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various fixes to support nmslib
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Ubuntu committed Jun 20, 2015
1 parent eddaee5 commit e58e4af
Showing 1 changed file with 64 additions and 51 deletions.
115 changes: 64 additions & 51 deletions ann_benchmarks/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -184,16 +184,24 @@ def __init__(self, metric, method_name, method_param):

def fit(self, X):
import nmslib
if self._method_name == 'vptree':
# To avoid this issue:
# terminate called after throwing an instance of 'std::runtime_error'
# what(): The data size is too small or the bucket size is too big. Select the parameters so that <total # of records> is NOT less than <bucket size> * 1000
# Aborted (core dumped)
self._method_param.append('bucketSize=%d' % min(int(X.shape[0] * 0.0005), 1000))
self._index = nmslib.initIndex(X.shape[0], self._nmslib_metric, [], self._method_name, self._method_param, nmslib.DataType.VECTOR, nmslib.DistType.FLOAT)

for i, x in enumerate(X):
nmslib.setData(self._index, i, x.tolist())
nmslib.buildIndex(self._index)

def query(self, v, n):
import nmslib
return nmslib.knnQuery(self._index, n, v.tolist())

def freeIndex(self):
import nmslib
nmslib.freeIndex(self._index)


Expand Down Expand Up @@ -280,7 +288,7 @@ def get_queries(args):
return queries

def get_algos(m):
return {
algos = {
'lshf': [LSHF(m, 5, 10), LSHF(m, 5, 20), LSHF(m, 10, 20), LSHF(m, 10, 50), LSHF(m, 20, 100)],
'flann': [FLANN(m, 0.2), FLANN(m, 0.5), FLANN(m, 0.7), FLANN(m, 0.8), FLANN(m, 0.9), FLANN(m, 0.95), FLANN(m, 0.97), FLANN(m, 0.98), FLANN(m, 0.99), FLANN(m, 0.995)],
'panns': [PANNS(m, 5, 20), PANNS(m, 10, 10), PANNS(m, 10, 50), PANNS(m, 10, 100), PANNS(m, 20, 100), PANNS(m, 40, 100)],
Expand All @@ -294,58 +302,63 @@ def get_algos(m):
'ball': [BallTree(m, 10), BallTree(m, 20), BallTree(m, 40), BallTree(m, 100), BallTree(m, 200), BallTree(m, 400), BallTree(m, 1000)],
'kd': [KDTree(m, 10), KDTree(m, 20), KDTree(m, 40), KDTree(m, 100), KDTree(m, 200), KDTree(m, 400), KDTree(m, 1000)],

# START: Non-Metric Space Library (nmslib) entries
'MP-lsh(lshkit)':[
Nmslib(m, 'lsh_multiprobe', ['desiredRecall=0.99','H=1200001','T=10','L=50','tuneK=10']),
Nmslib(m, 'lsh_multiprobe', ['desiredRecall=0.97','H=1200001','T=10','L=50','tuneK=10']),
Nmslib(m, 'lsh_multiprobe', ['desiredRecall=0.95','H=1200001','T=10','L=50','tuneK=10']),
Nmslib(m, 'lsh_multiprobe', ['desiredRecall=0.90','H=1200001','T=10','L=50','tuneK=10']),
Nmslib(m, 'lsh_multiprobe', ['desiredRecall=0.85','H=1200001','T=10','L=50','tuneK=10']),
Nmslib(m, 'lsh_multiprobe', ['desiredRecall=0.80','H=1200001','T=10','L=50','tuneK=10']),
Nmslib(m, 'lsh_multiprobe', ['desiredRecall=0.7','H=1200001','T=10','L=50','tuneK=10']),
Nmslib(m, 'lsh_multiprobe', ['desiredRecall=0.6','H=1200001','T=10','L=50','tuneK=10']),
Nmslib(m, 'lsh_multiprobe', ['desiredRecall=0.5','H=1200001','T=10','L=50','tuneK=10']),
Nmslib(m, 'lsh_multiprobe', ['desiredRecall=0.4','H=1200001','T=10','L=50','tuneK=10']),
Nmslib(m, 'lsh_multiprobe', ['desiredRecall=0.3','H=1200001','T=10','L=50','tuneK=10']),
Nmslib(m, 'lsh_multiprobe', ['desiredRecall=0.2','H=1200001','T=10','L=50','tuneK=10']),
Nmslib(m, 'lsh_multiprobe', ['desiredRecall=0.1','H=1200001','T=10','L=50','tuneK=10']),
],

