cf73f9fd2638c07e0bddefb9ab918486067c4e80,finetune/target_models/deployment_model.py,DeploymentModel,predict,#DeploymentModel#Any#Any#Any#,177

Before Change

        if exclude_target: //to initialize featurizer weights
            return features

        self.target_est = self.get_estimator("target")
        preds = None
        if features is not None:
            target_est = self.get_estimator("target")
            target_fn = self.input_pipeline.get_target_input_fn(features)

After Change

        features = [None]*n
        for i in tqdm.tqdm(range(n), total=n, desc="Featurization"):
            y = next(self._predictions)
            for key in y:
                print(np.shape(y[key]))
            features[i] = y

        if exclude_target: //to initialize featurizer weights
            return features

Instances