I just started with PyTorch and tried working my way through the tutorials.
When I run the standard neural_networks_tutorial.py
I get the following error:
Traceback (most recent call last):
File "src/pytorch_tests/neural_networks_tutorial.py", line 98, in <module>
out = net(input)
File "/home/ssudholt/checkouts/pytorch-tests/env/local/lib/python2.7/site-packages/torch/nn/modules/module.py", line 206, in __call__
result = self.forward(*input, **kwargs)
File "src/pytorch_tests/neural_networks_tutorial.py", line 61, in forward
x = F.max_pool2d(F.relu(self.conv1(x)), (2, 2))
File "/home/ssudholt/checkouts/pytorch-tests/env/local/lib/python2.7/site-packages/torch/nn/modules/module.py", line 206, in __call__
result = self.forward(*input, **kwargs)
File "/home/ssudholt/checkouts/pytorch-tests/env/local/lib/python2.7/site-packages/torch/nn/modules/conv.py", line 237, in forward
self.padding, self.dilation, self.groups)
File "/home/ssudholt/checkouts/pytorch-tests/env/local/lib/python2.7/site-packages/torch/nn/functional.py", line 40, in conv2d
return f(input, weight, bias)
TypeError: argument 0 is not a Variable
I ran the tutorial without any modifications:
import torch
from torch.autograd import Variable
import torch.nn as nn
import torch.nn.functional as F
class Net(nn.Module):
def __init__(self):
super(Net, self).__init__()
# 1 input image channel, 6 output channels, 5x5 square convolution
# kernel
self.conv1 = nn.Conv2d(1, 6, 5)
self.conv2 = nn.Conv2d(6, 16, 5)
# an affine operation: y = Wx + b
self.fc1 = nn.Linear(16 * 5 * 5, 120)
self.fc2 = nn.Linear(120, 84)
self.fc3 = nn.Linear(84, 10)
def forward(self, x):
# Max pooling over a (2, 2) window
x = F.max_pool2d(F.relu(self.conv1(x)), (2, 2))
# If the size is a square you can only specify a single number
x = F.max_pool2d(F.relu(self.conv2(x)), 2)
x = x.view(-1, self.num_flat_features(x))
x = F.relu(self.fc1(x))
x = F.relu(self.fc2(x))
x = self.fc3(x)
return x
def num_flat_features(self, x):
size = x.size()[1:] # all dimensions except the batch dimension
num_features = 1
for s in size:
num_features *= s
return num_features
net = Net()
net
print(net)
input = Variable(torch.randn(1, 1, 32, 32))
out = net(input)
print(out)
PyTorch was installed in a clean virtualenv through pip (version 0.1.12_2).
Google did non know anything about this error so I was hoping that maybe someone here can point me in the right direction.