'bruteforce0(nmslib)': [Nmslib(m, 'seq_search', ['copyMem=0'])],
'bruteforce1(nmslib)': [Nmslib(m, 'seq_search', ['copyMem=1'])],

'BallTree(nmslib)': [
Nmslib(m, 'vptree', ['tuneK=10', 'desiredRecall=0.99', 'bucketSize=100']),
Nmslib(m, 'vptree', ['tuneK=10', 'desiredRecall=0.95', 'bucketSize=100']),
Nmslib(m, 'vptree', ['tuneK=10', 'desiredRecall=0.90', 'bucketSize=100']),
Nmslib(m, 'vptree', ['tuneK=10', 'desiredRecall=0.85', 'bucketSize=100']),
Nmslib(m, 'vptree', ['tuneK=10', 'desiredRecall=0.8', 'bucketSize=100']),
Nmslib(m, 'vptree', ['tuneK=10', 'desiredRecall=0.7', 'bucketSize=100']),
Nmslib(m, 'vptree', ['tuneK=10', 'desiredRecall=0.6', 'bucketSize=100']),
Nmslib(m, 'vptree', ['tuneK=10', 'desiredRecall=0.5', 'bucketSize=100']),
Nmslib(m, 'vptree', ['tuneK=10', 'desiredRecall=0.4', 'bucketSize=100']),
Nmslib(m, 'vptree', ['tuneK=10', 'desiredRecall=0.3', 'bucketSize=100']),
Nmslib(m, 'vptree', ['tuneK=10', 'desiredRecall=0.2', 'bucketSize=100']),
Nmslib(m, 'vptree', ['tuneK=10', 'desiredRecall=0.1', 'bucketSize=100']),
],

'SW-graph(nmslib)':[
Nmslib(m, 'small_world_rand', ['NN=20', 'initIndexAttempts=4', 'initSearchAttempts=48']),
Nmslib(m, 'small_world_rand', ['NN=20', 'initIndexAttempts=4', 'initSearchAttempts=32']),
Nmslib(m, 'small_world_rand', ['NN=20', 'initIndexAttempts=4', 'initSearchAttempts=16']),
Nmslib(m, 'small_world_rand', ['NN=20', 'initIndexAttempts=4', 'initSearchAttempts=8']),
Nmslib(m, 'small_world_rand', ['NN=20', 'initIndexAttempts=4', 'initSearchAttempts=4']),
Nmslib(m, 'small_world_rand', ['NN=20', 'initIndexAttempts=4', 'initSearchAttempts=2']),
Nmslib(m, 'small_world_rand', ['NN=17', 'initIndexAttempts=4', 'initSearchAttempts=2']),
Nmslib(m, 'small_world_rand', ['NN=14', 'initIndexAttempts=4', 'initSearchAttempts=2']),
Nmslib(m, 'small_world_rand', ['NN=11', 'initIndexAttempts=5', 'initSearchAttempts=2']),
Nmslib(m, 'small_world_rand', ['NN=8', 'initIndexAttempts=5', 'initSearchAttempts=2']),
Nmslib(m, 'small_world_rand', ['NN=5', 'initIndexAttempts=5', 'initSearchAttempts=2']),
Nmslib(m, 'small_world_rand', ['NN=3', 'initIndexAttempts=5', 'initSearchAttempts=2']),
]
# END: Non-Metric Space Library (nmslib) entries
# START: Non-Metric Space Library (nmslib) entries
'bruteforce0(nmslib)': [Nmslib(m, 'seq_search', ['copyMem=0'])],
'bruteforce1(nmslib)': [Nmslib(m, 'seq_search', ['copyMem=1'])],

