I would get the error
RuntimeError: Expected tensor for argument #1 'input' to have the same dimension as tensor for 'result'; but 4 does not equal 2 (while checking arguments for cudnn_convolution)
If I run the code below. Quick googling returns various issues that cause this. I assume Pytorch doesn’t like the 9 in channels and 64 out channels?
import torch
import torch.nn as nn

real = torch.randn([32, 9, 32, 32])

class options():
    def __init__(self):
        self.ndf = 64

opt = options()    

netd = nn.Sequential(
            
            nn.Conv2d(9,opt.ndf,4,2,1,bias=False),
            nn.LeakyReLU(0.2,inplace=True),
            
            nn.Conv2d(opt.ndf,opt.ndf*2,4,2,1,bias=False),
            nn.BatchNorm2d(opt.ndf*2),
            nn.LeakyReLU(0.2,inplace=True),
            
            nn.Conv2d(opt.ndf*2,opt.ndf*4,4,2,1,bias=False),
            nn.BatchNorm2d(opt.ndf*4),
            nn.LeakyReLU(0.2,inplace=True),
            
            nn.Conv2d(opt.ndf*4,opt.ndf*8,4,2,1,bias=False),
            nn.BatchNorm2d(opt.ndf*8),
            nn.LeakyReLU(0.2,inplace=True),
            
            nn.Conv2d(opt.ndf*8,1,4,1,0,bias=False),
            
        )

netd.cuda()

test = netd(real)