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import sys
import pickle
import itertools
import glob
from pyecsca.misc.utils import TaskExecutor
from tqdm.auto import tqdm
from common import *
def divides_any(l: int, small_scalars: set[int]) -> bool:
for s in small_scalars:
if s%l==0:
return True
return False
def process_small_scalars(scalar_results: MultResults, divisors: set[int]) -> ProbMap:
result = {}
for divisor in divisors:
count = 0
for smult in scalar_results.multiplications:
if divides_any(divisor, smult):
count += 1
result[divisor] = count / scalar_results.samples
return ProbMap(result, scalar_results.samples, scalar_results.kind)
def load_chunk(fname: str, divisors: set[int], kind: str) -> dict[MultIdent, ProbMap]:
with open(fname, "rb") as f:
multiples = {}
while True:
try:
mult, distr = pickle.load(f)
multiples[mult] = distr
except EOFError:
break
res = {}
for mult, results in multiples.items():
results.kind = kind
res[mult] = process_small_scalars(results, divisors)
return res
if __name__ == "__main__":
distributions_mults = {}
bits = 256
num_workers = int(sys.argv[1]) if len(sys.argv) > 1 else 32
divisor_name = sys.argv[2] if len(sys.argv) > 2 else "all"
kind = sys.argv[3] if len(sys.argv) > 3 else "precomp+necessary"
use_init = (sys.argv[4].lower() == "true") if len(sys.argv) > 4 else True
use_multiply = (sys.argv[5].lower() == "true") if len(sys.argv) > 5 else True
files = sorted(glob.glob(f"multiples_{bits}_{kind}_{'init' if use_init else 'noinit'}_{'mult' if use_multiply else 'nomult'}_chunk*.pickle"))
selected_divisors = divisor_map[divisor_name]
with TaskExecutor(max_workers=num_workers) as pool:
for fname in files:
pool.submit_task(fname,
load_chunk,
fname, selected_divisors, kind)
for fname, future in tqdm(pool.as_completed(), total=len(pool.tasks), smoothing=0):
if error := future.exception():
print(f"Error {fname}, {error}")
continue
new_distrs = future.result()
for mult, prob_map in new_distrs.items():
if mult in distributions_mults:
distributions_mults[mult].merge(prob_map)
else:
distributions_mults[mult] = prob_map
for mult, prob_map in distributions_mults.items():
print(f"Got {prob_map.samples} for {mult}.")
# Save
with open(f"{divisor_name}_{kind}_distrs.pickle", "wb") as f:
pickle.dump(distributions_mults, f)
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