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fix: resolve TypeError during leaderboard sort on AutoML reload (fixes #681) #833

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fix: resolve TypeError during leaderboard sort on AutoML reload (fixes #681) #833

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8 changes: 7 additions & 1 deletion supervised/ensemble.py
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Original file line number Diff line number Diff line change
Expand Up @@ -571,7 +571,13 @@ def load(results_path, model_subpath, models_map):
{"model": models_map[m["model"]], "repeat": m["repeat"]}
]

ensemble.best_loss = json_desc.get("final_loss", ensemble.best_loss)
best_loss = json_desc.get("final_loss", ensemble.best_loss)
if best_loss is not None:
try:
best_loss = float(best_loss)
except ValueError:
pass
ensemble.best_loss = best_loss
ensemble.train_time = json_desc.get("train_time", ensemble.train_time)
ensemble._is_stacked = json_desc.get("is_stacked", ensemble._is_stacked)
predictions_fname = json_desc.get("predictions_fname")
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10 changes: 8 additions & 2 deletions supervised/model_framework.py
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Original file line number Diff line number Diff line change
Expand Up @@ -625,7 +625,7 @@ def save(self, results_path, model_subpath):
"is_stacked": self._is_stacked,
"joblib_version": joblib.__version__,
}
desc["final_loss"] = str(desc["final_loss"])
desc["final_loss"] = desc["final_loss"]
if self._threshold is not None:
desc["threshold"] = self._threshold
if self._single_prediction_time is not None:
Expand Down Expand Up @@ -707,7 +707,13 @@ def load(results_path, model_subpath, lazy_load=True):
mf._name = json_desc.get("name", mf._name)
mf._threshold = json_desc.get("threshold")
mf.train_time = json_desc.get("train_time", mf.train_time)
mf.final_loss = json_desc.get("final_loss", mf.final_loss)
final_loss = json_desc.get("final_loss", mf.final_loss)
if final_loss is not None:
try:
final_loss = float(final_loss)
except ValueError:
pass
mf.final_loss = final_loss
mf.metric_name = json_desc.get("metric_name", mf.metric_name)
mf._is_stacked = json_desc.get("is_stacked", mf._is_stacked)
mf._single_prediction_time = json_desc.get(
Expand Down