mirror of
https://github.com/facebookresearch/faiss.git
synced 2026-10-11 22:50:00 +00:00
Tia Lim
0f0f728166
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
134 lines
4.9 KiB
Python
134 lines
4.9 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 numpy as np
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import unittest
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from typing import List
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from utils import load_config
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from tests.testing_utils import TestDataCreator
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import tempfile
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from dataset import create_dataset_from_oivf_config
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DIMENSION: int = 768
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SMALL_FILE_SIZES: List[int] = [100, 210, 450]
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LARGE_FILE_SIZES: List[int] = [1253, 3459, 890]
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TEST_BATCH_SIZE: int = 500
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SMALL_SAMPLE_SIZE: int = 1000
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NUM_FILES: int = 3
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class TestUtilsMethods(unittest.TestCase):
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"""
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Unit tests for iterate and decreasing_matrix methods.
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"""
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def test_iterate_input_file_smaller_than_batch(self):
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"""
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Tests when batch size is larger than the file size.
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"""
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with tempfile.TemporaryDirectory() as tmpdirname:
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data_creator = TestDataCreator(
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tempdir=tmpdirname,
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dimension=DIMENSION,
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data_type=np.float16,
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file_sizes=SMALL_FILE_SIZES,
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)
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data_creator.create_test_data()
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args = data_creator.setup_cli()
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cfg = load_config(args.config)
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db_iterator = create_dataset_from_oivf_config(cfg, args.xb).iterate(
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0, TEST_BATCH_SIZE, np.float32
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)
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for i in range(len(SMALL_FILE_SIZES) - 1):
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vecs = next(db_iterator)
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if i != 1:
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self.assertEqual(vecs.shape[0], TEST_BATCH_SIZE)
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else:
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self.assertEqual(
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vecs.shape[0], sum(SMALL_FILE_SIZES) - TEST_BATCH_SIZE
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)
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def test_iterate_input_file_larger_than_batch(self):
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"""
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Tests when batch size is smaller than the file size.
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"""
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with tempfile.TemporaryDirectory() as tmpdirname:
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data_creator = TestDataCreator(
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tempdir=tmpdirname,
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dimension=DIMENSION,
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data_type=np.float16,
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file_sizes=LARGE_FILE_SIZES,
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)
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data_creator.create_test_data()
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args = data_creator.setup_cli()
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cfg = load_config(args.config)
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db_iterator = create_dataset_from_oivf_config(cfg, args.xb).iterate(
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0, TEST_BATCH_SIZE, np.float32
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)
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for i in range(len(LARGE_FILE_SIZES) - 1):
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vecs = next(db_iterator)
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if i != 9:
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self.assertEqual(vecs.shape[0], TEST_BATCH_SIZE)
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else:
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self.assertEqual(
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vecs.shape[0],
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sum(LARGE_FILE_SIZES) - TEST_BATCH_SIZE * 9,
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)
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def test_get_vs_iterate(self) -> None:
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"""
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Loads vectors with iterator and get, and checks that they match, non-aligned by file size case.
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"""
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with tempfile.TemporaryDirectory() as tmpdirname:
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data_creator = TestDataCreator(
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tempdir=tmpdirname,
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dimension=DIMENSION,
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data_type=np.float16,
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file_size=SMALL_SAMPLE_SIZE,
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num_files=NUM_FILES,
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normalise=True,
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)
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data_creator.create_test_data()
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args = data_creator.setup_cli()
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cfg = load_config(args.config)
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ds = create_dataset_from_oivf_config(cfg, args.xb)
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vecs_by_iterator = np.vstack(list(ds.iterate(0, 317, np.float32)))
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self.assertEqual(
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vecs_by_iterator.shape[0], SMALL_SAMPLE_SIZE * NUM_FILES
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)
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vecs_by_get = ds.get(list(range(vecs_by_iterator.shape[0])))
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self.assertTrue(np.all(vecs_by_iterator == vecs_by_get))
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def test_iterate_back(self) -> None:
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"""
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Loads vectors with iterator and get, and checks that they match, non-aligned by file size case.
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"""
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with tempfile.TemporaryDirectory() as tmpdirname:
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data_creator = TestDataCreator(
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tempdir=tmpdirname,
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dimension=DIMENSION,
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data_type=np.float16,
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file_size=SMALL_SAMPLE_SIZE,
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num_files=NUM_FILES,
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normalise=True,
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)
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data_creator.create_test_data()
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args = data_creator.setup_cli()
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cfg = load_config(args.config)
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ds = create_dataset_from_oivf_config(cfg, args.xb)
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vecs_by_iterator = np.vstack(list(ds.iterate(0, 317, np.float32)))
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self.assertEqual(
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vecs_by_iterator.shape[0], SMALL_SAMPLE_SIZE * NUM_FILES
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)
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vecs_chunk = np.vstack(
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[
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next(ds.iterate(i, 543, np.float32))
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for i in range(0, SMALL_SAMPLE_SIZE * NUM_FILES, 543)
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]
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)
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self.assertTrue(np.all(vecs_by_iterator == vecs_chunk))
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