Serialize multi_label_threshold for classification models #2368
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yosipk
commented
Aug 13, 2021
| @@ -145,6 +146,7 @@ def _init_model_with_state_dict(state): | |||
| label_dictionary=state["label_dictionary"], | |||
| label_type=state["label_type"], | |||
| multi_label=state["multi_label"], | |||
| multi_label_threshold=0.5 if "multi_label_threshold" not in state.keys() else state["multi_label_threshold"], | |||
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Instead of default 0.5 the defaults can be read from the class:
super_defaults = inspect.signature(super(TextPairClassifier, self).__init__)
multi_label_threshold_default = super_defaults.parameters['multi_label_threshold'].default
and then use multi_label_threshold_default instead of 0.5.
| @@ -101,6 +102,7 @@ def _init_model_with_state_dict(state): | |||
| label_dictionary=state["label_dictionary"], | |||
| label_type=label_type, | |||
| multi_label=state["multi_label"], | |||
| multi_label_threshold=0.5 if "multi_label_threshold" not in state.keys() else state["multi_label_threshold"], | |||
There was a problem hiding this comment.
Instead of default 0.5 the defaults can be read from the class:
super_defaults = inspect.signature(super(TextClassifier, self).__init__)
multi_label_threshold_default = super_defaults.parameters['multi_label_threshold'].default
and then use multi_label_threshold_default instead of 0.5.
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Cool didn't know about this!
|
@yosipk thanks for adding this! |
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Closes #2367