feat: replace traversal_paths with access_paths

dpr_text.py

@@ -24,7 +24,8 @@ def __init__(
         base_tokenizer_model: Optional[str] = None,
         title_tag_key: Optional[str] = None,
         max_length: Optional[int] = None,
-        traversal_paths: str = "@r",
+        access_paths: str = '@r',
+        traversal_paths: Optional[str] = None,
         batch_size: int = 32,
         device: str = "cpu",
         *args,
@@ -45,8 +46,9 @@ def __init__(
             tag property. It is recommended to set this property for context encoders,
             to match the model pre-training. It has no effect for question encoders.
         :param max_length: Max length argument for the tokenizer
-        :param traversal_paths: Default traversal paths for encoding, used if the
-            traversal path is not passed as a parameter with the request.
+        :param access_paths: Default access paths for encoding, used if the
+            access path is not passed as a parameter with the request.
+        :param traversal_paths: Please use `access_paths`
         :param batch_size: Default batch size for encoding, used if the
             batch size is not passed as a parameter with the request.
         :param device: The device (cpu or gpu) that the model should be on.
@@ -102,7 +104,16 @@ def __init__(
 
         self.model = self.model.to(self.device).eval()
 
-        self.traversal_paths = traversal_paths
+        self.access_paths = access_paths
+        if traversal_paths is not None:
+            import warnings
+            warnings.warn(
+                f'`traversal_paths` is renamed to `access_paths` with the same usage, please use the latter instead. '
+                f'`traversal_paths` will be removed soon.',
+                DeprecationWarning,
+            )
+            self.access_paths = traversal_paths
+
         self.batch_size = batch_size
 
     @requests
@@ -117,13 +128,23 @@ def encode(
             ``text`` attribute.
         :param parameters: dictionary to define the ``traversal_path`` and the
             ``batch_size``. For example,
-            ``parameters={'traversal_paths': '@r', 'batch_size': 10}``
+            ``parameters={'access_paths': '@r', 'batch_size': 10}``
         """
 
+        access_paths = parameters.get('traversal_paths', None)
+        if access_paths is not None:
+            import warnings
+            warnings.warn(
+                f'`traversal_paths` is renamed to `access_paths` with the same usage, please use the latter instead. '
+                f'`traversal_paths` will be removed soon.',
+                DeprecationWarning,
+            )
+            parameters['access_paths'] = access_paths
+
         document_batches_generator = DocumentArray(
             filter(
                 lambda x: bool(x.text),
-                docs[parameters.get("traversal_paths", self.traversal_paths)],
+                docs[parameters.get("access_paths", self.access_paths)],
             )
         ).batch(batch_size=parameters.get("batch_size", self.batch_size))
 

tests/unit/test_encoder.py

@@ -83,7 +83,7 @@ def test_encoding_gpu():
 
 
 @pytest.mark.parametrize(
-    "traversal_paths, counts",
+    "access_paths, counts",
     [
         ("@r", [["@r", 1], ["@c", 0], ["@cc", 0]]),
         ("@c", [["@r", 0], ["@c", 3], ["@cc", 0]]),
@@ -92,7 +92,7 @@ def test_encoding_gpu():
     ],
 )
 def test_traversal_path(
-    traversal_paths: List[str], counts: List, basic_encoder: DPRTextEncoder
+    access_paths: List[str], counts: List, basic_encoder: DPRTextEncoder
 ):
     text = "blah"
     docs = DocumentArray([Document(id="root1", text=text)])
@@ -106,7 +106,7 @@ def test_traversal_path(
         Document(id="chunk112", text=text),
     ]
 
-    basic_encoder.encode(docs=docs, parameters={"traversal_paths": traversal_paths})
+    basic_encoder.encode(docs=docs, parameters={"access_paths": access_paths})
     for path, count in counts:
         embeddings = docs[path].embeddings