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Back out "Better NaN handling" (#3006)

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Summary:
Pull Request resolved: https://github.com/facebookresearch/faiss/pull/3006

Original commit changeset: 99e7786582e9

Original Phabricator Diff: D48031390

Reviewed By: algoriddle

Differential Revision: D48353221

fbshipit-source-id: fd326f2a45d20f68507ca39a33a325528651b37d
This commit is contained in:
Maria Lomeli
2023-08-15 09:32:01 -07:00
committed by Facebook GitHub Bot
parent e3deb71cdb
commit c09992bc8a
5 changed files with 108 additions and 215 deletions
Download Patch File Download Diff File Expand all files Collapse all files
faiss/impl/HNSW.cpp
+11 -14
View File
@@ -9,7 +9,6 @@
#include <faiss/impl/HNSW.h>
#include <cmath>
#include <string>
#include <faiss/impl/AuxIndexStructures.h>
@@ -543,11 +542,12 @@ int search_from_candidates(
for (int i = 0; i < candidates.size(); i++) {
idx_t v1 = candidates.ids[i];
float d = candidates.dis[i];
assert(v1 >= 0);
FAISS_ASSERT(v1 >= 0);
if (!sel || sel->is_member(v1)) {
if (d < D[0]) {
faiss::maxheap_replace_top(k, D, I, d, v1);
nres++;
if (nres < k) {
faiss::maxheap_push(++nres, D, I, d, v1);
} else if (d < D[0]) {
faiss::maxheap_replace_top(nres, D, I, d, v1);
}
}
vt.set(v1);
@@ -612,9 +612,10 @@ int search_from_candidates(
auto add_to_heap = [&](const size_t idx, const float dis) {
if (!sel || sel->is_member(idx)) {
if (dis < D[0]) {
faiss::maxheap_replace_top(k, D, I, dis, idx);
nres++;
if (nres < k) {
faiss::maxheap_push(++nres, D, I, dis, idx);
} else if (dis < D[0]) {
faiss::maxheap_replace_top(nres, D, I, dis, idx);
}
}
candidates.push(idx, dis);
@@ -667,7 +668,7 @@ int search_from_candidates(
stats.n3 += ndis;
}
return std::min(nres, k);
return nres;
}
std::priority_queue<HNSW::Node> search_from_candidate_unbounded(
@@ -815,11 +816,6 @@ HNSWStats HNSW::search(
// greedy search on upper levels
storage_idx_t nearest = entry_point;
float d_nearest = qdis(nearest);
if (!std::isfinite(d_nearest)) {
// means either the query or the entry point are NaN: in
// both cases we can only return -1 as a result
return stats;
}
for (int level = max_level; level >= 1; level--) {
greedy_update_nearest(*this, qdis, level, nearest, d_nearest);
@@ -830,6 +826,7 @@ HNSWStats HNSW::search(
MinimaxHeap candidates(ef);
candidates.push(nearest, d_nearest);
search_from_candidates(
*this, qdis, k, I, D, candidates, vt, stats, 0, 0, params);
} else {
faiss/impl/ResultHandler.h
+3 -4
View File
@@ -445,8 +445,8 @@ struct SingleBestResultHandler {
/// begin results for query # i
void begin(const size_t current_idx) {
this->current_idx = current_idx;
min_dis = C::neutral();
min_idx = -1;
min_dis = HUGE_VALF;
min_idx = 0;
}
/// add one result for query i
@@ -472,8 +472,7 @@ struct SingleBestResultHandler {
this->i1 = i1;
for (size_t i = i0; i < i1; i++) {
this->dis_tab[i] = C::neutral();
this->ids_tab[i] = -1;
this->dis_tab[i] = HUGE_VALF;
}
}
faiss/impl/ScalarQuantizer.cpp
-5
View File
@@ -1075,11 +1075,6 @@ void ScalarQuantizer::set_derived_sizes() {
}
void ScalarQuantizer::train(size_t n, const float* x) {
for (size_t i = 0; i < n * d; i++) {
FAISS_THROW_IF_NOT_MSG(
std::isfinite(x[i]), "training data contains NaN or Inf");
}
int bit_per_dim = qtype == QT_4bit_uniform ? 4
: qtype == QT_4bit ? 4
: qtype == QT_6bit ? 6
tests/test_error_reporting.py
-182
View File
@@ -1,182 +0,0 @@
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""This script tests a few failure cases of Faiss and whether they are handled
properly."""
import numpy as np
