print "Error: the argument %s has to be specified" % (arg)
exit(1)
# mandatory arguments
train_data_spec = arguments['train_data']
valid_data_spec = arguments['valid_data']
extra_nnet_spec = arguments['extra_nnet_spec']
conv_nnet_spec = arguments['conv_nnet_spec']
nnet_spec = arguments['nnet_spec']
wdir = arguments['wdir']
# parse network configuration from arguments, and initialize data reading
cfg = NetworkConfig()
cfg.model_type = 'CNNV'
cfg.parse_config_cnn(arguments, '10:' + nnet_spec, conv_nnet_spec)
cfg.parse_config_extra(arguments, extra_nnet_spec)
cfg.init_data_reading(train_data_spec, valid_data_spec)
# parse pre-training options
# pre-training files and layer number (how many layers are set to the pre-training parameters)
ptr_layer_number = 0
ptr_file = ''
if arguments.has_key('ptr_file') and arguments.has_key('ptr_layer_number'):
ptr_file = arguments['ptr_file']
ptr_layer_number = int(arguments['ptr_layer_number'])
# check working dir to see whether it's resuming training
resume_training = False
if os.path.exists(wdir +
'/nnet.tmp') and os.path.exists(wdir +
'/training_state.tmp'):
for arg in required_arguments:
if arguments.has_key(arg) == False:
print "Error: the argument %s has to be specified" % (arg); exit(1)
# mandatory arguments
train_data_spec = arguments['train_data']
valid_data_spec = arguments['valid_data']
extra_nnet_spec = arguments['extra_nnet_spec']
conv_nnet_spec = arguments['conv_nnet_spec']
nnet_spec = arguments['nnet_spec']
wdir = arguments['wdir']
# parse network configuration from arguments, and initialize data reading
cfg = NetworkConfig(); cfg.model_type = 'CNNV'
cfg.parse_config_cnn(arguments, '10:' + nnet_spec, conv_nnet_spec)
cfg.parse_config_extra(arguments, extra_nnet_spec)
cfg.init_data_reading(train_data_spec, valid_data_spec)
# parse pre-training options
# pre-training files and layer number (how many layers are set to the pre-training parameters)
ptr_layer_number = 0; ptr_file = ''
if arguments.has_key('ptr_file') and arguments.has_key('ptr_layer_number'):
ptr_file = arguments['ptr_file']
ptr_layer_number = int(arguments['ptr_layer_number'])
# check working dir to see whether it's resuming training
resume_training = False
if os.path.exists(wdir + '/nnet.tmp') and os.path.exists(wdir + '/training_state.tmp'):
resume_training = True
cfg.lrate = _file2lrate(wdir + '/training_state.tmp')
log('> ... found nnet.tmp and training_state.tmp, now resume training from epoch ' + str(cfg.lrate.epoch))
