Create pipeline.py

pipeline.py

@@ -0,0 +1,28 @@
+from typing import Dict, List, Union
+import os
+
+class PreTrainedPipeline():
+    def __init__(self, path=""):
+        # IMPLEMENT_THIS
+        # Preload all the elements you are going to need at inference.
+        # For instance your model, processors, tokenizer that might be needed.
+        # This function is only called once, so do all the heavy processing I/O here"""
+        raise NotImplementedError(
+            "Please implement PreTrainedPipeline __init__ function"
+        )
+
+    def __call__(
+        self, inputs: Dict[str, Dict[str, List[Union[str, float]]]]
+    ) -> List[Union[str, float]]:
+        """
+        Args:
+            inputs (:obj:`dict`):
+                a dictionary containing a key 'data' mapping to a dict in which
+                the values represent each column.
+        Return:
+            A :obj:`list` of floats or strings: The classification output for each row.
+        """
+        # IMPLEMENT_THIS
+        raise NotImplementedError(
+            "Please implement PreTrainedPipeline __call__ function"
+        )