def __call__(self, params, min_row=0, max_row=-1):
"""Run the BKZ algorithm with parameters `param`.
:param params: BKZ parameters
:param min_row: start processing in this row
:param max_row: stop processing in this row (exclusive)
"""
tracer = BKZTreeTracer(self, verbosity=params.flags & BKZ.VERBOSE, start_clocks=True)
if params.flags & BKZ.AUTO_ABORT:
auto_abort = BKZ.AutoAbort(self.M, self.A.nrows)
cputime_start = time.clock()
with tracer.context("lll"):
self.lll_obj()
i = 0
while True:
with tracer.context("tour", i):
clean = self.tour(params, min_row, max_row, tracer)
i += 1
if clean or params.block_size >= self.A.nrows:
break
if (params.flags & BKZ.AUTO_ABORT) and auto_abort.test_abort():
break
if (params.flags & BKZ.MAX_LOOPS) and i >= params.max_loops:
break
if (params.flags & BKZ.MAX_TIME) and time.clock() - cputime_start >= params.max_time:
break
tracer.exit()
self.trace = tracer.trace
return clean
def __call__(cls,
M,
predicate,
block_size,
invalidate_cache=lambda: None,
threads=1,
max_loops=8,
**kwds):
params = SieverParams(threads=threads)
g6k = Siever(M, params)
tracer = SieveTreeTracer(g6k,
root_label="bkz-sieve",
start_clocks=True)
for b in range(20, block_size + 1, 10):
pump_n_jump_bkz_tour(g6k,
tracer,
b,
pump_params={"down_sieve": True})
auto_abort = BKZ.AutoAbort(M, M.d)
found, ntests, solution = False, 0, None
for tour in range(max_loops):
pump_n_jump_bkz_tour(g6k,
tracer,
block_size,
pump_params={"down_sieve": True})
invalidate_cache()
if auto_abort.test_abort():
break
with tracer.context("check"):
for i, v in enumerate(M.B):
ntests += 1
if predicate(v, standard_basis=True):
solution = tuple([int(v_) for v_ in v])
found = True
break
if found:
break
tracer.exit()
b0, b0e = M.get_r_exp(0, 0)
return USVPPredSolverResults(
success=found,
ntests=ntests,
solution=solution,
b0=b0**(0.5) * 2**(b0e / 2.0),
cputime=tracer.trace.data["cputime"],
walltime=tracer.trace.data["walltime"],
data=tracer.trace,
)
def __call__(cls,
M,
predicate,
block_size,
invalidate_cache=lambda: None,
max_loops=8,
threads=1,
**kwds):
bkz = BKZ2(M)
if block_size > STRATEGIES_MAX_DIM:
warnings.warn(
"reducing block size to {max}".format(max=STRATEGIES_MAX_DIM))
block_size = STRATEGIES_MAX_DIM
FPLLL.set_threads(threads)
params = BKZ.EasyParam(block_size=block_size, **kwds)
auto_abort = BKZ.AutoAbort(M, M.d)
tracer = BKZTreeTracer(bkz, root_label="bkz_enum", start_clocks=True)
found, ntests, solution = False, 0, None
for tour in range(max_loops):
bkz.tour(params)
if auto_abort.test_abort():
break
invalidate_cache()
with tracer.context("check"):
for i, v in enumerate(bkz.M.B):
ntests += 1
if predicate(v, standard_basis=True):
found = True
solution = tuple([int(v_) for v_ in v])
break
if found:
break
FPLLL.set_threads(1)
tracer.exit()
b0, b0e = bkz.M.get_r_exp(0, 0)
return USVPPredSolverResults(
success=found,
solution=solution,
ntests=ntests,
b0=b0**(0.5) * 2**(b0e / 2.0),
cputime=tracer.trace.data["cputime"],
walltime=tracer.trace.data["walltime"],
data=tracer.trace,
)
def __call__(self, block_size):
"""Perform BKZ reduction with given``block_size``.
Nothing is returned, the matrix ``A`` given during construction is modified in-place.
:param block_size: an integer > 2
"""
self.m.discover_all_rows()
auto_abort = BKZ.AutoAbort(self.m, self.A.nrows)
while True:
clean = self.bkz_loop(block_size, 0, self.A.nrows)
if clean:
break
if auto_abort.test_abort():
break
def __call__(self, params, min_row=0, max_row=-1, tracer=False):
"""Run the BKZ algorithm with parameters `param`.
:param params: BKZ parameters
:param min_row: start processing in this row
:param max_row: stop processing in this row (exclusive)
:param tracer: see ``normalize_tracer`` for accepted values
TESTS::
>>> from fpylll import *
>>> A = IntegerMatrix.random(60, "qary", k=30, q=127)
>>> from fpylll.algorithms.bkz import BKZReduction
>>> bkz = BKZReduction(A)
>>> _ = bkz(BKZ.EasyParam(10), tracer=True); bkz.trace is None
False
>>> _ = bkz(BKZ.EasyParam(10), tracer=False); bkz.trace is None
True
"""
tracer = normalize_tracer(tracer)
try:
label = params["name"]
except KeyError:
label = "bkz"
if not isinstance(tracer, Tracer):
tracer = tracer(
self,
root_label=label,
verbosity=params.flags & BKZ.VERBOSE,
start_clocks=True,
max_depth=2,
)
if params.flags & BKZ.AUTO_ABORT:
auto_abort = BKZ.AutoAbort(self.M, self.A.nrows)
cputime_start = process_time()
with tracer.context("lll"):
self.lll_obj()
i = 0
while True:
with tracer.context("tour",
i,
dump_gso=params.flags & BKZ.DUMP_GSO):
clean = self.tour(params, min_row, max_row, tracer)
i += 1
if clean or params.block_size >= self.A.nrows:
break
if (params.flags & BKZ.AUTO_ABORT) and auto_abort.test_abort():
break
if (params.flags & BKZ.MAX_LOOPS) and i >= params.max_loops:
break
if (params.flags & BKZ.MAX_TIME
) and process_time() - cputime_start >= params.max_time:
break
tracer.exit()
try:
self.trace = tracer.trace
except AttributeError:
self.trace = None
return clean