Your conv_seqn outputs the desired shape for me:
conv_seqn = nn.Sequential(
nn.Conv2d(in_channels=3, out_channels=32, kernel_size=3, padding=1),
nn.BatchNorm2d(32),
nn.ReLU(inplace=True),
nn.MaxPool2d(kernel_size=2, stride=2),
nn.Conv2d(in_channels=32, out_channels=64, kernel_size=3, padding=1),
nn.ReLU(inplace=True),
nn.MaxPool2d(kernel_size=4, stride=4),
nn.Conv2d(in_channels=64, out_channels=128, kernel_size=3, padding=1),
nn.ReLU(inplace=True),
nn.MaxPool2d(kernel_size=4, stride=4),
)

x = torch.randn(1, 3, 3840, 1920)
out = conv_seqn(x)
print(out.shape)