34 lines
1.0 KiB
Python
34 lines
1.0 KiB
Python
# Copyright (c) 2015-present, Facebook, Inc.
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# All rights reserved.
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#
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# This source code is licensed under the BSD+Patents license found in the
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# LICENSE file in the root directory of this source tree.
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import numpy as np
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d = 64 # dimension
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nb = 100000 # database size
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nq = 10000 # nb of queries
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np.random.seed(1234) # make reproducible
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xb = np.random.random((nb, d)).astype('float32')
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xb[:, 0] += np.arange(nb) / 1000.
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xq = np.random.random((nq, d)).astype('float32')
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xq[:, 0] += np.arange(nq) / 1000.
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import faiss
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nlist = 100
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m = 8
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k = 4
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quantizer = faiss.IndexFlatL2(d) # this remains the same
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index = faiss.IndexIVFPQ(quantizer, d, nlist, m, 8)
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# 8 specifies that each sub-vector is encoded as 8 bits
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index.train(xb)
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index.add(xb)
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D, I = index.search(xb[:5], k) # sanity check
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print(I)
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print(D)
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index.nprobe = 10 # make comparable with experiment above
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D, I = index.search(xq, k) # search
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print(I[-5:])
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