def setUp(self):
self.parser = train.create_parser()
init_channels: int, classes: int, layers: int,
auxiliary: bool) -> int:
model = Network(init_channels, classes, layers, auxiliary, genotype)
model_size_mb = utils.count_parameters_in_MB(model)
batch_size = 0
consumption = 0
while consumption < (memory - 500):
batch_size += 1
consumption = batch_model.predict([[model_size_mb, batch_size]])
log.info("Predicted consumption is %d MB", consumption)
return batch_size
if __name__ == '__main__':
log = logging.getLogger("batch_train")
parser = create_parser()
parser.add_argument('--archs',
type=str,
required=False,
nargs='+',
help='list of architectures to use',
default=[
arch for arch, gen in genotypes.__dict__.items()
if isinstance(gen, Genotype)
])
parser.add_argument('--batch_model',
type=str,
default="batch_predict.pkl",
help='list of architectures to use')
args = parser.parse_args()
def test_lc(self):
parser = train.create_parser()
namespace = parser.parse_args(("--lc", ))
self.assertIsNotNone(namespace.lc)
import argparse
import train
train_commands = [
# anoCAE
"-d LEGO_light/SV -a anoCAE -b 8 -l mssim -c rgb -e 60 -r custom --inspect",
# baselineCAE
"-d LEGO_light/SV -a baselineCAE -b 8 -l mssim -c rgb -e 60 -r custom --inspect",
# inceptionCAE
"-d LEGO_light/SV -a inceptionCAE -b 8 -l mssim -c rgb -e 60 -r custom --inspect",
# mvtecCAE
"-d LEGO_light/SV -a mvtecCAE -b 8 -l mssim -c rgb -e 60 -r custom --inspect",
# resnetCAE
"-d LEGO_light/SV -a resnetCAE -b 8 -l mssim -c rgb -e 60 -r custom --inspect",
# skipCAE
"-d LEGO_light/SV -a skipCAE -b 8 -l mssim -c rgb -e 60 -r custom --inspect",
]
parser = train.create_parser()
for command in train_commands:
args_list = command.split(" ")
args = parser.parse_args(args_list)
try:
train.main(args)
except Exception:
pass
def test_no_lc(self):
commands = train.create_parser().parse_args(("--model", "model.txt"))
words = train.prepare_line('I hate unittests.,,apple;', commands)
for word in words:
self.assertTrue(word.isalpha())
def test_lc(self):
commands = train.create_parser().parse_args(("--lc", ))
words = train.prepare_line("I don't like unittest__oh-oh", commands)
for word in words:
self.assertTrue(word.islower())
self.assertTrue(word.isalpha())
def test_model(self):
parser = train.create_parser()
namespace = parser.parse_args(("--mode", "model.txt"))
self.assertEqual(namespace.model, "model.txt")
def test_input_dir(self):
parser = train.create_parser()
namespace = parser.parse_args(("--input-dir", "input/"))
self.assertEqual("input/", namespace.input_dir)
def run_experiments(experiments_filepath):
parser = create_parser()
args = parser.parse_args(args=[])
args.config_file = experiments_filepath
run(args, parser)