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-rw-r--r--math/py-faiss/files/test.py16
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diff --git a/math/py-faiss/files/test.py b/math/py-faiss/files/test.py
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+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)