mxnet基础到提高(35)-ndarray

2维数组，矩阵

import mxnet.ndarray as nd
a=nd.array(((1,2),(3,4)))
print(a)

[[ 1. 2.]
[ 3. 4.]]
<NDArray 2x2 @cpu(0)>

随机数

import mxnet.ndarray as nd
a=nd.random.uniform(-10,10,(3,5))#-10到10之间，3*5大小
print(a)

[[ 0.97627068 1.85689163 4.30378723 6.88531494 2.05526733]
[ 7.15891266 0.89766407 6.94503403 -1.52690411 2.47127438]
[ 2.91788197 -2.31236553 -1.24825573 -4.04930782 7.83546066]]
<NDArray 3x5 @cpu(0)>

指定值填充数组

import mxnet.ndarray as nd
a=nd.full((3,4),0.0)
b=nd.full((3,4),1.0)
print(a)
print(b)

[[ 0. 0. 0. 0.]
[ 0. 0. 0. 0.]
[ 0. 0. 0. 0.]]
<NDArray 3x4 @cpu(0)>

[[ 1. 1. 1. 1.]
[ 1. 1. 1. 1.]
[ 1. 1. 1. 1.]]
<NDArray 3x4 @cpu(0)>

数组属性

import mxnet.ndarray as nd
a=nd.full((3,4),1.0)
print(a)
print(a.shape)
print(a.size)
print(a.dtype)

[[ 0. 0. 0. 0.]
[ 0. 0. 0. 0.]
[ 0. 0. 0. 0.]]
<NDArray 3x4 @cpu(0)>
(3, 4)
12
<class ‘numpy.float32’>

数组运算

import mxnet.ndarray as nd
a=nd.full((3,4),1.0)
b=nd.full((3,4),5.0)
print(a+b)
print(a-b)
print(a*b)
print(a/b)

[[ 6. 6. 6. 6.]
[ 6. 6. 6. 6.]
[ 6. 6. 6. 6.]]
<NDArray 3x4 @cpu(0)>

[[-4. -4. -4. -4.]
[-4. -4. -4. -4.]
[-4. -4. -4. -4.]]
<NDArray 3x4 @cpu(0)>

[[ 5. 5. 5. 5.]
[ 5. 5. 5. 5.]
[ 5. 5. 5. 5.]]
<NDArray 3x4 @cpu(0)>

[[ 0.2 0.2 0.2 0.2]
[ 0.2 0.2 0.2 0.2]
[ 0.2 0.2 0.2 0.2]]
<NDArray 3x4 @cpu(0)>

ndarray与numpy互相转换

import mxnet.ndarray as nd
a=nd.full((3,4),2.0)
c=a.asnumpy()#to numpy
print(c)
print(a)
d=nd.array(c)#to ndarray
print(d)

[[ 2. 2. 2. 2.]
[ 2. 2. 2. 2.]
[ 2. 2. 2. 2.]]

[[ 2. 2. 2. 2.]
[ 2. 2. 2. 2.]
[ 2. 2. 2. 2.]]
<NDArray 3x4 @cpu(0)>

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