import unittest
import faiss
from common_faiss_tests import get_dataset_2
from faiss.contrib.datasets import SyntheticDataset
class TestValidIndexParams(unittest.TestCase):
def test_IndexIVFPQ(self):
d = 32
nb = 1000
nt = 1500
nq = 200
(xt, xb, xq) = get_dataset_2(d, nt, nb, nq)
coarse_quantizer = faiss.IndexFlatL2(d)
index = faiss.IndexIVFPQ(coarse_quantizer, d, 32, 8, 8)
index.cp.min_points_per_centroid = 5 # quiet warning
index.train(xt)
index.add(xb)
# invalid nprobe
index.nprobe = 0
k = 10
self.assertRaises(RuntimeError, index.search, xq, k)
# invalid k
index.nprobe = 4
k = -10
self.assertRaises(AssertionError, index.search, xq, k)
# valid params
index.nprobe = 4
k = 10
D, nns = index.search(xq, k)
self.assertEqual(D.shape[0], nq)
self.assertEqual(D.shape[1], k)
def test_IndexFlat(self):
d = 32
nb = 1000
nt = 0
nq = 200
(xt, xb, xq) = get_dataset_2(d, nt, nb, nq)
index = faiss.IndexFlat(d, faiss.METRIC_L2)
index.add(xb)
# invalid k
k = -5
self.assertRaises(AssertionError, index.search, xq, k)
# valid k
k = 5
D, I = index.search(xq, k)
self.assertEqual(D.shape[0], nq)
self.assertEqual(D.shape[1], k)
class TestReconsException(unittest.TestCase):
def test_recons_exception(self):
d = 64 # dimension
nb = 1000
rs = np.random.RandomState(1234)
xb = rs.rand(nb, d).astype('float32')
nlist = 10
quantizer = faiss.IndexFlatL2(d) # the other index
index = faiss.IndexIVFFlat(quantizer, d, nlist)
index.train(xb)
index.add(xb)
index.make_direct_map()
index.reconstruct(9)
self.assertRaises(
RuntimeError,
index.reconstruct, 100001
)
def test_reconstuct_after_add(self):
index = faiss.index_factory(10, 'IVF5,SQfp16')
index.train(faiss.randn((100, 10), 123))
index.add(faiss.randn((100, 10), 345))
index.make_direct_map()
index.add(faiss.randn((100, 10), 678))
# should not raise an exception
index.reconstruct(5)
print(index.ntotal)
index.reconstruct(150)
class TestNaN(unittest.TestCase):
""" NaN values handling is transparent: they don't produce results
but should not crash. The tests below cover a few common index types.
"""
def do_test_train(self, factory_string):
""" NaN and Inf should raise an exception at train time """
ds = SyntheticDataset(32, 200, 20, 10)
index = faiss.index_factory(ds.d, factory_string)
# try to train with NaNs
xt = ds.get_train().copy()
xt[:, ::4] = np.nan
self.assertRaises(RuntimeError, index.train, xt)
def test_train_IVFSQ(self):
self.do_test_train("IVF10,SQ8")
def test_train_IVFPQ(self):
self.do_test_train("IVF10,PQ4np")
def test_train_SQ(self):
self.do_test_train("SQ8")
def do_test_add(self, factory_string):
""" stored NaNs should not be returned at search time """
ds = SyntheticDataset(32, 200, 20, 10)
index = faiss.index_factory(ds.d, factory_string)
if not index.is_trained:
index.train(ds.get_train())
xb = ds.get_database()
xb[12, 3] = np.nan
index.add(xb)
D, I = index.search(ds.get_queries(), 20)
self.assertTrue(np.where(I == 12)[0].size == 0)
def test_add_Flat(self):
self.do_test_add("Flat")
def test_add_HNSW(self):
self.do_test_add("HNSW32,Flat")
def xx_test_add_SQ8(self):
# this is expected to fail because:
# in ASAN mode, the float NaN -> int conversion crashes
# in opt mode it works but there is no way to encode the NaN,
# so the value cannot be ignored.
self.do_test_add("SQ8")
def test_add_IVFFlat(self):
self.do_test_add("IVF10,Flat")
def do_test_search(self, factory_string):
""" NaN query vectors should return -1 """
ds = SyntheticDataset(32, 200, 20, 10)
index = faiss.index_factory(ds.d, factory_string)
if not index.is_trained:
index.train(ds.get_train())
index.add(ds.get_database())
xq = ds.get_queries()
