print("Selected beamformers:",' '.join(beamformers).upper())
serializers.load_hdf5(args.model, model)
if args.gpu >= 0:
cuda.get_device(args.gpu).use()
model.to_gpu()
xp = np if args.gpu < 0 else cuda.cupy
chainer.no_backprop_mode()
stage = args.flist[:2]
scenario = args.flist.split('_')[-1]
# CHiME data handling
if scenario == 'simu':
flist = gen_flist_simu(args.chime_dir, stage)
elif scenario == 'real':
flist = gen_flist_real(args.chime_dir, stage)
else:
raise ValueError('Unknown flist {}'.format(args.flist))
for env in ['caf', 'bus', 'str', 'ped']:
for beamformer in beamformers:
mkdir_p(os.path.join(args.output_dir, beamformer,'{}05_{}_{}'.format(
stage, env, scenario
)))
t_io = 0
t_net = 0
t_beamform = 0
# Beamform loop
model = SimpleFWMaskEstimator()
else:
raise ValueError('Unknown model type. Possible are "BLSTM" and "FW"')
serializers.load_hdf5(args.model, model)
if args.gpu >= 0:
cuda.get_device(args.gpu).use()
model.to_gpu()
xp = np if args.gpu < 0 else cuda.cupy
stage = args.flist[:2]
scenario = args.flist.split('_')[-1]
# CHiME data handling
if scenario == 'simu':
flist = gen_flist_simu(args.chime_dir, stage)
elif scenario == 'real':
flist = gen_flist_real(args.chime_dir, stage)
else:
raise ValueError('Unknown flist {}'.format(args.flist))
for env in ['caf', 'bus', 'str', 'ped']:
mkdir_p(os.path.join(args.output_dir, '{}05_{}_{}'.format(
stage, env, scenario
)))
t_io = 0
t_net = 0
t_beamform = 0
# Beamform loop
for cur_line in tqdm(flist):
