input_space = dnn_model.get_input_space() batch = input_space.make_theano_batch() fprop = theano.function([batch], dnn_model.fprop(batch)) # load aux model aux_model = joblib.load(args.aux_model) L = os.path.splitext(os.path.split(args.aux_model)[-1])[0].split('_L')[-1] if L == 'All': which_layers = [1, 2, 3] else: which_layers = [int(L)] # fft params nfft = 2 * (input_space.dim - 1) nhop = nfft // 2 win = winfunc(1024) # design lowpass filter. b, a = sp.signal.butter(4, cut_freq / (22050. / 2.)) flist = glob.glob(args.in_path + '*.wav') dnn_file = open( os.path.join(args.out_path, stripf(args.dnn_model) + '.adversaries.txt'), 'w') dnn_file_filt = open( os.path.join(args.out_path, stripf(args.dnn_model) + '.adversaries.filtered.txt'), 'w') aux_file = open( os.path.join(args.out_path,
input_space = dnn_model.get_input_space() batch = input_space.make_theano_batch() fprop = theano.function([batch], dnn_model.fprop(batch)) # load aux model aux_model = joblib.load(args.aux_model) L = os.path.splitext(os.path.split(args.aux_model)[-1])[0].split('_L')[-1] if L=='All': which_layers = [1,2,3] else: which_layers = [int(L)] # fft params nfft = 2*(input_space.dim-1) nhop = nfft//2 win = winfunc(1024) # design lowpass filter. b,a = sp.signal.butter(4, cut_freq/(22050./2.)) flist = glob.glob(args.in_path +'*.wav') dnn_file = open(os.path.join(args.out_path, stripf(args.dnn_model) + '.adversaries.txt'), 'w') dnn_file_filt = open(os.path.join(args.out_path, stripf(args.dnn_model) + '.adversaries.filtered.txt'), 'w') aux_file = open(os.path.join(args.out_path, stripf(args.aux_model) + '.adversaries.txt'), 'w') aux_file_filt = open(os.path.join(args.out_path, stripf(args.aux_model) + '.adversaries.filtered.txt'), 'w') for f in flist: fname = stripf(f) # load audio file
# load aux model if args.aux_model: aux_model = joblib.load(args.aux_model) L = os.path.splitext(os.path.split(args.aux_model)[-1])[0].split('_L')[-1] if L=='All': which_layers = [1,2,3] else: which_layers = [int(L)] aux_file = open(os.path.join(args.out_path, stripf(args.aux_model) + '.adversaries.txt'), 'w') dnn_file = open(os.path.join(args.out_path, stripf(args.dnn_model) + '.adversaries.txt'), 'w') # fft params nfft = 2*(dim-1) nhop = nfft//2 win = winfunc(2048) flist = glob.glob(os.path.join(args.in_path, '*')) for f in flist: fname = stripf(f) if f.endswith('.wav'): read_fun = audiolab.wavread elif f.endswith('.au'): read_fun = audiolab.auread elif f.endswith('.mp3'): read_fun = read_mp3 else: continue