
        Figure 4: Graphical representation of a residual skip connection. The middle node is like the main branch of a residual block, and the final node represents the sum of the input and output of the main branch.

Now, TorchVision’s get_graph_node_names function applies FX as described above, and in the process of doing so, tags each node with a human readable name. Let’s try this with our toy CNN model from the previous section:
model = CNN(3, 4, 10)
from torchvision.models.feature_extraction import get_graph_node_names
nodes, _ = get_graph_node_names(model)
print(nodes)

which will result in:
```python