For example, you can test with this code snippet.
import torch
from torch import nn
from torch.nn.utils import spectral_norm

x = torch.rand(size=(1, 3, 4, 4))
My_Conv = nn.Conv2d(in_channels=3, out_channels=16, kernel_size=3, stride=1, padding=1)
print(My_Conv(x).shape) # works

My_Conv_with_spectral_norm = spectral_norm(nn.Conv2d(in_channels=3, out_channels=16, kernel_size=3, stride=1, padding=1))
print(My_Conv_with_spectral_norm(x).shape) # works

My_Conv_sequential = nn.Sequential(
    nn.Conv2d(in_channels=3, out_channels=16, kernel_size=3, stride=1, padding=1)
)
print(My_Conv_sequential(x).shape) # works

My_Conv_sequential_spectral_norm = spectral_norm(
    nn.Sequential(
        nn.Conv2d(in_channels=3, out_channels=16, kernel_size=3, stride=1, padding=1)
    )
)
print(My_Conv_sequential_spectral_norm(x).shape) # will not work