示例#1
0
def input_value_classification_deep_l1_training():
    logger = logging_daily.logging_daily(
        resource_filename('deepbiome', 'tests/data/log_info.yaml'))
    logger.reset_logging()
    log = logger.get_logging()
    log.setLevel(logging_daily.logging.INFO)

    config_data = configuration.Configurator(
        resource_filename('deepbiome',
                          'tests/data/classification_deep_l1_path_info.cfg'),
        log)
    config_data.set_config_map(config_data.get_section_map())
    config_data.print_config_map()

    config_network = configuration.Configurator(
        resource_filename(
            'deepbiome', 'tests/data/classification_deep_l1_network_info.cfg'),
        log)
    config_network.set_config_map(config_network.get_section_map())
    config_network.print_config_map()

    path_info = config_data.get_config_map()
    network_info = config_network.get_config_map()

    for k, v in path_info['data_info'].items():
        if 'data' in v:
            resource_filename('deepbiome', 'tests/%s' % v)
            path_info['data_info'][k] = resource_filename(
                'deepbiome', 'tests/%s' % v)
    return log, network_info, path_info
示例#2
0
    workers = int(argdict['workers'][0])
except:
    workers = 1
try:
    use_multiprocessing = argdict['use_multiprocessing'][0] == 'True'
except:
    use_multiprocessing = False

# Logger ###########################################################
logger = logging_daily.logging_daily(argdict['log_info'][0])
logger.reset_logging()
log = logger.get_logging()
log.setLevel(logging_daily.logging.INFO)

log.info('Argument input')
for argname, arg in argdict.items():
    log.info('    {}:{}'.format(argname, arg))

# Configuration ####################################################
config_data = configuration.Configurator(argdict['path_info'][0], log)
config_data.set_config_map(config_data.get_section_map())
config_data.print_config_map()

config_network = configuration.Configurator(argdict['network_info'][0], log)
config_network.set_config_map(config_network.get_section_map())
config_network.print_config_map()

path_info = config_data.get_config_map()
network_info = config_network.get_config_map()
test_evaluation, train_evaluation, network = deepbiome.deepbiome_train(
    log, network_info, path_info)  #, number_of_fold=100)