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16 lines
588 B
Python
16 lines
588 B
Python
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 # make faiss available
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index = faiss.IndexFlatL2(d) # build the index
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print(index.is_trained)
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index.add(xb) # add vectors to the index
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print(index.ntotal)
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