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Merge pull request #6 from searchivarius/master
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Adding benchmarks for some of the Non-Metric Space Library Methods
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@erikbern
erikbern committed Jun 14, 2015
2 parents 09f2fc6 + a9d735e commit edbc72b
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2 changes: 1 addition & 1 deletion README.rst
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Expand Up @@ -12,6 +12,7 @@ Evaluated
* `PANNS <https://github.com/ryanrhymes/panns>`__
* `NearPy <http://nearpy.io>`__
* `KGraph <https://github.com/aaalgo/kgraph>`__
* `NonMetricSpaceLib <https://github.com/searchivarius/NonMetricSpaceLib>`__

Data sets
---------
Expand Down Expand Up @@ -65,5 +66,4 @@ References
----------

* `sim-shootout <https://github.com/piskvorky/sim-shootout>`__ by Radim Řehůřek
* `NonMetricSpaceLib <https://github.com/searchivarius/NonMetricSpaceLib>`__
* This `blog post <http://maheshakya.github.io/gsoc/2014/08/17/performance-comparison-among-lsh-forest-annoy-and-flann.html>`__
74 changes: 73 additions & 1 deletion ann_benchmarks.py
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Expand Up @@ -2,6 +2,7 @@
import annoy
import pyflann
import panns
import nmslib
import nearpy, nearpy.hashes, nearpy.distances
import pykgraph
import gzip, numpy, time, os, multiprocessing, argparse, pickle, resource
Expand Down Expand Up @@ -173,6 +174,26 @@ def query(self, v, n):
result = self._kgraph.search(self._X, numpy.array([v]), K=n, threads=1, P=self._P)
return result[0]

class Nmslib(BaseANN):
def __init__(self, metric, method_name, method_param):
self._nmslib_metric = {'angular': 'cosinesimil', 'euclidean': 'l2'}[metric]
self._method_name = method_name
self._method_param = method_param
self.name = 'Nmslib(method_name=%s, method_param=%s)' % (method_name, method_param)

def fit(self, X):
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):
return nmslib.knnQuery(self._index, n, v.tolist())

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


class BruteForce(BaseANN):
def __init__(self, metric):
Expand Down Expand Up @@ -260,7 +281,58 @@ def get_algos(m):
'kgraph': [KGraph(m, 20), KGraph(m, 50), KGraph(m, 100), KGraph(m, 200), KGraph(m, 500), KGraph(m, 1000)],
'bruteforce': [BruteForce(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)]
'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
}


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2 changes: 1 addition & 1 deletion install.sh
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sudo apt-get install -y python-numpy python-scipy
cd install
for fn in annoy.sh panns.sh nearpy.sh sklearn.sh flann.sh kgraph.sh glove.sh sift.sh
for fn in annoy.sh panns.sh nearpy.sh sklearn.sh flann.sh kgraph.sh nmslib.sh glove.sh sift.sh
do
source $fn
done
3 changes: 1 addition & 2 deletions install/glove.sh
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wget "http://www-nlp.stanford.edu/data/glove.twitter.27B.100d.txt.gz"
gzip -d glove.twitter.27B.100d.txt.gz
rm glove.twitter.27B.100d.txt.gz
gunzip -d glove.twitter.27B.100d.txt.gz
cut -d " " -f 2- glove.twitter.27B.100d.txt > glove.txt # strip first column
rm glove.twitter.27B.100d.txt
16 changes: 16 additions & 0 deletions install/nmslib.sh
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echo "Installing Python interface for the Non-Metric Space Library"
# Remove the previous version if existed
rm -rf NonMetricSpaceLib
# Note that we use the develop branch here:
git clone https://github.com/searchivarius/NonMetricSpaceLib.git
cd NonMetricSpaceLib/similarity_search
git checkout ann-benchmark
sudo apt-get install -y cmake libeigen3-dev libgsl0-dev libboost-all-dev g++-4.8
# Actually let's make g++ an alias
alias g++=g++-4.8
cmake .
make -j 4
cd ../python_binding
make
sudo make install
cd ..

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