def test_texts_getter_dam(tmpdir):
dam = DocumentArrayMemmap(tmpdir)
dam.extend([Document(text='hello') for _ in range(100)])
assert len(dam.texts) == 100
t1 = dam.texts
t2 = dam.get_attributes('text')
assert t1 == t2
def test_extend_and_get_attribute(tmpdir, embed_dim):
dam = DocumentArrayMemmap(tmpdir)
dam.clear()
docs = list(random_docs(100, start_id=0, embed_dim=embed_dim))
dam.extend(docs)
dam2 = DocumentArrayMemmap(tmpdir)
x = dam2.get_attributes('embedding')
assert len(dam2) == 100
docs = list(random_docs(100, start_id=100, embed_dim=embed_dim))
dam2.extend(docs)
x = dam2.get_attributes('embedding')
assert len(x) == 200
assert x[0].shape == (embed_dim, )
assert len(dam2) == 200
def test_blobs_getter_dam(tmpdir):
blobs = np.random.random((100, 10, 10))
dam = DocumentArrayMemmap(tmpdir)
dam.extend([Document(blob=blob) for blob in blobs])
assert len(dam) == 100
np.testing.assert_almost_equal(dam.get_attributes('blob'), dam.blobs)
def test_dam_embeddings(tmpdir):
dam = DocumentArrayMemmap(tmpdir)
dam.extend(Document(embedding=np.array([1, 2, 3, 4])) for _ in range(100))
np.testing.assert_almost_equal(dam.get_attributes('embedding'),
dam.embeddings)
def test_dam_get_embeddings_slice(tmpdir):
da = DocumentArrayMemmap(tmpdir)
da.extend(Document(embedding=np.array([1, 2, 3, 4])) for _ in range(100))
np.testing.assert_almost_equal(
da.get_attributes('embedding')[10:20],
da._get_embeddings(slice(10, 20)))
def test_tags_getter_dam(tmpdir):
dam = DocumentArrayMemmap(tmpdir)
dam.extend([Document(tags={'a': 2, 'c': 'd'}) for _ in range(100)])
assert len(dam.tags) == 100
assert dam.tags == dam.get_attributes('tags')
