In [4]:

    

import torch
import torchvision
import torch.nn as nn
import numpy as np
import torch.utils.data as data
import torchvision.transforms as transforms
import torchvision.datasets as dsets
from torch.autograd import Variable


    

In [7]:

    

# Tensorを作成
# Variableで囲んでrequires_grad=Trueにすると自動微分で勾配を求められる
x = Variable(torch.Tensor([1]), requires_grad=True)
w = Variable(torch.Tensor([2]), requires_grad=True)
b = Variable(torch.Tensor([3]), requires_grad=True)

# 計算グラフ
y = w * x + b


    

In [11]:

    

y


    

    
Out[11]:





Variable containing:
 5
[torch.FloatTensor of size 1]

In [12]:

    

y.backward()


    

In [13]:

    

print(x.grad)  # dy/dx = w = 2


    

    




Variable containing:
 2
[torch.FloatTensor of size 1]

In [14]:

    

print(w.grad)  # dy/dw = x = 1


    

    




Variable containing:
 1
[torch.FloatTensor of size 1]

In [15]:

    

print(b.grad)  # dy/db = 1


    

    




Variable containing:
 1
[torch.FloatTensor of size 1]

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