I have a similar error.
RuntimeError: running_mean should contain 64 elements not 32
 in forward(self, x1)
31
32         x1 = self.conv1(x1)
—> 33         x1 = self.bn1(x1)
34         x1 = self.relu1(x1)
35         x1 = self.maxpool1(x1)
Initial 2 layers of my model.
class Net(nn.Module):
def init(self):
super(Net, self).init()
    self.conv1 = nn.Conv2d(in_channels=3,out_channels=64,kernel_size=(3,3),stride=(2,2),padding=(1,1))
    self.bn1 = nn.BatchNorm2d(num_features=64)
    self.relu1=nn.ReLU()
    self.maxpool1= nn.MaxPool2d(kernel_size=(3,3),stride=(1,1),padding=(1,1))
    
    self.conv2 = nn.Conv2d(in_channels=64,out_channels=64,kernel_size=(3,3),stride=(2,2),padding=(1,1))
    self.bn1 = nn.BatchNorm2d(num_features=64)
    self.relu1=nn.ReLU()
    self.maxpool1= nn.MaxPool2d(kernel_size=(3,3),stride=(1,1),padding=(1,1))