Option('gethidrep', 'whether to dump hidden rep after loading [%default]', False, converter=int),
Option('pretrain', 'whether to dump matrices and configs without doing anything [%default]', True, converter=int),
Option('finetune', 'whether to do fine tuning after initializing/learning weights [%default]', False, converter=int),
Option('finetune_epochs', 'epochs for fine-tuning [%default]', 100, converter=int),
Option('finetune_rprop', 'whether to use rprop for fine-tuning [%default]', 1, converter=int),
Option('finetune_batch_size', 'size of minibatches for fine-tuning [%default]', 1000, converter=int),
Option('finetune_softmax', 'whether to use softmax for fine-tuning [%default]', 1, converter=int),
Option('finetune_learnrate', 'learnrate for finetuning [%default]', 0.01, converter=float),
Option('finetune_cost', 'weight decay for finetuning [%default]', 0.001, converter=float),
Option('finetune_momentum', 'momentum for finetuning when backprop used [%default]', 0.5, converter=float),
Option('finetune_onlylast', 'epochs where only not-pretrained upper layer is updated [%default]', 0, converter=int),
Option('finetune_online_learning', 'online learning [%default]', '0', converter=int),
]
cfg = Config(options, usage = "usage: %prog [options]")
try:
sys.path.insert(0,os.path.join(os.getenv('HOME'),'bin'))
import optcomplete
optcomplete.autocomplete(cfg._parser)
except ImportError:
pass
cfg.grab_from_argv(sys.argv) # to fetch the config file name
try:
os.mkdir(cfg.workdir)
except:pass
cfg.config_file = os.path.join(cfg.workdir, "pyrbm.ini")
Option('finetune_momentum',
'momentum for finetuning when backprop used [%default]',
0.5,
converter=float),
Option(
'finetune_onlylast',
'epochs where only not-pretrained upper layer is updated [%default]',
0,
converter=int),
Option('finetune_online_learning',
'online learning [%default]',
'0',
converter=int),
]
cfg = Config(options, usage="usage: %prog [options]")
try:
sys.path.insert(0, os.path.join(os.getenv('HOME'), 'bin'))
import optcomplete
optcomplete.autocomplete(cfg._parser)
except ImportError:
pass
cfg.grab_from_argv(sys.argv) # to fetch the config file name
try:
os.mkdir(cfg.workdir)
except:
pass
cfg.config_file = os.path.join(cfg.workdir, "pyrbm.ini")
cp.rnd_binarize(self.v)
if __name__=='__main__':
loc = locals()
options = [
Option('device', 'GPU device to use [%default]', 0, short_name='d', converter=int),
Option('chains', 'number of markov chains [%default]', 512, short_name='c', converter=int),
Option('steps', 'number of annealing steps (don\'t change this at the moment [%default]', 145000, short_name='s', converter=int),
Option('postfix', 'index/postfix of file [%default]', "pretrain", short_name='i', converter=str),
Option('utype', 'type of visible units (cont/gaussian/binary) [%default]', 'binary.binary', short_name='V', converter=lambda x: [eval("UnitType."+y, loc) for y in x.split(".")]),
Option('path', 'Path to weights [%default]', '.', short_name='p', converter=str),
]
cfg = Config(options, usage = "usage: %prog [options]")
try:
sys.path.insert(0,os.path.join(os.getenv('HOME'),'bin'))
import optcomplete
optcomplete.autocomplete(cfg._parser)
except ImportError:
pass
cfg.grab_from_argv(sys.argv)
cfg.batchsize=-1 # not used, only compatibility with dataset classes
#load pickle with rbm cfg
fn = os.path.join(cfg.path, "info-0.pickle")
with open(fn,"r") as f:
rbmcfg=cPickle.load(f)