Sure,
heres the code of printed tensors
def predict(img_path):
    PATH = './wytrenowaned.pth'
    img = Image.open(img_path)
    pil_to_tensor = transforms.ToTensor()(img).unsqueeze_(0)
    print(pil_to_tensor.shape)

And my Net code goes as follows:
class Net(nn.Module):
    def __init__(self):
        super(Net, self).__init__()
        self.conv1 = nn.Conv2d(3, 6, 5)
        self.pool = nn.MaxPool2d(2, 2)
        self.conv2 = nn.Conv2d(6, 16, 5)
        self.fc1 = nn.Linear(16 * 71 * 71, 120)
        self.fc2 = nn.Linear(120, 84)
        self.fc3 = nn.Linear(84, 10)

    def forward(self, x):
        x = self.pool(F.relu(self.conv1(x)))
        x = self.pool(F.relu(self.conv2(x)))
        x = x.view(x.size(0), 16 * 71 * 71)
        x = F.relu(self.fc1(x))
        x = F.relu(self.fc2(x))
        x = self.fc3(x)
        return x

i would like to point out that everything went smoothly while i was training and testing it on datasets created from my ImageFolder