a refitting of the model to the reloaded data, even if a fitted, potentially out-dated model is on the scheduler. Differential Revision: D56105161
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…n metrics (facebook#2367) Summary: This commit unifies the interface of and the loading of the model's training data in `_predict_on_cross_validation_data` and `_predict_on_training_data`. Previously, `_predict_on_training_data` would reload the data from the experiment, which could lead to differences in the number of observations to `_predict_on_cross_validation_data` if the model was not fit on all existing data. In addition, this commit introduces a `force_refit` option for `get_fitted_model_bridge` which forces a reloading of the data and a refitting of the model to the reloaded data, even if a fitted, potentially out-dated model is on the scheduler. Reviewed By: sunnyshen321 Differential Revision: D56105161
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…n metrics (facebook#2367) Summary: This commit unifies the interface of and the loading of the model's training data in `_predict_on_cross_validation_data` and `_predict_on_training_data`. Previously, `_predict_on_training_data` would reload the data from the experiment, which could lead to differences in the number of observations to `_predict_on_cross_validation_data` if the model was not fit on all existing data. In addition, this commit introduces a `force_refit` option for `get_fitted_model_bridge` which forces a reloading of the data and a refitting of the model to the reloaded data, even if a fitted, potentially out-dated model is on the scheduler. Reviewed By: sunnyshen321 Differential Revision: D56105161
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This pull request has been merged in f8d5377. |
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Summary:
This commit unifies the interface of and the loading of the model's training data in
_predict_on_cross_validation_dataand_predict_on_training_data. Previously,_predict_on_training_datawould reload the data from the experiment, which could lead to differences in the number of observations to_predict_on_cross_validation_dataif the model was not fit on all existing data.In addition, this commit introduces a
force_refitoption forget_fitted_model_bridgewhich forces a reloading of the data and a refitting of the model to the reloaded data, even if a fitted, potentially out-dated model is on the scheduler.Differential Revision: D56105161