<｜begin▁of▁sentence｜>### Instruction:
As a speech pathologist, I often work with individuals of all ages to assess and treat speech, language, or communication disorders. Sometimes, I need to convert complex data into a more simplified format to better understand and communicate the information. For example, if I have a conversation between three people and want to analyze the overall communication patterns, I might need to condense the multiple interactions between the same individuals and consider the cumulative impact of those interactions. This may involve identifying recurring topics and understanding the overall flow of the conversation. Similarly, in the context of directed graphs with multiple edges and corresponding weights, the process of converting the graph to an undirected format while collapsing multiple edges and summing their weights requires careful consideration and can be achieved using the `to_undirected` function in the igraph library.
### Response:
import igraph as ig

# Create a directed graph with multiple edges
g = ig.Graph(directed=True)
g.add_vertices(3)
g.add_edges([(0, 1), (1, 0), (0, 1)])
g.es['weight'] = [1, 2, 3]

# Convert to undirected graph by collapsing multiple edges
g_undirected = g.to_undirected(mode='collapse', combine_edges='sum')

# Print edge list with weights
print(g_undirected.get_edgelist(), g_undirected.es['weight'])
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