<｜begin▁of▁sentence｜>### Instruction:
Given two MultiDiGraphs where the first graph has edges [('A', 'B', {'weight': 2}), ('A', 'C', {'weight': 3})] and the second graph has edges [('B', 'C', {'weight': 5}), ('C', 'A', {'weight': 7})], how can we create a unified view of the successor and predecessor adjacency dictionaries for node 'A' in the first graph, and how can we explore their combined edges and attributes?
### Response:
import networkx as nx

# Create two MultiDiGraphs
g1 = nx.MultiDiGraph()
g2 = nx.MultiDiGraph()

# Add some edges to the first graph
g1.add_edge('A', 'B', weight=2)
g1.add_edge('A', 'C', weight=3)

# Add some edges to the second graph
g2.add_edge('B', 'C', weight=5)
g2.add_edge('C', 'A', weight=7)

# Create UnionMultiInner representing the union of G.succ['A'] and G.pred['A']
union_inner = nx.classes.coreviews.UnionMultiInner(g1.succ['A'], g1.pred['A'])

# Access UnionMultiInner data
for nbr, edict in union_inner.items():
    for key, eattr in edict.items():
        print(f'Neighbor: {nbr}, Key: {key}, Attributes: {eattr}')
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