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Summary: Pull Request resolved: https://github.com/facebookresearch/faiss/pull/5349 # this is a no-op change Ran `black -l 80` over all tracked Python files under `fbcode/faiss/`, using line length 80 to match faiss's documented coding style (`CONTRIBUTING.md`: "80 character line length (both for C++ and Python)"). 172 files were reformatted; 28 were already compliant. This is a pure-formatting change. `black` runs its AST-equivalence safety check on every file, so no identifiers, string/numeric values, operators, or control flow were altered — only whitespace, indentation, line wrapping, blank lines, trailing commas, and string-quote normalization (single to double quotes). `fbcode/faiss/` is intentionally excluded from Meta's standard Python autoformatter (`arc f` / `arc lint -a` report no formatter for these paths) because it mirrors to public GitHub, so the Python had drifted out of any consistent style. The C++ is already clang-format-clean (0 of 807 files change), so this effort is Python-only. This diff brings the Python to canonical `black` formatting. Excluded `demos/index_pq_flat_separate_codes_from_codebook.py`: it contains a Jupyter `!rm` shell-magic line and is not valid Python, so `black` cannot parse it. This is the base of a 3-diff stack: (1) this black reformat; (2) `.flake8` alignment (max-line-length 80 + black-compatible ignores E203/W503); (3) genuine lint fixes (F401/F403/F841/B011). Reviewed By: mnorris11 Differential Revision: D109736099 fbshipit-source-id: 9a054635766ed11aa3760a788395babd3d198abf
201 lines
6.2 KiB
Python
201 lines
6.2 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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"""
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Wheel smoke tests for faiss-cpu pip package.
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These tests validate that a pip-installed wheel is correctly packaged:
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- Shared libraries load (SWIG, BLAS, OpenMP)
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- Core search functionality works
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- Key index types are registered
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- Serialization roundtrips
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- Python reference counting is safe
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- Contrib submodules are included
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They are intentionally minimal and fast (~15s total). The full test suite
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runs separately in the cmake-based CI.
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"""
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import platform
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import unittest
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import numpy as np
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import faiss
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class TestImportAndMetadata(unittest.TestCase):
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"""Catch: missing shared libs, broken SWIG, wrong Python ABI."""
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def test_version_attribute(self):
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assert hasattr(faiss, "__version__")
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parts = faiss.__version__.split(".")
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assert len(parts) == 3
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assert all(p.isdigit() for p in parts)
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def test_compile_options(self):
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opts = faiss.get_compile_options()
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assert isinstance(opts, str)
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class TestOpenMP(unittest.TestCase):
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"""Catch: OpenMP not linked."""
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def test_openmp_threads(self):
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n = faiss.omp_get_max_threads()
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assert n >= 1
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faiss.omp_set_num_threads(2)
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assert faiss.omp_get_max_threads() == 2
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# Restore
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faiss.omp_set_num_threads(n)
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class TestFlatSearch(unittest.TestCase):
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"""Catch: BLAS not linked, SIMD codepath issues."""
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def test_flat_l2(self):
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d, n = 64, 1000
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np.random.seed(42)
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xb = np.random.random((n, d)).astype("float32")
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index = faiss.IndexFlatL2(d)
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index.add(xb)
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D, I = index.search(xb[:5], 10)
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assert I.shape == (5, 10)
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# Nearest neighbor of each vector should be itself
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np.testing.assert_array_equal(I[:, 0], np.arange(5))
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# Self-distance should be ~0
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np.testing.assert_allclose(D[:, 0], 0, atol=1e-5)
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def test_flat_ip(self):
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d, n = 64, 1000
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np.random.seed(42)
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xb = np.random.random((n, d)).astype("float32")
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faiss.normalize_L2(xb)
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index = faiss.IndexFlatIP(d)
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index.add(xb)
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D, I = index.search(xb[:5], 10)
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assert I.shape == (5, 10)
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np.testing.assert_array_equal(I[:, 0], np.arange(5))
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np.testing.assert_allclose(D[:, 0], 1.0, atol=1e-5)
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class TestIndexFactory(unittest.TestCase):
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"""Catch: missing index implementations, broken factory string parsing."""
