Upload NLIScorer

pipeline.py

@@ -363,13 +363,13 @@ class NLIScorer(Pipeline):
     def _sanitize_parameters(self, **kwargs):
         preprocess_kwargs = {}
         postprocess_kwargs = {}
-        if "task_name" in kwargs:
-            preprocess_kwargs["task_name"] = kwargs["task_name"]
-            preprocess_kwargs["task_name"] = kwargs["task_name"]
+        if "task_type" in kwargs:
+            preprocess_kwargs["task_type"] = kwargs["task_type"]
+            preprocess_kwargs["task_type"] = kwargs["task_type"]
         return preprocess_kwargs, {}, postprocess_kwargs
 
-    def preprocess(self, inputs, task_name):
-        TaskClass = TASK_CLASSES[task_name]
+    def preprocess(self, inputs, task_type):
+        TaskClass = TASK_CLASSES[task_type]
         task_class = TaskClass(tokenizer=self.tokenizer, **inputs)
         return task_class.as_model_inputs
 
@@ -377,8 +377,8 @@ class NLIScorer(Pipeline):
         outputs = self.model(**model_inputs)
         return outputs
 
-    def postprocess(self, model_outputs, task_name):
-        threshold = TASK_THRESHOLDS[task_name]
+    def postprocess(self, model_outputs, task_type):
+        threshold = TASK_THRESHOLDS[task_type]
         pos_scores = model_outputs["logits"].softmax(-1)[0][1]
         best_class = int(pos_scores > threshold)
         if best_class == 1: