def test_eval_finder(document_store: BaseDocumentStore, reader):
retriever = ElasticsearchRetriever(document_store=document_store)
finder = Finder(reader=reader, retriever=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 finder
results = finder.eval(label_index="test_feedback", doc_index="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="test_feedback", doc_index="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"]
# clean up
document_store.delete_all_documents(index="test_eval_document")
document_store.delete_all_documents(index="test_feedback")
def test_eval_elastic_retriever(document_store: BaseDocumentStore, open_domain):
retriever = ElasticsearchRetriever(document_store=document_store)
# 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")