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eff0898a13
Summary: Pull Request resolved: https://github.com/facebookresearch/faiss/pull/3966 This actually enables the linting. Manual changes: - tools/arcanist/lint/fbsource-licenselint-config.toml - tools/arcanist/lint/fbsource-lint-engine.toml Automated changes: `arc lint --apply-patches --take LICENSELINT --paths-cmd 'hg files faiss'` Reviewed By: asadoughi Differential Revision: D64484165 fbshipit-source-id: 4f2f6e953c94ef6ebfea8a5ae035ccfbea65ed04
43 lines
1.5 KiB
Python
43 lines
1.5 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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#
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# This source code is licensed under the MIT license found in the
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# LICENSE file in the root directory of this source tree.
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import faiss
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from faiss.contrib.evaluation import knn_intersection_measure
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from faiss.contrib import datasets
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# 64-dim vectors, 50000 vectors in the training, 100000 in database,
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# 10000 in queries, dtype ('float32')
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ds = datasets.SyntheticDataset(64, 50000, 100000, 10000)
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d = 64 # dimension
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# Constructing the refine PQ index with SQfp16 with index factory
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index_fp16 = faiss.index_factory(d, 'PQ32x4fs,Refine(SQfp16)')
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index_fp16.train(ds.get_train())
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index_fp16.add(ds.get_database())
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# Constructing the refine PQ index with SQ8
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index_sq8 = faiss.index_factory(d, 'PQ32x4fs,Refine(SQ8)')
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index_sq8.train(ds.get_train())
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index_sq8.add(ds.get_database())
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# Parameterization on k factor while doing search for index refinement
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k_factor = 3.0
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params = faiss.IndexRefineSearchParameters(k_factor=k_factor)
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# Perform index search using different index refinement
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D_fp16, I_fp16 = index_fp16.search(ds.get_queries(), 100, params=params)
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D_sq8, I_sq8 = index_sq8.search(ds.get_queries(), 100, params=params)
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# Calculating knn intersection measure for different index types on refinement
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KIM_fp16 = knn_intersection_measure(I_fp16, ds.get_groundtruth())
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KIM_sq8 = knn_intersection_measure(I_sq8, ds.get_groundtruth())
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# KNN intersection measure accuracy shows that choosing SQ8 impacts accuracy
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assert (KIM_fp16 > KIM_sq8)
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print(I_sq8[:5])
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print(I_fp16[:5])
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