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Fix log when training model #111

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Fix log when training model #111

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fa37f42
Fix log when training model
mirand863 Mar 8, 2024
9b6dfe4
Fix error in log
mirand863 Mar 10, 2024
79100b7
Fix error in log
mirand863 Mar 10, 2024
ee7c294
Catch unpickling error
mirand863 Mar 10, 2024
88c26fb
Add exception when unpickling
mirand863 Mar 18, 2024
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13 changes: 8 additions & 5 deletions hiclass/LocalClassifierPerLevel.py
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Original file line number Diff line number Diff line change
Expand Up @@ -258,11 +258,14 @@ def _fit_classifier(self, level, separator):
md5 = hashlib.md5(str(level).encode("utf-8")).hexdigest()
filename = f"{self.tmp_dir}/{md5}.sav"
if exists(filename):
(_, classifier) = pickle.load(open(filename, "rb"))
self.logger_.info(
f"Loaded trained model for local classifier {level} from file {filename}"
)
return classifier
try:
(_, classifier) = pickle.load(open(filename, "rb"))
self.logger_.info(
f"Loaded trained model for local classifier {level} from file {filename}"
)
return classifier
except (pickle.UnpicklingError, EOFError):
self.logger_.error(f"Could not load model from file {filename}")
self.logger_.info(f"Training local classifier {level}")
X, y, sample_weight = self._remove_empty_leaves(
separator, self.X_, self.y_[:, level], self.sample_weight_
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17 changes: 11 additions & 6 deletions hiclass/LocalClassifierPerNode.py
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Original file line number Diff line number Diff line change
Expand Up @@ -249,12 +249,17 @@ def _fit_classifier(self, node):
md5 = hashlib.md5(node.encode("utf-8")).hexdigest()
filename = f"{self.tmp_dir}/{md5}.sav"
if exists(filename):
(_, classifier) = pickle.load(open(filename, "rb"))
self.logger_.info(
f"Loaded trained model for local classifier {node.split(self.separator_)[-1]} from file {filename}"
)
return classifier
self.logger_.info(f"Training local classifier {node}")
try:
(_, classifier) = pickle.load(open(filename, "rb"))
self.logger_.info(
f"Loaded trained model for local classifier {node.split(self.separator_)[-1]} from file {filename}"
)
return classifier
except (pickle.UnpicklingError, EOFError):
self.logger_.error(f"Could not load model from file {filename}")
self.logger_.info(
f"Training local classifier {str(node).split(self.separator_)[-1]}"
)
X, y, sample_weight = self.binary_policy_.get_binary_examples(node)
unique_y = np.unique(y)
if len(unique_y) == 1 and self.replace_classifiers:
Expand Down
17 changes: 11 additions & 6 deletions hiclass/LocalClassifierPerParentNode.py
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Original file line number Diff line number Diff line change
Expand Up @@ -218,12 +218,17 @@ def _fit_classifier(self, node):
md5 = hashlib.md5(node.encode("utf-8")).hexdigest()
filename = f"{self.tmp_dir}/{md5}.sav"
if exists(filename):
(_, classifier) = pickle.load(open(filename, "rb"))
self.logger_.info(
f"Loaded trained model for local classifier {node.split(self.separator_)[-1]} from file {filename}"
)
return classifier
self.logger_.info(f"Training local classifier {node}")
try:
(_, classifier) = pickle.load(open(filename, "rb"))
self.logger_.info(
f"Loaded trained model for local classifier {node.split(self.separator_)[-1]} from file {filename}"
)
return classifier
except (pickle.UnpicklingError, EOFError):
self.logger_.error(f"Could not load model from file {filename}")
self.logger_.info(
f"Training local classifier {str(node).split(self.separator_)[-1]}"
)
# get children examples
X, y, sample_weight = self._get_successors(node)
unique_y = np.unique(y)
Expand Down