math/py-faiss: New port: Library for efficient similarity search & clustering of dense vectors

1 files changed, 16 insertions, 0 deletions

diff --git a/math/py-faiss/files/test.py b/math/py-faiss/files/test.py
new file mode 100644
index 000000000000..f1395cf46a3e
--- /dev/null
+++ b/math/py-faiss/files/test.py
@@ -0,0 +1,16 @@
+import numpy as np
+d = 64                           # dimension
+nb = 100000                      # database size
+nq = 10000                       # nb of queries
+np.random.seed(1234)             # make reproducible
+xb = np.random.random((nb, d)).astype('float32')
+xb[:, 0] += np.arange(nb) / 1000.
+xq = np.random.random((nq, d)).astype('float32')
+xq[:, 0] += np.arange(nq) / 1000.
+
+
+import faiss                   # make faiss available
+index = faiss.IndexFlatL2(d)   # build the index
+print(index.is_trained)
+index.add(xb)                  # add vectors to the index
+print(index.ntotal)