raise ImportError ('This script can only be run, and can\'t be imported')
logger.info(" ".join(sys.argv))
arg_parser = argparse.ArgumentParser()
arg_parser.add_argument('--use-gpu', type = str)
arg_parser.add_argument('--sleep', type = int)
arg_parser.add_argument('config_file', type = str)
arg_parser.add_argument('model_file', type = str)
arg_parser.add_argument('prior_counts_file', type = str)
args = arg_parser.parse_args()
config = configparser.ConfigParser()
config.read(args.config_file)
feature_conf = section_config.parse(config.items('feature'))
nnet_conf = section_config.parse(config.items('nnet'))
optimizer_conf = section_config.parse(config.items('optimizer'))
srcdir = os.path.dirname(args.model_file)
input_dim = int(open(srcdir+'/input_dim').read())
output_dim = int(open(srcdir+'/output_dim').read())
max_length = feature_conf.get('max_length', None)
jitter_window = feature_conf.get('jitter_window', None)
splice = feature_conf['context_width']
# set gpu
logger.info("use-gpu: %s", str(args.use_gpu))
logger.info("initializing the graph")
'copy-transition-model', '--binary=false', gmm + '/final.mdl',
exp + '/final.mdl'
]).communicate()
# read config file
config = configparser.ConfigParser()
if os.path.isfile(exp + '/config'):
logger.info("Loading config file from original exp directory")
config_file = exp + '/config'
else:
logger.info("Copying config file to exp directory")
shutil.copyfile(config_file, exp + '/config')
config.read(config_file)
# parse config sections
nnet_conf = section_config.parse(config.items('nnet'))
nnet_train_conf = section_config.parse(config.items('nnet-train'))
optimizer_conf = section_config.parse(config.items('optimizer'))
scheduler_conf = section_config.parse(config.items('scheduler'))
feature_conf = section_config.parse(config.items('feature'))
nnet_proto_file = config.get('general', 'nnet_proto', fallback=None)
summary_dir = config.get('general', 'summary_dir', fallback=None)
summary_dir = exp + '/' + summary_dir if summary_dir is not None else None
# separate data into 10% cv and 90% training
Popen([
'utils/subset_data_dir_tr_cv.sh', '--cv-spk-percent', '10', data,
exp + '/tr90', exp + '/cv10'
]).communicate()
arg_parser.add_argument('--use-gpu', dest = 'use_gpu', action = 'store_true')
arg_parser.add_argument('--verbose', dest = 'verbose', action = 'store_true')
arg_parser.add_argument('--use-raw-data', dest = 'use_raw_data', action = 'store_true')
arg_parser.add_argument('--gpu-ids', type = str, default = '-1')
arg_parser.add_argument('data', type = str)
arg_parser.add_argument('model_file', type = str)
arg_parser.add_argument('wspecifier', type = str)
arg_parser.set_defaults(use_gpu = False, verbose = False, use_raw_data = False)
args = arg_parser.parse_args()
srcdir = os.path.dirname(args.model_file)
config = configparser.ConfigParser()
config.read(srcdir+'/config')
feature_conf = section_config.parse(config.items('feature'))
nnet_conf = section_config.parse(config.items('nnet'))
nnet_train_conf = section_config.parse(config.items('nnet-train'))
input_dim = int(open(srcdir+'/input_dim').read())
output_dim = parse_int_or_list(srcdir+'/output_dim')
embedding_index = int(open(srcdir+'/embedding_index').read())
splice = feature_conf['context_width']
# prepare feature pipeline
feat_type = feature_conf.get('feat_type', 'raw')
cmvn_type = feature_conf.get('cmvn_type', 'utt')
delta_opts = feature_conf.get('delta_opts', '')
# set gpu, this is used to load the graph successfully, not really for gpu
logger.info("use-gpu: %s", str(args.use_gpu))