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import mxnet as mx
a = mx.sym.Variable('a')
b = mx.sym.Variable('b')
c = a + b
(a, b, c)


    

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# elemental wise times
d = a * b  
# matrix multiplication
e = mx.sym.dot(a, b)   
# reshape
f = mx.sym.Reshape(d+e, shape=(1,4))  
# broadcast
g = mx.sym.broadcast_to(f, shape=(2,4))  
mx.viz.plot_network(symbol=g)


    

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%matplotlib inline
from __future__ import print_function
import os
import time
# set the number of threads you want to use before importing mxnet
os.environ['MXNET_CPU_WORKER_NTHREADS'] = '4'
import mxnet as mx
import numpy as np
import matplotlib.pyplot as plt


    

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# download example images
proxy = os.popen('cat /etc/profile | grep https_proxy | cut -f2 -d"="').read()[:-1]
os.popen('wget -e use_proxy=yes -e http_proxy={} http://data.mxnet.io/data/test_images.tar.gz'.format(proxy)).read()
os.popen('tar -xf test_images.tar.gz').read()


    

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# opencv
import cv2
N = 1000
tic = time.time()
for i in range(N):
    img = cv2.imread('test_images/ILSVRC2012_val_00000001.JPEG', flags=1)
    img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
print(N/(time.time()-tic), 'images decoded per second with opencv')
plt.imshow(img); plt.show()


    

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