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):