#!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Fri Aug 10 16:13:29 2018

@author: myhaspl
"""
from mxnet import nd
x1=nd.array(((1,2,3),(5,6,7)))
x2=nd.array(((10,20,30),(50,60,70)))
y1=x1+x2
y2=x1*x2
print y1
print y2
print nd.ones((2,3))
print nd.random.uniform(-1,1,(2,3))
print nd.full((2,3), 2.0)
print (x1.shape, x1.size, x1.dtype)

the NDArray, MXNets primary tool for storing and transforming data. I

输出：

[[11. 22. 33.]
 [55. 66. 77.]]
<NDArray 2x3 @cpu(0)>

[[ 10.  40.  90.]
 [250. 360. 490.]]
<NDArray 2x3 @cpu(0)>

[[1. 1. 1.]
 [1. 1. 1.]]
<NDArray 2x3 @cpu(0)>

[[0.09762704 0.18568921 0.43037868]
 [0.6885315  0.20552671 0.71589124]]
<NDArray 2x3 @cpu(0)>

[[2. 2. 2.]
 [2. 2. 2.]]
<NDArray 2x3 @cpu(0)>
((2L, 3L), 6L, <type 'numpy.float32'>)

#!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Fri Aug 10 16:13:29 2018

@author: myhaspl
"""
from mxnet import nd
x1=nd.array(((1,2,3),(5,6,7)))
x2=nd.array(((10,20,30),(50,60,70)))
print x1
print x1.T
print nd.dot(x1,x2.T)
print x1[:,1]
print x1[0,:]
print x2[0,2]
x1[:,2]=888
print x1

[[1. 2. 3.]
 [5. 6. 7.]]
<NDArray 2x3 @cpu(0)>

[[1. 5.]
 [2. 6.]
 [3. 7.]]
<NDArray 3x2 @cpu(0)>

[[ 140.  380.]
 [ 380. 1100.]]
<NDArray 2x2 @cpu(0)>

[2. 6.]
<NDArray 2 @cpu(0)>

[1. 2. 3.]
<NDArray 3 @cpu(0)>

[30.]
<NDArray 1 @cpu(0)>

[[  1.   2. 888.]
 [  5.   6. 888.]]
<NDArray 2x3 @cpu(0)>

#!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Fri Aug 10 16:13:29 2018

@author: myhaspl
"""
from mxnet import nd
x1=nd.array(((1,2,3),(5,6,7)))
x2=nd.array(((10,20,30),(50,60,70)))
a = x1.asnumpy()
print a
print nd.array(a)

[[1. 2. 3.]
 [5. 6. 7.]]

[[1. 2. 3.]
 [5. 6. 7.]]
<NDArray 2x3 @cpu(0)>