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0866d60 May 3, 2016
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""" A simple benchmark on the dataset
Compares the running time of this package vs the QMF library from Quora.
On my laptop (2015 Macbook Pro , Dual Core 3.1 GHz Intel Core i7) running
with 50 factors for 15 iterations this is the output:
QMF finished in 547.933080912
Implicit finished in 302.997884989
Implicit is 1.80837262587 times faster
(implicit-mf package was run separately, I estimate it at over 60,000 times
slower on the dataset - with an estimated running time of around 250 days)
from __future__ import print_function
import logging
import argparse
import time
from subprocess import call
from implicit import alternating_least_squares
from lastfm import read_data, bm25_weight
def benchmark_implicit(matrix, factors, reg, iterations):
start = time.time()
alternating_least_squares(matrix, factors, reg, iterations)
return time.time() - start
def benchmark_qmf(qmfpath, matrix, factors, reg, iterations):
matrix = matrix.tocoo()
datafile = "qmf_data.txt"
open(datafile, "w").write("\n".join("%s %s %s" % vals
for vals in zip(matrix.row, matrix.col,
def get_qmf_command(nepochs):
return [qmfpath, "--train_dataset", datafile,
"--nfactors", str(factors),
"--confidence_weight", "1",
"--nepochs", str(nepochs),
"--regularization_lambda", str(reg)]
# ok, so QMF needs to read the data in - and including
# that in the timing isn't fair. So run it once with no iterations
# to get a sense of how long reading the input data takes, and
# subtract from the final results
read_start = time.time()
read_dataset_time = time.time() - read_start
calculate_start = time.time()
return time.time() - calculate_start - read_dataset_time
def run_benchmark(args):
plays = bm25_weight(read_data(args.inputfile)[1])
qmf_time = benchmark_qmf(args.qmfpath, plays, args.factors, args.regularization,
implicit_time = benchmark_implicit(plays, args.factors, args.regularization, args.iterations)
print("QMF finished in", qmf_time)
print("Implicit finished in", implicit_time)
print("Implicit is %s times faster" % (qmf_time / implicit_time))
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="Generates Benchmark",
parser.add_argument('--input', type=str,
dest='inputfile', help=' dataset file')
parser.add_argument('--qmfpath', type=str,
dest='qmfpath', help='full path to qmf wals.bin file', required=True)
parser.add_argument('--factors', type=int, default=50, dest='factors',
help='Number of factors to calculate')
parser.add_argument('--reg', type=float, default=0.8, dest='regularization',
help='regularization weight')
parser.add_argument('--iter', type=int, default=15, dest='iterations',
help='Number of ALS iterations')
args = parser.parse_args()