'BallTree(nmslib)': [
Nmslib(m, 'vptree', ['tuneK=10', 'desiredRecall=0.99']),
Nmslib(m, 'vptree', ['tuneK=10', 'desiredRecall=0.95']),
Nmslib(m, 'vptree', ['tuneK=10', 'desiredRecall=0.90']),
Nmslib(m, 'vptree', ['tuneK=10', 'desiredRecall=0.85']),
Nmslib(m, 'vptree', ['tuneK=10', 'desiredRecall=0.8']),
Nmslib(m, 'vptree', ['tuneK=10', 'desiredRecall=0.7']),
Nmslib(m, 'vptree', ['tuneK=10', 'desiredRecall=0.6']),
Nmslib(m, 'vptree', ['tuneK=10', 'desiredRecall=0.5']),
Nmslib(m, 'vptree', ['tuneK=10', 'desiredRecall=0.4']),
Nmslib(m, 'vptree', ['tuneK=10', 'desiredRecall=0.3']),
Nmslib(m, 'vptree', ['tuneK=10', 'desiredRecall=0.2']),
Nmslib(m, 'vptree', ['tuneK=10', 'desiredRecall=0.1']),
],

'SW-graph(nmslib)':[
Nmslib(m, 'small_world_rand', ['NN=20', 'initIndexAttempts=4', 'initSearchAttempts=48']),
Nmslib(m, 'small_world_rand', ['NN=20', 'initIndexAttempts=4', 'initSearchAttempts=32']),
Nmslib(m, 'small_world_rand', ['NN=20', 'initIndexAttempts=4', 'initSearchAttempts=16']),
Nmslib(m, 'small_world_rand', ['NN=20', 'initIndexAttempts=4', 'initSearchAttempts=8']),
Nmslib(m, 'small_world_rand', ['NN=20', 'initIndexAttempts=4', 'initSearchAttempts=4']),
Nmslib(m, 'small_world_rand', ['NN=20', 'initIndexAttempts=4', 'initSearchAttempts=2']),
Nmslib(m, 'small_world_rand', ['NN=17', 'initIndexAttempts=4', 'initSearchAttempts=2']),
Nmslib(m, 'small_world_rand', ['NN=14', 'initIndexAttempts=4', 'initSearchAttempts=2']),
Nmslib(m, 'small_world_rand', ['NN=11', 'initIndexAttempts=5', 'initSearchAttempts=2']),
Nmslib(m, 'small_world_rand', ['NN=8', 'initIndexAttempts=5', 'initSearchAttempts=2']),
Nmslib(m, 'small_world_rand', ['NN=5', 'initIndexAttempts=5', 'initSearchAttempts=2']),
Nmslib(m, 'small_world_rand', ['NN=3', 'initIndexAttempts=5', 'initSearchAttempts=2']),
]
}

if m == 'euclidean':
# Only works for euclidean distance
algos['MP-lsh(lshkit)'] = [
Nmslib(m, 'lsh_multiprobe', ['desiredRecall=0.99','H=1200001','T=10','L=50','tuneK=10']),
Nmslib(m, 'lsh_multiprobe', ['desiredRecall=0.97','H=1200001','T=10','L=50','tuneK=10']),
Nmslib(m, 'lsh_multiprobe', ['desiredRecall=0.95','H=1200001','T=10','L=50','tuneK=10']),
Nmslib(m, 'lsh_multiprobe', ['desiredRecall=0.90','H=1200001','T=10','L=50','tuneK=10']),
Nmslib(m, 'lsh_multiprobe', ['desiredRecall=0.85','H=1200001','T=10','L=50','tuneK=10']),
Nmslib(m, 'lsh_multiprobe', ['desiredRecall=0.80','H=1200001','T=10','L=50','tuneK=10']),
Nmslib(m, 'lsh_multiprobe', ['desiredRecall=0.7','H=1200001','T=10','L=50','tuneK=10']),
Nmslib(m, 'lsh_multiprobe', ['desiredRecall=0.6','H=1200001','T=10','L=50','tuneK=10']),
Nmslib(m, 'lsh_multiprobe', ['desiredRecall=0.5','H=1200001','T=10','L=50','tuneK=10']),
Nmslib(m, 'lsh_multiprobe', ['desiredRecall=0.4','H=1200001','T=10','L=50','tuneK=10']),
Nmslib(m, 'lsh_multiprobe', ['desiredRecall=0.3','H=1200001','T=10','L=50','tuneK=10']),
Nmslib(m, 'lsh_multiprobe', ['desiredRecall=0.2','H=1200001','T=10','L=50','tuneK=10']),
Nmslib(m, 'lsh_multiprobe', ['desiredRecall=0.1','H=1200001','T=10','L=50','tuneK=10']),
]

# END: Non-Metric Space Library (nmslib) entries

return algos


def get_fn(base, args):
fn = os.path.join(base, args.dataset)
Expand Down

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