mxnet基础到提高(35)-ndarray
2維數組,矩陣
import mxnet.ndarray as nd a=nd.array(((1,2),(3,4))) print(a)[[ 1. 2.]
[ 3. 4.]]
<NDArray 2x2 @cpu(0)>
隨機數
import mxnet.ndarray as nd a=nd.random.uniform(-10,10,(3,5))#-10到10之間,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)>
指定值填充數組
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)>
數組屬性
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’>
數組運算
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與numpy互相轉換
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)>
[[ 2. 2. 2. 2.]
[ 2. 2. 2. 2.]
[ 2. 2. 2. 2.]]
<NDArray 3x4 @cpu(0)>
總結
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