The execution order of each module in an nn.Sequential container is the same order their forward methods will be called.
Here is a small example, which shows that the first case yields a dense output, while the second one zeroes out some output units:
# Case 1
model = nn.Sequential(
    nn.Dropout(0.5),
    nn.Linear(10, 10)
)

x = torch.randn(1, 10)
out = model(x)
print(out)

# Case 2
model = nn.Sequential(
    nn.Linear(10, 10),
    nn.Dropout(0.5)
)

x = torch.randn(1, 10)
out = model(x)
print(out)