def test_internals_api(n_components):
callback = CustomCallback()
reducer = UMAP(n_components=n_components, callback=callback)
reducer.fit(data)
callback.check()
# Make sure super().__init__ is called
callback = CustomCallback(skip_init=True)
model = UMAP(n_epochs=10, callback=callback)
with pytest.raises(ValueError):
model.fit_transform(data)
def reduce_dimensionality(self, embeddings):
"""Reduce dimensionality of embeddings using UMAP and train a UMAP model
Args:
embeddings (cupy.ndarray): The extracted embeddings using the
sentence transformer module.
Returns:
umap_embeddings: The reduced embeddings
"""
m_cos = NearestNeighbors(n_neighbors=15, metric="cosine")
m_cos.fit(embeddings)
knn_graph_cos = m_cos.kneighbors_graph(embeddings, mode="distance")
u1 = UMAP(n_neighbors=15, n_components=5, min_dist=0.0)
umap_embeddings = u1.fit_transform(embeddings, knn_graph=knn_graph_cos)
return umap_embeddings