pytorch中tensor张量的创建
import torch
import numpy as np
print(torch.tensor([1,2,3]))
print(torch.tensor(np.arange(15).reshape(3,5)))
print(torch.empty([3,4]))
print(torch.ones([3,4]))
print(torch.zeros([3,4]))
#0-1之间的随机数
print(torch.rand([2,3]))
#3-10之间的随机整数
print(torch.randint(3,10,(2,2)))
#正态分布,均值为0,方差为1
print(torch.randn([3,4]))
D:\anaconda\python.exe C:/Users/liuxinyu/Desktop/pytorch_test/day1/tensor.py
tensor([1, 2, 3])
tensor([[ 0, 1, 2, 3, 4],
[ 5, 6, 7, 8, 9],
[10, 11, 12, 13, 14]], dtype=torch.int32)
tensor([[0., 0., 0., 0.],
[0., 0., 0., 0.],
[0., 0., 0., 0.]])
tensor([[1., 1., 1., 1.],
[1., 1., 1., 1.],
[1., 1., 1., 1.]])
tensor([[0., 0., 0., 0.],
[0., 0., 0., 0.],
[0., 0., 0., 0.]])
tensor([[0.5792, 0.9149, 0.3303],
[0.6756, 0.5236, 0.0648]])
tensor([[9, 3],
[4, 7]])
tensor([[ 1.2060, -0.8728, -0.6619, 1.2589],
[-0.8896, -0.1648, -0.0978, -0.8487],
[ 0.2621, 0.9406, 0.0079, 0.0284]])
Process finished with exit code 0
多思考也是一种努力,做出正确的分析和选择,因为我们的时间和精力都有限,所以把时间花在更有价值的地方。

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