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import os
from argparse import ArgumentParser, ArgumentDefaultsHelpFormatter
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(formatter_class=ArgumentDefaultsHelpFormatter)
parser.add_argument("--threads", type=int, default=4, help="Number of threads")
parser.add_argument("--parsimony", type=float, default=0.001, help="How much to punish complexity")
parser.add_argument("--alpha", type=int, default=10, help="Scaling of temperature")
parser.add_argument("--maxsize", type=int, default=20, help="Max size of equation")
parser.add_argument("--niterations", type=int, default=20, help="Number of total migration periods")
parser.add_argument("--npop", type=int, default=100, help="Number of members per population")
parser.add_argument("--ncyclesperiteration", type=int, default=5000, help="Number of evolutionary cycles per migration")
parser.add_argument("--topn", type=int, default=10, help="How many best species to distribute from each population")
parser.add_argument("--fractionReplacedHof", type=float, default=0.1, help="Fraction of population to replace with hall of fame")
parser.add_argument("--fractionReplaced", type=float, default=0.1, help="Fraction of population to replace with best from other populations")
parser.add_argument("--migration", type=bool, default=True, help="Whether to migrate")
parser.add_argument("--hofMigration", type=bool, default=True, help="Whether to have hall of fame migration")
parser.add_argument("--shouldOptimizeConstants", type=bool, default=True, help="Whether to use classical optimization on constants before every migration (doesn't impact performance that much)")
parser.add_argument("--annealing", type=bool, default=True, help="Whether to use simulated annealing")
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)
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