<｜begin▁of▁sentence｜>### Instruction:
Imagine you are the cinematographer for a new documentary series, visualizing complex networks in real life. Your current episode focuses on the intricacies of city transportation planning, where different routes have variable costs and efficiencies associated with them.

Your task is to create a visual representation of a transportation network that consists of five destinations. Think of destinations 1 through 4 as already connected in a single, linear route, much like a quiet backroad. However, destination 5 is set apart, an isolated scenic overlook awaiting visitors. 

To bring this network together, you're provided with a list of potential new routes that can be established, each with its own cost to build, akin to the production costs of including additional footage in your documentary. The available connections with their respective costs are as follows: a route from 1 to 5 at a cost of 11, from 2 to 5 at a cost of 10, an existing route between 4 and 3 just needs a touch-up at a cost of 1, and a rather expensive option that spans from 4 to 5 at a cost of 51.

Your challenge is to determine which of these available routes should be added to ensure that the transportation network is robust enough to remain connected even if any one route were to be closed for repairs. This is akin to planning for extra footage to ensure your documentary can still tell a coherent story even if one segment doesn’t make the final cut due to unforeseen circumstances. Your goal is to achieve this without overshooting the allocated budget or disrupting the existing flow of traffic. How would you go about selecting the new routes to incorporate, thereby making the network '2-edge-connected'?
### Response:
import networkx as nx

G = nx.path_graph(4)
G.add_node(5)
avail = {(1, 5): 11, (2, 5): 10, (4, 3): 1, (4, 5): 51}
augment_edges = nx.k_edge_augmentation(G, k=2, avail=avail)
print(sorted(augment_edges))
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