<｜begin▁of▁sentence｜>### Instruction:
As a fashion blogger, imagine you have been approached by a new fashion startup that wants to create a network graph to visualize the relationships between different fashion brands. They have provided you with a dict-of-dicts representation of the connections between three brands: 'A', 'B', and 'C'. 

Brand 'A' has a connection to brand 'B' with a weight of 1 and to brand 'C' with a weight of 2. Brand 'B' connects to brand 'C' with a weight of 3, and brand 'C' has a connection back to brand 'A' with a weight of 4. 

Your task is to use this data to create an undirected network graph that will help the startup visualize the relationships between these brands, with the edge weights represented as attributes. You can use the networkx library to assist you in building the graph and including the edge attributes.
### Response:
from igraph import Graph

# Define a dict-of-dicts structure to represent the edges and their attributes
edges = {'A': {'B': {'weight': 1}, 'C': {'weight': 2}},
          'B': {'C': {'weight': 3}},
          'C': {'A': {'weight': 4}}}

# Create a graph from the dict-of-dicts
# This will create an undirected graph with 'name' as the vertex_name_attr
graph = Graph.DictDict(edges, directed=False, vertex_name_attr='name')

# Print the created graph's summary
print(graph.summary())
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