def rank(self, docs_matrix: List['DocumentArray'], parameters: Dict,
**kwargs) -> 'DocumentArray':
"""
:param docs: the doc which gets bubbled up matches
:param kwargs: not used (kept to maintain interface)
"""
result_da = DocumentArray(
) # length: 1 as every time there is only one query
for d_mod1, d_mod2 in zip(*docs_matrix):
final_matches = {} # type: Dict[str, Document]
for m in d_mod1.matches:
m.score.value *= d_mod1.weight
final_matches[m.parent_id] = Document(m, copy=True)
for m in d_mod2.matches:
if m.parent_id in final_matches:
final_matches[m.parent_id].score.value += (m.score.value *
d_mod2.weight)
else:
m.score.value *= d_mod2.weight
final_matches[m.parent_id] = Document(m, copy=True)
da = DocumentArray(list(final_matches.values()))
da.sort(key=lambda ma: ma.score.value, reverse=True)
d = Document(matches=da[:int(parameters['top_k'])])
result_da.append(d)
return result_da
def test_da_sort_by_document_interface_in_proto():
docs = [Document(embedding=np.array([1] * (10 - i))) for i in range(10)]
da = DocumentArray(
[docs[i] if (i % 2 == 0) else docs[i].proto for i in range(len(docs))])
assert len(da) == 10
assert da[0].embedding.shape == (10, )
da.sort(key=lambda d: d.embedding.dense.shape[0])
assert da[0].embedding.shape == (1, )
def test_da_sort_by_score():
da = DocumentArray(
[Document(id=i, copy=True, scores={'euclid': 10 - i}) for i in range(10)]
)
assert da[0].id == '0'
assert da[0].scores['euclid'].value == 10
da.sort(key=lambda d: d.scores['euclid'].value) # sort matches by their values
assert da[0].id == '9'
assert da[0].scores['euclid'].value == 1
def test_da_sort_topk_tie():
da = DocumentArray(
[Document(id=i, tags={'order': i % 10}) for i in range(100)])
da.sort(top_k=10, key=lambda doc: doc.tags['order'])
top_k_ids = [doc.id for doc in da[0:10]]
assert top_k_ids == [
'0', '10', '20', '30', '40', '50', '60', '70', '80', '90'
]
for i in range(10):
assert da[i].tags['order'] == 0
def rank(self, docs_matrix: List[DocumentArray], parameters: Dict, **kwargs):
result = DocumentArray()
docs_matrix = [doc_arr for doc_arr in docs_matrix if doc_arr is not None and len(doc_arr) > 0]
for single_doc_per_modality in zip(*docs_matrix):
final_matches = {}
for doc in single_doc_per_modality:
for m in doc.matches:
if m.tags['root_doc_id'] in final_matches:
final_matches[m.tags['root_doc_id']].score.value += m.score.value
else:
final_matches[m.tags['root_doc_id']] = Document(id=m.tags['root_doc_id'], score=m.score)
da = DocumentArray(list(final_matches.values()))
da.sort(key=lambda ma: ma.score.value, reverse=True)
d = Document(matches=da[: int(parameters.get('top_k', 3))])
result.append(d)
return result
def test_da_sort_topk():
da = DocumentArray(
[Document(id=i, scores={'euclid': 10 - i}) for i in range(10)])
original = deepcopy(da)
da.sort(top_k=3, key=lambda d: d.scores['euclid'].value)
top = [da[i].scores['euclid'].value for i in range(3)]
rest = [da[i].scores['euclid'].value for i in range(3, 10)]
assert top[0] == 1 and top[1] == 2 and top[2] == 3
assert rest != sorted(rest)
assert len(da) == len(original)
assert all([d.id in original for d in da])
da.sort(top_k=3, key=lambda d: d.scores['euclid'].value, reverse=True)
top = [da[i].scores['euclid'].value for i in range(3)]
rest = [da[i].scores['euclid'].value for i in range(3, 10)]
assert top[0] == 10 and top[1] == 9 and top[2] == 8
assert rest != sorted(rest, reverse=True)
assert len(da) == len(original)
assert all([d.id in original for d in da])
def rank(self, docs_matrix: List['DocumentArray'], parameters: Dict,
**kwargs) -> 'DocumentArray':
"""
:param docs_matrix: list of :class:`DocumentArray` on multiple requests to
get bubbled up matches.
:param parameters: the parameters passed into the ranker, in this case stores :attr`top_k`
to filter k results based on score.
:param kwargs: not used (kept to maintain interface)
"""
result_da = DocumentArray(
) # length: 1 as every time there is only one query
for d_mod1, d_mod2 in zip(*docs_matrix):
final_matches = {} # type: Dict[str, Document]
for m in d_mod1.matches:
m.scores[
'relevance'] = m.scores['cosine'].value * d_mod1.weight
final_matches[m.parent_id] = Document(m, copy=True)
for m in d_mod2.matches:
if m.parent_id in final_matches:
final_matches[
m.parent_id].scores['relevance'] = final_matches[
m.parent_id].scores['relevance'].value + (
m.scores['cosine'].value * d_mod2.weight)
else:
m.scores[
'relevance'] = m.scores['cosine'].value * d_mod2.weight
final_matches[m.parent_id] = Document(m, copy=True)
da = DocumentArray(list(final_matches.values()))
da.sort(key=lambda ma: ma.scores['relevance'].value, reverse=True)
d = Document(matches=da[:int(parameters['top_k'])])
result_da.append(d)
return result_da
