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T_keys = list()
for i in range(max_dim):
T_keys.append(np.random.rand(i+1,1))
one way encryption transformation
M_keys = list()
for i in range(max_dim):
M_keys.append(innerProdClient(T_keys[i],l))
M_onehot = list()
for h in range(max_dim):
i = h+1
buffered_eyes = list()
for row in np.eye(i+1):
buffer = np.ones(i+1)
buffer[0:i+1] = row
buffered_eyes.append((M_keys[i-1].T * buffer).T)
M_onehot.append(buffered_eyes)
c_ones = list()
for i in range(max_dim):
c_ones.append(encrypt(T_keys[i],np.ones(i+1), w, l).astype('int'))
v_onehot = list()
onehot = list()
for i in range(max_dim):
eyes = list()
eyes_txt = list()
for eye in np.eye(i+1):
eyes_txt.append(eye)
eyes.append(one_way_encrypt_vector(eye,scaling_factor))
v_onehot.append(eyes)
onehot.append(eyes_txt)
HAPPENS ON SECURE SERVER
l = 100
w = 2 ** 25
aBound = 10
tBound = 10
eBound = 10
max_dim = 16
scaling_factor = 1000
keys
T_keys = list()
for i in range(max_dim):
T_keys.append(np.random.rand(i+1,1))
one way encryption transformation
M_keys = list()
for i in range(max_dim):
M_keys.append(innerProdClient(T_keys[i],l))
M_onehot = list()
for h in range(max_dim):
i = h+1
buffered_eyes = list()
for row in np.eye(i+1):
buffer = np.ones(i+1)
buffer[0:i+1] = row
buffered_eyes.append((M_keys[i-1].T * buffer).T)
M_onehot.append(buffered_eyes)
c_ones = list()
for i in range(max_dim):
c_ones.append(encrypt(T_keys[i],np.ones(i+1), w, l).astype('int'))
v_onehot = list()
onehot = list()
for i in range(max_dim):
eyes = list()
eyes_txt = list()
for eye in np.eye(i+1):
eyes_txt.append(eye)
eyes.append(one_way_encrypt_vector(eye,scaling_factor))
v_onehot.append(eyes)
onehot.append(eyes_txt)
H_sigmoid_txt = np.zeros((5,5))
H_sigmoid_txt[0][0] = 0.5
H_sigmoid_txt[0][1] = 0.25
H_sigmoid_txt[0][2] = -1/48.0
H_sigmoid_txt[0][3] = 1/480.0
H_sigmoid_txt[0][4] = -17/80640.0
H_sigmoid = list()
for row in H_sigmoid_txt:
H_sigmoid.append(one_way_encrypt_vector(row))
OverflowError Traceback (most recent call last)
in
43 for eye in np.eye(i+1):
44 eyes_txt.append(eye)
---> 45 eyes.append(one_way_encrypt_vector(eye,scaling_factor))
46 v_onehot.append(eyes)
47 onehot.append(eyes_txt)
in one_way_encrypt_vector(vector, scaling_factor)
95 M_temp = (M_keys[vec_len-2].Tpadded_vectorscaling_factor / (vec_len-1)).T
96 e_vector = innerProd(c_ones[vec_len-2],c_ones[vec_len-2],M_temp,l)
---> 97 return e_vector.astype('int')
98
99 def load_linear_transformation(syn0_text,scaling_factor = 1000):
OverflowError: Python int too large to convert to C long
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