elif level == "ERROR":
logger.setLevel(logging.ERROR)
else:
logger.setLevel(logging.WARNING)
def runNet(modelConfig):
nnetType = modelConfig["nnetType"]
logger.info("Loading Other Configuration for %s", nnetType)
if nnetType == "CNN":
from pythonDnn.run.run_CNN import runCNN as runModel
elif nnetType == "CNN3D":
from pythonDnn.run.run_CNN3d import runCNN3D as runModel
elif nnetType == "RBM":
from pythonDnn.run.run_DBN import runRBM as runModel
elif nnetType == "SDA":
from pythonDnn.run.run_SDA import runSdA as runModel
elif nnetType == "DNN":
from pythonDnn.run.run_DNN import runDNN as runModel
else:
logger.error("Unknown nnet Type")
return 1
runModel(modelConfig)
if __name__ == "__main__":
setLogger()
modelConfig = load_model(sys.argv[1])
setLoggerLevel(modelConfig)
runNet(modelConfig)
train_sets = read_dataset(data_spec['training'])
preTraining(dbn, train_sets, model_config['pretrain_params'])
del train_sets
########################
# FINETUNING THE MODEL #
########################
if model_config['processes']['finetuning']:
fineTunning(dbn, model_config, data_spec)
########################
# TESTING THE MODEL #
########################
if model_config['processes']['testing']:
testing(dbn, data_spec)
##########################
# Export Features ##
##########################
if model_config['processes']['export_data']:
exportFeatures(dbn, model_config, data_spec)
logger.info('Saving model to ' + str(model_config['output_file']) + '....')
dbn.save(filename=model_config['output_file'])
logger.info('Saved model to ' + str(model_config['output_file']))
if __name__ == '__main__':
import sys
setLogger()
runRBM(sys.argv[1])
########################
# FINETUNING THE MODEL #
########################
if model_config['processes']['finetuning']:
fineTunning(dnn,model_config,data_spec)
########################
# TESTING THE MODEL #
########################
if model_config['processes']['testing']:
testing(dnn,data_spec)
##########################
## Export Features ##
##########################
if model_config['processes']['export_data']:
exportFeatures(dnn,model_config,data_spec)
logger.info('Saving model to ' + str(model_config['output_file']) + '....')
dnn.save(filename=model_config['output_file'])
logger.info('Saved model to ' + str(model_config['output_file']))
if __name__ == '__main__':
import sys
setLogger(level="INFO");
logger.info('Stating....');
runDNN(sys.argv[1]);
sys.exit(0)
train_sets = read_dataset(data_spec['training'])
preTraining(dbn,train_sets,model_config['pretrain_params'])
del train_sets;
########################
# FINETUNING THE MODEL #
########################
if model_config['processes']['finetuning']:
fineTunning(dbn,model_config,data_spec)
########################
# TESTING THE MODEL #
########################
if model_config['processes']['testing']:
testing(dbn,data_spec)
##########################
# Export Features ##
##########################
if model_config['processes']['export_data']:
exportFeatures(dbn,model_config,data_spec)
logger.info('Saving model to ' + str(model_config['output_file']) + '....')
dbn.save(filename=model_config['output_file'])
logger.info('Saved model to ' + str(model_config['output_file']))
if __name__ == '__main__':
import sys
setLogger();
runRBM(sys.argv[1])
elif level == "ERROR":
logger.setLevel(logging.ERROR)
else:
logger.setLevel(logging.WARNING)
def runNet(modelConfig):
nnetType = modelConfig ['nnetType']
logger.info("Loading Other Configuration for %s",nnetType);
if nnetType == 'CNN':
from pythonDnn.run.run_CNN import runCNN as runModel
elif nnetType == 'CNN3D':
from pythonDnn.run.run_CNN3d import runCNN3D as runModel
elif nnetType == 'RBM':
from pythonDnn.run.run_DBN import runRBM as runModel
elif nnetType == 'SDA':
from pythonDnn.run.run_SDA import runSdA as runModel
elif nnetType == 'DNN':
from pythonDnn.run.run_DNN import runDNN as runModel
else :
logger.error('Unknown nnet Type')
return 1
runModel(modelConfig)
if __name__ == '__main__':
setLogger();
modelConfig = load_model(sys.argv[1])
setLoggerLevel(modelConfig)
runNet(modelConfig)