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