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def test_ivf_pq(self):
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d, n = 64, 10000
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np.random.seed(42)
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xb = np.random.random((n, d)).astype("float32")
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index = faiss.index_factory(d, "IVF32,PQ8")
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assert not index.is_trained
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index.train(xb)
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assert index.is_trained
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index.add(xb)
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assert index.ntotal == n
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D, I = index.search(xb[:5], 10)
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assert I.shape == (5, 10)
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def test_hnsw(self):
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d, n = 64, 2000
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np.random.seed(42)
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xb = np.random.random((n, d)).astype("float32")
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index = faiss.IndexHNSWFlat(d, 16)
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index.hnsw.efSearch = 64
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index.add(xb)
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assert index.ntotal == n
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D, I = index.search(xb[:5], 10)
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assert I.shape == (5, 10)
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# HNSW should find the vector itself as nearest neighbor
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np.testing.assert_array_equal(I[:, 0], np.arange(5))
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class TestSerialization(unittest.TestCase):
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"""Catch: broken I/O, buffer handling."""
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def test_serialize_deserialize_roundtrip(self):
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d = 32
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np.random.seed(42)
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xb = np.random.random((100, d)).astype("float32")
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index = faiss.IndexFlatL2(d)
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index.add(xb)
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# Serialize to bytes
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data = faiss.serialize_index(index)
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assert isinstance(data, np.ndarray)
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assert data.dtype == np.uint8
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# Deserialize
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index2 = faiss.deserialize_index(data)
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assert index2.ntotal == 100
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# Results should match
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D1, I1 = index.search(xb[:3], 5)
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D2, I2 = index2.search(xb[:3], 5)
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np.testing.assert_array_equal(I1, I2)
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np.testing.assert_allclose(D1, D2)
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class TestGCSafety(unittest.TestCase):
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"""Catch: Python reference counting bugs, crashes on GC."""
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def test_ivf_quantizer_lifecycle(self):
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d, n = 32, 5000
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np.random.seed(42)
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xb = np.random.random((n, d)).astype("float32")
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quantizer = faiss.IndexFlatL2(d)
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index = faiss.IndexIVFFlat(quantizer, d, 32)
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index.train(xb)
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index.add(xb)
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# Delete the quantizer reference — the index should still work
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# because faiss.__init__.py adds it to referenced_objects
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del quantizer
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D, I = index.search(xb[:3], 5)
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assert I.shape == (3, 5)
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class TestContribImports(unittest.TestCase):
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"""Catch: missing Python files in the wheel."""
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def test_contrib_modules(self):
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import faiss.contrib.datasets
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import faiss.contrib.evaluation
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import faiss.contrib.inspect_tools
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import faiss.contrib.ivf_tools
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import faiss.contrib.exhaustive_search
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import faiss.contrib.factory_tools
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import faiss.contrib.vecs_io # noqa: F401
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def test_contrib_torch_subpackage(self):
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try:
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import torch # noqa: F401
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except ImportError:
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raise unittest.SkipTest("torch not available")
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import faiss.contrib.torch
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import faiss.contrib.torch.clustering
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import faiss.contrib.torch.quantization # noqa: F401
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class TestSIMD(unittest.TestCase):
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"""Catch: Dynamic Dispatch not selecting a SIMD path (x86_64 only)."""
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@unittest.skipIf(
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platform.machine() not in ("x86_64", "AMD64"),
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"SIMD level check only meaningful on x86_64",
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)
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@unittest.skipIf(
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platform.system() == "Windows",
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"Windows wheels are built generic (no SIMD) — see pyproject.toml",
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)
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def test_dd_selects_simd_path(self):
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opts = faiss.get_compile_options()
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if "DD" not in opts:
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raise unittest.SkipTest("Not a Dynamic Dispatch build")
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# DD builds should select at least AVX2 on modern x86_64
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assert (
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"AVX2" in opts or "AVX512" in opts
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), f"DD build did not select a SIMD path: {opts}"
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