def test_eval_pipeline(document_store: BaseDocumentStore, reader, retriever): # add eval data (SQUAD format) document_store.add_eval_data( filename="samples/squad/tiny.json", doc_index="haystack_test_eval_document", label_index="haystack_test_feedback", ) labels = document_store.get_all_labels_aggregated( index="haystack_test_feedback") q_to_l_dict = {l.question: {"retriever": l, "reader": l} for l in labels} eval_retriever = EvalRetriever() eval_reader = EvalReader() assert document_store.get_document_count( index="haystack_test_eval_document") == 2 p = Pipeline() p.add_node(component=retriever, name="ESRetriever", inputs=["Query"]) p.add_node(component=eval_retriever, name="EvalRetriever", inputs=["ESRetriever"]) p.add_node(component=reader, name="QAReader", inputs=["EvalRetriever"]) p.add_node(component=eval_reader, name="EvalReader", inputs=["QAReader"]) for q, l in q_to_l_dict.items(): res = p.run( query=q, top_k_retriever=10, labels=l, top_k_reader=10, index="haystack_test_eval_document", ) assert eval_retriever.recall == 1.0 assert round(eval_reader.top_k_f1, 4) == 0.8333 assert eval_reader.top_k_em == 0.5
def test_eval_finder(document_store: BaseDocumentStore, reader, retriever): finder = Finder(reader=reader, retriever=retriever) # add eval data (SQUAD format) document_store.add_eval_data( filename="samples/squad/tiny.json", doc_index="haystack_test_eval_document", label_index="haystack_test_feedback", ) assert document_store.get_document_count(index="haystack_test_eval_document") == 2 # eval finder results = finder.eval( label_index="haystack_test_feedback", doc_index="haystack_test_eval_document", top_k_retriever=1, top_k_reader=5 ) assert results["retriever_recall"] == 1.0 assert results["retriever_map"] == 1.0 assert abs(results["reader_topk_f1"] - 0.66666) < 0.001 assert abs(results["reader_topk_em"] - 0.5) < 0.001 assert abs(results["reader_topk_accuracy"] - 1) < 0.001 assert results["reader_top1_f1"] <= results["reader_topk_f1"] assert results["reader_top1_em"] <= results["reader_topk_em"] assert results["reader_top1_accuracy"] <= results["reader_topk_accuracy"] # batch eval finder results_batch = finder.eval_batch( label_index="haystack_test_feedback", doc_index="haystack_test_eval_document", top_k_retriever=1, top_k_reader=5 ) assert results_batch["retriever_recall"] == 1.0 assert results_batch["retriever_map"] == 1.0 assert results_batch["reader_top1_f1"] == results["reader_top1_f1"] assert results_batch["reader_top1_em"] == results["reader_top1_em"] assert results_batch["reader_topk_accuracy"] == results["reader_topk_accuracy"]
def test_eval_elastic_retriever(document_store: BaseDocumentStore, open_domain, retriever): # add eval data (SQUAD format) document_store.delete_all_documents(index="test_eval_document") document_store.delete_all_documents(index="test_feedback") document_store.add_eval_data(filename="samples/squad/tiny.json", doc_index="test_eval_document", label_index="test_feedback") assert document_store.get_document_count(index="test_eval_document") == 2 # eval retriever results = retriever.eval(top_k=1, label_index="test_feedback", doc_index="test_eval_document", open_domain=open_domain) assert results["recall"] == 1.0 assert results["map"] == 1.0 # clean up document_store.delete_all_documents(index="test_eval_document") document_store.delete_all_documents(index="test_feedback")
def test_eval_reader(reader, document_store: BaseDocumentStore): # add eval data (SQUAD format) document_store.delete_all_documents(index="test_eval_document") document_store.delete_all_documents(index="test_feedback") document_store.add_eval_data(filename="samples/squad/tiny.json", doc_index="test_eval_document", label_index="test_feedback") assert document_store.get_document_count(index="test_eval_document") == 2 # eval reader reader_eval_results = reader.eval(document_store=document_store, label_index="test_feedback", doc_index="test_eval_document", device="cpu") assert reader_eval_results["f1"] > 0.65 assert reader_eval_results["f1"] < 0.67 assert reader_eval_results["EM"] == 0.5 assert reader_eval_results["top_n_accuracy"] == 1.0 # clean up document_store.delete_all_documents(index="test_eval_document") document_store.delete_all_documents(index="test_feedback")
def test_eval_reader(reader, document_store: BaseDocumentStore): # add eval data (SQUAD format) document_store.add_eval_data( filename="samples/squad/tiny.json", doc_index="haystack_test_eval_document", label_index="haystack_test_feedback", ) assert document_store.get_document_count(index="haystack_test_eval_document") == 2 # eval reader reader_eval_results = reader.eval( document_store=document_store, label_index="haystack_test_feedback", doc_index="haystack_test_eval_document", device="cpu", ) assert reader_eval_results["f1"] > 66.65 assert reader_eval_results["f1"] < 66.67 assert reader_eval_results["EM"] == 50 assert reader_eval_results["top_n_accuracy"] == 100.0
def test_eval_pipeline(document_store: BaseDocumentStore, reader, retriever): # add eval data (SQUAD format) document_store.add_eval_data( filename="samples/squad/tiny.json", doc_index="haystack_test_eval_document", label_index="haystack_test_feedback", ) labels = document_store.get_all_labels_aggregated(index="haystack_test_feedback") eval_retriever = EvalDocuments() eval_reader = EvalAnswers(sas_model="sentence-transformers/paraphrase-MiniLM-L3-v2",debug=True) eval_reader_cross = EvalAnswers(sas_model="cross-encoder/stsb-TinyBERT-L-4",debug=True) eval_reader_vanila = EvalAnswers() assert document_store.get_document_count(index="haystack_test_eval_document") == 2 p = Pipeline() p.add_node(component=retriever, name="ESRetriever", inputs=["Query"]) p.add_node(component=eval_retriever, name="EvalDocuments", inputs=["ESRetriever"]) p.add_node(component=reader, name="QAReader", inputs=["EvalDocuments"]) p.add_node(component=eval_reader, name="EvalAnswers", inputs=["QAReader"]) p.add_node(component=eval_reader_cross, name="EvalAnswers_cross", inputs=["QAReader"]) p.add_node(component=eval_reader_vanila, name="EvalAnswers_vanilla", inputs=["QAReader"]) for l in labels: res = p.run( query=l.question, top_k_retriever=10, labels=l, top_k_reader=10, index="haystack_test_eval_document", ) assert eval_retriever.recall == 1.0 assert round(eval_reader.top_k_f1, 4) == 0.8333 assert eval_reader.top_k_em == 0.5 assert round(eval_reader.top_k_sas, 3) == 0.800 assert round(eval_reader_cross.top_k_sas, 3) == 0.671 assert eval_reader.top_k_em == eval_reader_vanila.top_k_em