DeepSZ/extract_weights_and_compression.py at master · szcompressor/DeepSZ · GitHub

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import numpy as np
import matplotlib as mpl
mpl.use('Agg')
import matplotlib.pyplot as plt
import caffe
plt.rcParams['figure.figsize'] = (15, 15)
import os

caffe.set_mode_cpu()
model_def = './deploy.prototxt'
model_weights = './caffenet_pruned.caffemodel'

net = caffe.Net(model_def,      # defines the structure of the model
                model_weights,  # contains the trained weights
                caffe.TEST)

print ("Initialization done!")
print ("Start converting weights into sparse representation ...")

folder = os.path.exists("./data")
if not folder:
    os.makedirs("./data")

feat = net.params['fc6'][0].data
feat = np.reshape(feat, 4096*9216)

k = len(feat)
data = np.zeros(k, dtype='float32')
index = np.zeros(k, dtype='uint8')

k = 0
kk = 0
bit = 0

for i in range(len(feat)):
    if (bit == 255) and (feat[i] == 0):
        index[k] = 0
        k = k+1
        bit = 0
    if (feat[i] != 0):
        data[kk] = feat[i]
        index[k] = bit
        k = k+1
        kk = kk+1
        bit = 0
    bit = bit + 1

a = np.zeros(kk, dtype='float32')
b = np.zeros(k, dtype='uint8')
for i in range(kk):
    a[i] = data[i]
for i in range(k):
    b[i] = index[i]

a.astype('float32').tofile('./data/fc6-data-o.dat')
b.astype('uint8').tofile('./data/fc6-index-o.dat')

print ("fc6 transferred")
print ("start compressing and decompressing ...")

bash_line = "python ./bash_script.py " + str(kk) + " 6"
os.system(bash_line)
bash_line = "source ./SZ_compress_script/fc6_script.sh"
os.system(bash_line)

print ("fc6 decompression finished")

feat = net.params['fc7'][0].data
feat = np.reshape(feat, 4096*4096)

k = len(feat)
data = np.zeros(k, dtype='float32')
index = np.zeros(k, dtype='uint8')

k = 0
kk = 0
bit = 0

for i in range(len(feat)):
    if (bit == 255) and (feat[i] == 0):
        index[k] = 0
        k = k+1
        bit = 0
    if (feat[i] != 0):
        data[kk] = feat[i]
        index[k] = bit
        k = k+1
        kk = kk+1
        bit = 0
    bit = bit + 1

a = np.zeros(kk, dtype='float32')
b = np.zeros(k, dtype='uint8')
for i in range(kk):
    a[i] = data[i]
for i in range(k):
    b[i] = index[i]

a.astype('float32').tofile('./data/fc7-data-o.dat')
b.astype('uint8').tofile('./data/fc7-index-o.dat')

print ("fc7 transferred")
print ("start compressing and decompressing ...")

bash_line = "python ./bash_script.py " + str(kk) + " 7"
os.system(bash_line)
bash_line = "source ./SZ_compress_script/fc7_script.sh"
os.system(bash_line)

print ("fc7 decompression finished")


feat = net.params['fc8'][0].data
feat = np.reshape(feat, 1000*4096)

k = len(feat)
data = np.zeros(k, dtype='float32')
index = np.zeros(k, dtype='uint8')

k = 0
kk = 0
bit = 0

for i in range(len(feat)):
    if (bit == 255) and (feat[i] == 0):
        index[k] = 0
        k = k+1
        bit = 0
    if (feat[i] != 0):
        data[kk] = feat[i]
        index[k] = bit
        k = k+1
        kk = kk+1
        bit = 0
    bit = bit + 1

a = np.zeros(kk, dtype='float32')
b = np.zeros(k, dtype='uint8')
for i in range(kk):
    a[i] = data[i]
for i in range(k):
    b[i] = index[i]

a.astype('float32').tofile('./data/fc8-data-o.dat')
b.astype('uint8').tofile('./data/fc8-index-o.dat')

print ("fc8 transferred")
print ("start compressing and decompressing ...")

bash_line = "python ./bash_script.py " + str(kk) + " 8"
os.system(bash_line)
bash_line = "source ./SZ_compress_script/fc8_script.sh"
os.system(bash_line)

print ("fc8 decompression finished")