def oneshot(ver, gene):
import sys
if "../lib" not in sys.path:
sys.path.append("../lib")
import geneop
import config as cfg
gene_type = ver
geneop.load_type(gene_type)
gene = int(gene)
n = {
"v1": 142,
}[gene_type]
gene = geneop.cvtintlst(gene, n)
cfg.worker_config = {
"result_format": ("sdr", "neg_gflops", "neg_mega_pc"),
"batch_size": 2,
"max_lr": 3e-4,
"min_lr": 1e-4,
"warmup_fac": 0.3,
"first_lr_period": 100,
"warmup_period": 100,
"n_hop_per_sample": 64,
"work_sr": 8000,
"hop_size": 256,
"fft_size": 1024,
"n_feature": 512,
"n_train": 156,
"n_step": 700,
"n_eval": 3,
}
pre_fn()
r = eval_fn(gene)
del cfg.worker_config
clean_env()
return r
def infer(x, n_out_channel, train, ver=None, gene=None):
import sys
if not "../lib" in sys.path:
sys.path.append("../lib")
import geneop
import config as cfg
if ver is not None:
geneop.load_type(ver)
if isinstance(gene, int):
gene = geneop.cvtintlst(gene, geneop.gene_len)
else:
raise TypeError("Invalid gene value `%r`" % (gene,))
else:
geneop.load_type(cfg.gene_ver)
gene = geneop.cvtintlst(cfg.gene_value, geneop.gene_len)
return geneop.build_from_gene(x, n_out_channel, gene)
def boundary():
cb = geneop.cvtintlst(0b0, 1)
ccg_res = geneop.cvtintlst(0b1, 1) + cb + cb
cg_res_64 = geneop.cvtintlst(0b11, 2) + ccg_res
cg_pass = geneop.cvtintlst(0b00, 2) + ccg_res
pb_1x16 = geneop.cvtintlst(0b00_11, 4)
pb_pass = geneop.cvtintlst(0b00_00, 4)
rb_a = pb_1x16 + geneop.cvtintlst(0b11, 2) + ccg_res
rb_pass = pb_pass + geneop.cvtintlst(0b11, 2) + ccg_res
b_a = cg_res_64 + rb_a + rb_pass + ccg_res
b_b = cg_res_64 + rb_pass + rb_a + ccg_res
assert b_from_gene(None, 128, b_a) == b_from_gene(None, 128, b_a)
v4m0 = geneop.cvtintlst(0b11_0_00_000_0000,
12) + b_a + b_a + b_a + b_a + b_a
v4m0_b = geneop.cvtintlst(0b11_0_00_000_0000,
12) + b_b + b_a + b_b + b_a + b_b
v4m0_c = geneop.cvtintlst(0b11_0_01_001_0001,
12) + b_b + b_a + b_b + b_a + b_b
assert cmp_gene(v4m0, v4m0_b)
assert not cmp_gene(v4m0, v4m0_c)
print(geneop.cvtlstint(v4m0))
def eval_single(gene):
gene = geneop.cvtintlst(int(gene), cfg.n)
return cfg.worker.eval_fn(gene)
# module: Python module for specified evo_type (do not change!)
evo_module = __import__("evo_%s" % (evo_type, ))
# float: Ratio of pure random gene in initial population.
# 0.0 means no pure random gene, 1.0 means all population are built with pure random gene.
init_random_ratio = 0.0
p2 = 0.02
# Section: Gene
# str: "v1" for the paper (do not change!)
gene_type = "v1"
geneop.load_type(gene_type)
# List[List[bool]]: Handcrafted initial population (do not change!)
if init_random_ratio != 1.0:
if gene_type == "v1":
manual_gene_list = [
geneop.cvtintlst(x, 142) for x in [
4182591019167972528534244115322478782824676,
]
]
else:
assert False
# Section: Evolution(Additional)
# int: Maximum number of bits to flip when generate gene from handcrafted popluation (do not change!)
if init_random_ratio != 1.0:
if gene_type in ("v1", ):
gene_jitter_count = 20
else:
assert False
# Section: Worker