Update pipeline.py

pipeline.py

@@ -12,10 +12,10 @@ class PreTrainedPipeline():
         self.pipeline = pipeline("text-classification", model=model, tokenizer=tokenizer)
 
 
-    def __call__(self, data: Any) -> List[List[Dict[str, float]]]:
+    def __call__(self, inputs: Any) -> List[List[Dict[str, float]]]:
         """
         Args:
-            data (:obj:`str`):
+            inputs (:obj:`str`):
                 a string containing some text
         Return:
             A :obj:`list`:. The object returned should be a list of one list like [[{"label": 0.9939950108528137}]] containing :
@@ -23,12 +23,4 @@ class PreTrainedPipeline():
                 - "score": A score between 0 and 1 describing how confident the model is for this label/class.
         """
         # pop inputs for pipeline
-        inputs = data.pop("inputs", data)
-        parameters = data.pop("parameters", None)
-
-        # pass inputs with all kwargs in data
-        if parameters is not None:
-            prediction = self.pipeline(inputs, **parameters)
-        else:
-            prediction = self.pipeline(inputs)
-        return prediction
+        return self.pipeline(inputs)