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import os | |
from argparse import ArgumentParser | |
from collections import namedtuple | |
def eureqa(threads=4, parsimony=1e-3, alpha=10, | |
maxsize=20, migration=True, | |
hofMigration=True, fractionReplacedHof=0.1, | |
shouldOptimizeConstants=True, | |
binary_operators=["plus", "mult"], | |
unary_operators=["cos", "exp", "sin"], | |
niterations=20, npop=100, annealing=True, | |
ncyclesperiteration=5000, fractionReplaced=0.1, | |
topn=10 | |
): | |
def_hyperparams = f""" | |
include("operators.jl") | |
########################## | |
# # Allowed operators | |
# (Apparently using const for globals helps speed) | |
const binops = {'[' + ', '.join(binary_operators) + ']'} | |
const unaops = {'[' + ', '.join(unary_operators) + ']'} | |
########################## | |
# How many equations to search when replacing | |
const ns=10; | |
################## | |
# Hyperparameters | |
# How much to punish complexity | |
const parsimony = {parsimony:f}f0 | |
# How much to scale temperature by (T between 0 and 1) | |
const alpha = {alpha:f}f0 | |
# Max size of an equation (too large will slow program down) | |
const maxsize = {maxsize:d} | |
# Whether to migrate between threads (you should) | |
const migration = {'true' if migration else 'false'} | |
# Whether to re-introduce best examples seen (helps a lot) | |
const hofMigration = {'true' if hofMigration else 'false'} | |
# Fraction of population to replace with hall of fame | |
const fractionReplacedHof = {fractionReplacedHof}f0 | |
# Optimize constants | |
const shouldOptimizeConstants = {'true' if shouldOptimizeConstants else 'false'} | |
################## | |
""" | |
def_datasets = """ | |
# Here is the function we want to learn (x2^2 + cos(x3) + 5) | |
########################## | |
# # Dataset to learn | |
const X = convert(Array{Float32, 2}, randn(100, 5)*2) | |
const y = convert(Array{Float32, 1}, ((cx,)->cx^2).(X[:, 2]) + cos.(X[:, 3]) .- 5) | |
########################## | |
""" | |
with open('.hyperparams.jl', 'w') as f: | |
print(def_hyperparams, file=f) | |
with open('.dataset.jl', 'w') as f: | |
print(def_datasets, file=f) | |
command = ' '.join([ | |
'julia -O3', | |
f'--threads {threads}', | |
'-e', | |
f'\'include("paralleleureqa.jl"); fullRun({niterations:d}, npop={npop:d}, annealing={"true" if annealing else "false"}, ncyclesperiteration={ncyclesperiteration:d}, fractionReplaced={fractionReplaced:f}f0, verbosity=round(Int32, 1e9), topn={topn:d})\'' | |
]) | |
import os | |
os.system(command) | |
if __name__ == "__main__": | |
parser = ArgumentParser() | |
parser.add_argument("--threads", type=int, default=4, help="number of threads") | |
parser.add_argument("--parsimony", type=float, default=4, help="number of threads") | |
parser.add_argument( | |
"--binary-operators", type=str, nargs="+", default=["plus", "mul"], | |
help="Binary operators. Make sure they are defined in operators.jl") | |
parser.add_argument( | |
"--unary-operators", type=str, default=["exp", "sin", "cos"], | |
help="Unary operators. Make sure they are defined in operators.jl") | |
args = vars(parser.parse_args()) #dict | |
run(**args) | |