8a420e8ef11ebf828e5e5b33e8a830eb74c39d6a,baseline/services.py,ClassifierService,predict,#ClassifierService#Any#Any#Any#,215

Before Change

            logger.warning("Warning: Passing `preproc` to `ClassifierService.predict` is deprecated.")
        tokens_batch = self.batch_input(tokens)
        self.prepare_vectorizers(tokens_batch)
        if self.preproc == "client":
            examples = self.vectorize(tokens_batch)
        elif self.preproc == "server":
            // TODO: here we allow vectorizers even for preproc=server to get `word_lengths`.
            // vectorizers should not be available when preproc=server.
            featurized_examples = self.vectorize(tokens_batch)
            examples = {
                        "tokens": np.array([" ".join(x) for x in tokens_batch]),
                        self.model.lengths_key: featurized_examples[self.model.lengths_key]
            }

        outcomes_list = self.model.predict(examples)
        return self.format_output(outcomes_list)

    def format_output(self, predicted):

After Change

        if backend not in {"tf"}:
            raise ValueError("only Tensorflow is currently supported for remote Services")
        import_user_module("baseline.{}.remote".format(backend))
        exp_type = kwargs.get("remote_type")
        if exp_type is None:
            exp_type = "http" if remote.startswith("http") else "grpc"
            exp_type = "{}-preproc".format(exp_type) if preproc == "server" else exp_type
            exp_type = f"{exp_type}-{task_name}"

Instances