Add FAISS reset after fixture teardown

test/conftest.py

@@ -210,18 +210,6 @@ def no_answer_prediction(no_answer_reader, test_docs_xs):
     return prediction
 
 
-@pytest.fixture(params=["elasticsearch", "faiss", "memory", "sql"])
-def document_store_with_docs(request, test_docs_xs):
-    document_store = get_document_store(request.param)
-    document_store.write_documents(test_docs_xs)
-    return document_store
-
-
-@pytest.fixture(params=["elasticsearch", "faiss", "memory", "sql"])
-def document_store(request, test_docs_xs):
-    return get_document_store(request.param)
-
-
 @pytest.fixture(params=["es_filter_only", "elasticsearch", "dpr", "embedding", "tfidf"])
 def retriever(request, document_store):
     return get_retriever(request.param, document_store)
@@ -232,6 +220,48 @@ def retriever_with_docs(request, document_store_with_docs):
     return get_retriever(request.param, document_store_with_docs)
 
 
+def get_retriever(retriever_type, document_store):
+
+    if retriever_type == "dpr":
+        retriever = DensePassageRetriever(document_store=document_store,
+                                          query_embedding_model="facebook/dpr-question_encoder-single-nq-base",
+                                          passage_embedding_model="facebook/dpr-ctx_encoder-single-nq-base",
+                                          use_gpu=False, embed_title=True)
+    elif retriever_type == "tfidf":
+        return TfidfRetriever(document_store=document_store)
+    elif retriever_type == "embedding":
+        retriever = EmbeddingRetriever(
+            document_store=document_store,
+            embedding_model="deepset/sentence_bert",
+            use_gpu=False
+        )
+    elif retriever_type == "elasticsearch":
+        retriever = ElasticsearchRetriever(document_store=document_store)
+    elif retriever_type == "es_filter_only":
+        retriever = ElasticsearchFilterOnlyRetriever(document_store=document_store)
+    else:
+        raise Exception(f"No retriever fixture for '{retriever_type}'")
+
+    return retriever
+
+
+@pytest.fixture(params=["elasticsearch", "faiss", "memory", "sql"])
+def document_store_with_docs(request, test_docs_xs):
+    document_store = get_document_store(request.param)
+    document_store.write_documents(test_docs_xs)
+    yield document_store
+    if request.param == "faiss":
+        document_store.faiss_index.reset()
+
+
+@pytest.fixture(params=["elasticsearch", "faiss", "memory", "sql"])
+def document_store(request, test_docs_xs):
+    document_store = get_document_store(request.param)
+    yield document_store
+    if request.param == "faiss":
+        document_store.faiss_index.reset()
+
+
 def get_document_store(document_store_type):
     if document_store_type == "sql":
         if os.path.exists("haystack_test.db"):
@@ -251,34 +281,8 @@ def get_document_store(document_store_type):
             sql_url="sqlite:///haystack_test_faiss.db",
             return_embedding=False
         )
-        document_store.faiss_index.reset()
         return document_store
     else:
         raise Exception(f"No document store fixture for '{document_store_type}'")
 
     return document_store
-
-
-def get_retriever(retriever_type, document_store):
-
-    if retriever_type == "dpr":
-        retriever = DensePassageRetriever(document_store=document_store,
-                                          query_embedding_model="facebook/dpr-question_encoder-single-nq-base",
-                                          passage_embedding_model="facebook/dpr-ctx_encoder-single-nq-base",
-                                          use_gpu=False, embed_title=True)
-    elif retriever_type == "tfidf":
-        return TfidfRetriever(document_store=document_store)
-    elif retriever_type == "embedding":
-        retriever = EmbeddingRetriever(
-            document_store=document_store,
-            embedding_model="deepset/sentence_bert",
-            use_gpu=False
-        )
-    elif retriever_type == "elasticsearch":
-        retriever = ElasticsearchRetriever(document_store=document_store)
-    elif retriever_type == "es_filter_only":
-        retriever = ElasticsearchFilterOnlyRetriever(document_store=document_store)
-    else:
-        raise Exception(f"No retriever fixture for '{retriever_type}'")
-
-    return retriever