xq[7, 3] = np.nan
D, I = index.search(ds.get_queries(), 20)
self.assertTrue(np.all(I[7] == -1))
def test_search_Flat(self):
self.do_test_search("Flat")
def test_search_HNSW(self):
self.do_test_search("HNSW32,Flat")
def test_search_IVFFlat(self):
self.do_test_search("IVF10,Flat")
def test_search_SQ(self):
self.do_test_search("SQ8")
tests/test_index.py
+94 -10
View File
@@ -4,6 +4,8 @@
# LICENSE file in the root directory of this source tree.
"""this is a basic test script for simple indices work"""
from __future__ import absolute_import, division, print_function
# no unicode_literals because it messes up in py2
import numpy as np
import unittest
@@ -11,17 +13,16 @@ import faiss
import tempfile
import os
import re
import warnings
from common_faiss_tests import get_dataset, get_dataset_2
class TestModuleInterface(unittest.TestCase):
def test_version_attribute(self):
assert hasattr(faiss, '__version__')
assert re.match('^\\d+\\.\\d+\\.\\d+$', faiss.__version__)
class TestIndexFlat(unittest.TestCase):
def do_test(self, nq, metric_type=faiss.METRIC_L2, k=10):
@@ -108,14 +109,6 @@ class TestIndexFlat(unittest.TestCase):
def test_with_blas_reservoir_ip(self):
self.do_test(200, faiss.METRIC_INNER_PRODUCT, k=150)
def test_noblas_1res(self):
self.do_test(10, k=1)
def test_with_blas_1res(self):
self.do_test(200, k=1)
def test_with_blas_1res_ip(self):
self.do_test(200, faiss.METRIC_INNER_PRODUCT, k=1)
class TestIndexFlatL2(unittest.TestCase):
def test_indexflat_l2_sync_norms_1(self):
@@ -1014,6 +1007,41 @@ class TestShardReplicas(unittest.TestCase):
index.remove_replica(index1)
self.assertEqual(index.ntotal, 0)
class TestReconsException(unittest.TestCase):
def test_recons_exception(self):
d = 64 # dimension
nb = 1000
rs = np.random.RandomState(1234)
xb = rs.rand(nb, d).astype('float32')
nlist = 10
quantizer = faiss.IndexFlatL2(d) # the other index
index = faiss.IndexIVFFlat(quantizer, d, nlist)
index.train(xb)
index.add(xb)
index.make_direct_map()
index.reconstruct(9)
self.assertRaises(
RuntimeError,
index.reconstruct, 100001
)
def test_reconstuct_after_add(self):
index = faiss.index_factory(10, 'IVF5,SQfp16')
index.train(faiss.randn((100, 10), 123))
index.add(faiss.randn((100, 10), 345))
index.make_direct_map()
index.add(faiss.randn((100, 10), 678))
# should not raise an exception
index.reconstruct(5)
print(index.ntotal)
index.reconstruct(150)
class TestReconsHash(unittest.TestCase):
def do_test(self, index_key):
@@ -1085,6 +1113,62 @@ class TestReconsHash(unittest.TestCase):
self.do_test("IVF5,PQ4x4np")
class TestValidIndexParams(unittest.TestCase):
def test_IndexIVFPQ(self):
d = 32
nb = 1000
nt = 1500
nq = 200
(xt, xb, xq) = get_dataset_2(d, nt, nb, nq)
coarse_quantizer = faiss.IndexFlatL2(d)
index = faiss.IndexIVFPQ(coarse_quantizer, d, 32, 8, 8)
index.cp.min_points_per_centroid = 5 # quiet warning
index.train(xt)
index.add(xb)
# invalid nprobe
index.nprobe = 0
k = 10
self.assertRaises(RuntimeError, index.search, xq, k)
# invalid k
index.nprobe = 4
k = -10
self.assertRaises(AssertionError, index.search, xq, k)
# valid params
index.nprobe = 4
k = 10
D, nns = index.search(xq, k)
self.assertEqual(D.shape[0], nq)
self.assertEqual(D.shape[1], k)
def test_IndexFlat(self):
d = 32
nb = 1000
nt = 0
nq = 200
(xt, xb, xq) = get_dataset_2(d, nt, nb, nq)
index = faiss.IndexFlat(d, faiss.METRIC_L2)
index.add(xb)
# invalid k
k = -5
self.assertRaises(AssertionError, index.search, xq, k)
# valid k
k = 5
D, I = index.search(xq, k)
self.assertEqual(D.shape[0], nq)
self.assertEqual(D.shape[1], k)
class TestLargeRangeSearch(unittest.TestCase):