def get_default_specific_model_parameters(network_class, network_type):
model_params = HParams(model_class=None)
if network_type is not None:
model_module_name = 'model_%s' % network_type
model_class_name = underline_to_camel(model_module_name)
try:
src_module = __import__('src.models.%s.%s' %
(network_class, model_module_name))
model_class = eval(
'src_module.models.%s.%s.%s' %
(network_class, model_module_name, model_class_name))
model_params = model_class.get_default_model_parameters()
model_params.add_hparam('model_class',
model_class) # add model class
except ImportError:
print('Fatal Error: no model module: \"src.models.%s.%s\"' %
(network_class, model_module_name))
except AttributeError:
print(
'Fatal Error: probably (1) no model class named as %s.%s, '
'or (2) the class no \"get_default_model_parameters()\"' %
(network_class, model_module_name))
return model_params
class ParamsCenter(object):
def __init__(self):
self.hparam_name_list = []
# ------parsing input arguments"--------
parser = argparse.ArgumentParser()
parser.register('type', 'bool', (lambda x: x.lower() in
("yes", "true", "t", "1")))
parser.add_argument('--mode',
type=str,
default='train',
help='train_tasks')
parser.add_argument('--dataset',
type=str,
default='snli',
help='[snli|multinli_m|multinli_mm]')
parser.add_argument('--network_class',
type=str,
default='transformer',
help='None')
parser.add_argument('--network_type',
type=str,
default=None,
help='None')
parser.add_argument('--gpu',
type=str,
default='3',
help='selected gpu index')
parser.add_argument('--gpu_mem',
type=float,
default=None,
help='selected gpu index')
parser.add_argument('--model_dir_prefix',
type=str,
default='prefix',
help='model dir name prefix')
parser.add_argument('--aws',
type='bool',
default=False,
help='using aws')
# parsing parameters group
parser.add_argument('--preprocessing_params',
type=str,
default='',
help='')
parser.add_argument('--model_params', type=str, default='', help='')
parser.add_argument('--training_params', type=str, default='', help='')
parser.set_defaults(shuffle=True)
args = parser.parse_args()
self.parsed_params = HParams()
for key, val in args.__dict__.items():
self.parsed_params.add_hparam(key, val)
self.register_hparams(self.parsed_params, 'parsed_params')
# pre-processed
self.preprocessed_params = self.get_default_preprocessing_params()
self.preprocessed_params.parse(self.parsed_params.preprocessing_params)
self.register_hparams(self.preprocessed_params, 'preprocessed_params')
# model
self.model_params = merge_params(
self.get_default_model_parameters(),
self.get_default_specific_model_parameters(
self.parsed_params.network_class,
self.parsed_params.network_type))
self.model_params.parse(self.parsed_params.model_params)
self.register_hparams(self.model_params, 'model_params')
# traning
self.training_params = self.get_default_training_params()
self.training_params.parse(self.parsed_params.training_params)
self.register_hparams(self.training_params, 'training_params')
@staticmethod
def get_default_preprocessing_params():
params = HParams(
max_sent_len=50,
load_preproc=True,
)
return params
@staticmethod
def get_default_model_parameters():
return HParams()
@staticmethod
def get_default_training_params():
hparams = HParams(
optimizer='openai_adam',
grad_norm=1.,
n_steps=90000,
lr=6.25e-5,
# control
save_model=False,
save_num=3,
load_model=False,
load_path='',
summary_period=1000,
eval_period=500,
train_batch_size=20,
test_batch_size=24,
)
return hparams
@staticmethod
def get_default_specific_model_parameters(network_class, network_type):
model_params = HParams(model_class=None)
if network_type is not None:
model_module_name = 'model_%s' % network_type
model_class_name = underline_to_camel(model_module_name)
try:
src_module = __import__('src.models.%s.%s' %
(network_class, model_module_name))
model_class = eval(
'src_module.models.%s.%s.%s' %
(network_class, model_module_name, model_class_name))
model_params = model_class.get_default_model_parameters()
model_params.add_hparam('model_class',
model_class) # add model class
except ImportError:
print('Fatal Error: no model module: \"src.models.%s.%s\"' %
(network_class, model_module_name))
except AttributeError:
print(
'Fatal Error: probably (1) no model class named as %s.%s, '
'or (2) the class no \"get_default_model_parameters()\"' %
(network_class, model_module_name))
return model_params
# ============== Utils =============
def register_hparams(self, hparams, name):
assert isinstance(hparams, HParams)
assert isinstance(name, str)
assert name not in self.hparam_name_list
self.hparam_name_list.append(name)
setattr(self, name, hparams)
@property
def all_params(self):
all_params = HParams()
for hparam_name in reversed(self.hparam_name_list):
cur_params = getattr(self, hparam_name)
all_params = merge_params(all_params, cur_params)
return all_params
def __getitem__(self, item):
assert isinstance(item, str)
for hparam_name in reversed(self.hparam_name_list):
try:
return getattr(getattr(self, hparam_name), item)
except AttributeError:
pass
raise AttributeError('no item named as \'%s\'' % item)