cab8566e1e7ac059bde5355b4057c94f42a7fd6d,baseline/services.py,ONNXTaggerService,predict,#ONNXTaggerService#Any#,418

Before Change

    def predict(self, tokens, **kwargs):
        tokens_batch = self.batch_input(tokens)
        self.prepare_vectorizers(tokens_batch)
        examples = self.vectorize(tokens_batch)
        outcomes_list = self.model.run(None, examples)
        outcomes_list = outcomes_list[0]
        return self.format_output(tokens, outcomes_list)

    def format_output(self, tokens, predicted):
        results = []

After Change

        self.prepare_vectorizers(tokens_batch)
        // Process each example in the batch by itself to hide the one at a time nature
        examples = [self.vectorize([tokens]) for tokens in tokens_batch]
        outcomes_list = np.concatenate([self.model.run(None, example)[0] for example in examples], axis=0)
        return self.format_output(outcomes_list, tokens_batch, label_field=kwargs.get("label", "label"))

    def vectorize(self, tokens_batch):

Instances