import torch
from torch.autograd import Variable
import numpy as np
'''
pytorch中Variable与torch.Tensor类型的相互转换
'''
 
# 1.torch.Tensor转换成Variablea=torch.randn((5,3))
b=Variable(a)
print('a',a.type(),a.shape)
print('b',type(b),b.shape)
 
# 2.Variable转换成torch.Tensor
c=b.data#通过 Variable.data 方法相当于将Variable中的torch.tensor 取出来
print('c',c.type(),c.shape)
 
'''
torch.tensor与numpy之间的相互转换
'''
# 3.torch.tensor转换成numpy
d=c.numpy()
# 4.numpy转换成torch.tensor
e=torch.from_numpy(d)
print('d',type(d))
print('e',type(e))
 
'''
numpy和list之间的相互转换  注意这种转换只支持one-dimension array
'''
# 5.numpy转换成list
f1=d.tolist()
f2=list(d)
# 6.list转换成numpy
g=np.asarray(f2)
print('f1',type(f1))
print('f2',type(f2))
print('g',type(g))
'''
a torch.FloatTensor torch.Size([5, 3])
b <class 'torch.Tensor'> torch.Size([5, 3])
c torch.FloatTensor torch.Size([5, 3])
d <class 'numpy.ndarray'>
e <class 'torch.Tensor'>
f1 <class 'list'>
f2 <class 'list'>
g <class 'numpy.ndarray'>
'''