[AutoNLP]add predict (#4967)

* add_predict * fix * fix
PaddlePaddle · Feb 24, 2023 · f38a255 · f38a255
1 parent edf6fef
commit f38a255
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Showing 4 changed files with 341 additions and 198 deletions.
diff --git a/paddlenlp/experimental/autonlp/auto_trainer_base.py b/paddlenlp/experimental/autonlp/auto_trainer_base.py
@@ -138,6 +138,7 @@ def _preprocess_fn(
         preprocess an example from raw features to input features that Transformers models expect (e.g. input_ids, attention_mask, labels, etc)
         """
 
+    @abstractmethod
     def export(self, export_path, trial_id=None):
         """
         Export the model from a certain `trial_id` to the given file path.
@@ -171,15 +172,24 @@ def evaluate(self, trial_id=None, eval_dataset=None) -> Dict[str, float]:
         """
         raise NotImplementedError
 
+    @abstractmethod
+    def predict(self, test_dataset: Dataset, trial_id: Optional[str] = None):
+        """
+        Run prediction and returns predictions and potential metrics from a certain `trial_id` on the given dataset
+        Args:
+            test_dataset (Dataset, required): Custom test dataset and must contains the 'text_column' and 'label_column' fields.
+            trial_id (str, optional): Specify the model to be evaluated through the `trial_id`. Defaults to the best model selected by `metric_for_best_model`.
+        """
+        raise NotImplementedError
+
     def _override_hp(self, config: Dict[str, Any], default_hp: Any) -> Any:
         """
         Overrides the arguments with the provided hyperparameter config
         """
         new_hp = copy.deepcopy(default_hp)
         for key, value in config.items():
-            if key.startswith(default_hp.__class__.__name__):
-                _, hp_key = key.split(".")
-                setattr(new_hp, hp_key, value)
+            if key in new_hp.to_dict():
+                setattr(new_hp, key, value)
         return new_hp
 
     def _filter_model_candidates(
@@ -264,7 +274,7 @@ def train(
             experiment_name: (str, optional): name of the experiment. Experiment log will be stored under <output_dir>/<experiment_name>.
                 Defaults to UNIX timestamp.
             hp_overrides: (dict[str, Any], optional): Advanced users only.
-                override the hyperparameters of every model candidate.  For example, {"TrainingArguments.max_steps": 5}.
+                override the hyperparameters of every model candidate.  For example, {"max_steps": 5}.
             custom_model_candiates: (dict[str, Any], optional): Advanced users only.
                 Run the user-provided model candidates instead of the default model candidated from PaddleNLP. See `._model_candidates` property as an example