def __init__(self, parser):
opt = parser.parse_args()
# Possibly build a dictionary (not all models do this).
if opt['dict_build_first'] and 'dict_file' in opt:
if opt['dict_file'] is None and opt.get('model_file'):
opt['dict_file'] = opt['model_file'] + '.dict'
print("[ building dictionary first... ]")
build_dict(opt)
# Create model and assign it to the specified task
self.agent = create_agent(opt)
self.world = create_task(opt, self.agent)
self.train_time = Timer()
self.validate_time = Timer()
self.log_time = Timer()
self.save_time = Timer()
print('[ training... ]')
self.parleys = 0
self.max_num_epochs = opt['num_epochs'] if opt['num_epochs'] > 0 else float('inf')
self.max_train_time = opt['max_train_time'] if opt['max_train_time'] > 0 else float('inf')
self.log_every_n_secs = opt['log_every_n_secs'] if opt['log_every_n_secs'] > 0 else float('inf')
self.val_every_n_secs = opt['validation_every_n_secs'] if opt['validation_every_n_secs'] > 0 else float('inf')
self.save_every_n_secs = opt['save_every_n_secs'] if opt['save_every_n_secs'] > 0 else float('inf')
self.best_valid = 0
self.impatience = 0
self.saved = False
self.valid_world = None
self.opt = opt
def __init__(self, parser):
opt = parser.parse_args()
# Possibly build a dictionary (not all models do this).
if opt['dict_build_first'] and 'dict_file' in opt:
if opt['dict_file'] is None and opt.get('model_file'):
opt['dict_file'] = opt['model_file'] + '.dict'
print("[ building dictionary first... ]")
build_dict(opt)
# Create model and assign it to the specified task
self.agent = create_agent(opt)
self.world = create_task(opt, self.agent)
self.train_time = Timer()
self.validate_time = Timer()
self.log_time = Timer()
self.save_time = Timer()
print('[ training... ]')
self.parleys = 0
self.max_num_epochs = opt[
'num_epochs'] if opt['num_epochs'] > 0 else float('inf')
self.max_train_time = opt[
'max_train_time'] if opt['max_train_time'] > 0 else float('inf')
self.log_every_n_secs = opt['log_every_n_secs'] if opt[
'log_every_n_secs'] > 0 else float('inf')
self.val_every_n_secs = opt['validation_every_n_secs'] if opt[
'validation_every_n_secs'] > 0 else float('inf')
self.save_every_n_secs = opt['save_every_n_secs'] if opt[
'save_every_n_secs'] > 0 else float('inf')
self.best_valid = 0
self.impatience = 0
self.saved = False
self.valid_world = None
self.opt = opt
def __init__(self, parser):
opt = parser.parse_args()
# Possibly load from checkpoint
if opt['load_from_checkpoint'] and opt.get(
'model_file') and os.path.isfile(opt['model_file'] +
'.checkpoint'):
opt['init_model'] = opt['model_file'] + '.checkpoint'
# Possibly build a dictionary (not all models do this).
if opt['dict_build_first'] and 'dict_file' in opt:
if opt['dict_file'] is None and opt.get('model_file'):
opt['dict_file'] = opt['model_file'] + '.dict'
print("[ building dictionary first... ]")
build_dict(opt)
# Create model and assign it to the specified task
self.agent = create_agent(opt)
self.world = create_task(opt, self.agent)
self.train_time = Timer()
self.validate_time = Timer()
self.log_time = Timer()
self.save_time = Timer()
print('[ training... ]')
self.parleys = 0
self.max_num_epochs = opt[
'num_epochs'] if opt['num_epochs'] > 0 else float('inf')
self.max_train_time = opt[
'max_train_time'] if opt['max_train_time'] > 0 else float('inf')
self.log_every_n_secs = opt['log_every_n_secs'] if opt[
'log_every_n_secs'] > 0 else float('inf')
self.val_every_n_secs = opt['validation_every_n_secs'] if opt[
'validation_every_n_secs'] > 0 else float('inf')
self.save_every_n_secs = opt['save_every_n_secs'] if opt[
'save_every_n_secs'] > 0 else float('inf')
self.valid_optim = 1 if opt['validation_metric_mode'] == 'max' else -1
self.best_valid = None
if opt.get('model_file') and os.path.isfile(opt['model_file'] +
'.best_valid'):
with open(opt['model_file'] + ".best_valid", 'r') as f:
x = f.readline()
self.best_valid = float(x)
f.close()
self.impatience = 0
self.saved = False
self.valid_world = None
self.opt = opt