Create pipeline.py

pipeline.py

@@ -0,0 +1,36 @@
+from typing import List
+
+import os
+
+import fasttext.util
+
+class PreTrainedPipeline():
+
+    def __init__(self, path=""):
+
+        """
+
+        Initialize model
+
+        """
+
+        self.model = fasttext.load_model(os.path.join(path, 'debate2vec.bin'))
+
+    def __call__(self, inputs: str) -> List[float]:
+
+        """
+
+        Args:
+
+            inputs (:obj:`str`):
+
+                a string to get the features of.
+
+        Return:
+
+            A :obj:`list` of floats: The features computed by the model.
+
+        """
+
+        return self.model.get_sentence_vector(inputs).tolist()
+