Update pipeline.py

pipeline.py

@@ -12,15 +12,23 @@ class PreTrainedPipeline():
         self.pipeline = pipeline("text-classification", model=model, tokenizer=tokenizer)
 
 
-    def __call__(self, inputs: Any) -> List[List[Dict[str, float]]]:
+    def __call__(self, data: Any) -> List[List[Dict[str, float]]]:
         """
         Args:
-            inputs (:obj:`str`):
-                a string containing some text
+            data (:obj:):
+                includes the input data and the parameters for the inference.
         Return:
             A :obj:`list`:. The object returned should be a list of one list like [[{"label": 0.9939950108528137}]] containing :
                 - "label": A string representing what the label/class is. There can be multiple labels.
                 - "score": A score between 0 and 1 describing how confident the model is for this label/class.
         """
-        # pop inputs for pipeline
-        return self.pipeline(inputs)
+        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)
+        # postprocess the prediction
+        return prediction