def acnet_cfqkbnc():
try_arg = start_exp()
network_type = 'cfqkbnc'
dataset_name = 'cifar10'
log_dir = 'acnet_exps/{}_{}_train'.format(network_type, try_arg)
save_weights = 'acnet_exps/{}_{}_savedweights.pth'.format(
network_type, try_arg)
weight_decay_strength = 1e-4
batch_size = 64
lrs = parse_usual_lr_schedule(try_arg)
if 'bias' in try_arg:
weight_decay_bias = weight_decay_strength
else:
weight_decay_bias = 0
if 'warmup' in try_arg:
warmup_factor = 0
else:
warmup_factor = 1
config = get_baseconfig_by_epoch(
network_type=network_type,
dataset_name=dataset_name,
dataset_subset='train',
global_batch_size=batch_size,
num_node=1,
weight_decay=weight_decay_strength,
optimizer_type='sgd',
momentum=0.9,
max_epochs=lrs.max_epochs,
base_lr=lrs.base_lr,
lr_epoch_boundaries=lrs.lr_epoch_boundaries,
lr_decay_factor=lrs.lr_decay_factor,
warmup_epochs=5,
warmup_method='linear',
warmup_factor=warmup_factor,
ckpt_iter_period=20000,
tb_iter_period=100,
output_dir=log_dir,
tb_dir=log_dir,
save_weights=save_weights,
val_epoch_period=2,
linear_final_lr=lrs.linear_final_lr,
weight_decay_bias=weight_decay_bias)
if 'normal' in try_arg:
builder = None
elif 'acnet' in try_arg:
from acnet.acnet_builder import ACNetBuilder
builder = ACNetBuilder(base_config=config, deploy=False)
else:
assert False
ding_train(config,
show_variables=True,
convbuilder=builder,
use_nesterov='nest' in try_arg)
def acnet_wrnc16():
try_arg = start_exp()
network_type = 'wrnc16plain'
dataset_name = 'cifar10'
log_dir = 'acnet_exps/{}_{}_train'.format(network_type, try_arg)
save_weights = 'acnet_exps/{}_{}_savedweights.pth'.format(network_type, try_arg)
weight_decay_strength = 5e-4
batch_size = 128
deps = wrn_origin_deps_flattened(2, 8)
lrs = parse_usual_lr_schedule(try_arg)
config = get_baseconfig_by_epoch(network_type=network_type, dataset_name=dataset_name, dataset_subset='train',
global_batch_size=batch_size, num_node=1,
weight_decay=weight_decay_strength, optimizer_type='sgd', momentum=0.9,
max_epochs=lrs.max_epochs, base_lr=lrs.base_lr, lr_epoch_boundaries=lrs.lr_epoch_boundaries,
lr_decay_factor=lrs.lr_decay_factor,
warmup_epochs=5, warmup_method='linear', warmup_factor=1,
ckpt_iter_period=20000, tb_iter_period=100, output_dir=log_dir,
tb_dir=log_dir, save_weights=save_weights, val_epoch_period=2, deps=deps)
if 'normal' in try_arg:
builder = None
elif 'acnet' in try_arg:
from acnet_builder import ACNetBuilder
builder = ACNetBuilder()
else:
assert False
ding_train(config, show_variables=True, convbuilder=builder)