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					@ -293,7 +293,7 @@ class TextCategorizer(TrainablePipe):
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        bp_scores(gradient)
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					        bp_scores(gradient)
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        if sgd is not None:
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					        if sgd is not None:
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            self.finish_update(sgd)
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					            self.finish_update(sgd)
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        losses[self.name] += (gradient ** 2).sum()
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					        losses[self.name] += (gradient**2).sum()
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        return losses
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					        return losses
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    def _examples_to_truth(
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					    def _examples_to_truth(
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					@ -327,7 +327,7 @@ class TextCategorizer(TrainablePipe):
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        not_missing = self.model.ops.asarray(not_missing)  # type: ignore
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					        not_missing = self.model.ops.asarray(not_missing)  # type: ignore
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        d_scores = scores - truths
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					        d_scores = scores - truths
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        d_scores *= not_missing
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					        d_scores *= not_missing
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        mean_square_error = (d_scores ** 2).mean()
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					        mean_square_error = (d_scores**2).mean()
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        return float(mean_square_error), d_scores
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					        return float(mean_square_error), d_scores
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    def add_label(self, label: str) -> int:
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					    def add_label(self, label: str) -> int:
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