<｜begin▁of▁sentence｜>### Instruction:
As a corporate trainer, perhaps you're working with a team of employees who are implementing a network analysis tool to better understand the connections within their organization. They have a graph data file called 'graph_data.gml' that contains the relationships between employees and teams. They are interested in obtaining the sparse adjacency matrix using the `get_adjacency_sparse` function in their network analysis tool without specifying an edge attribute. This task will allow them to analyze the network structure more effectively and gain valuable insights into the connections within the organization.
### Response:
import igraph as ig
from scipy.sparse import csr_matrix

# Load a graph
filename = 'graph_data.gml'
g = ig.Graph.Read_GML(filename)

# Get the sparse adjacency matrix of the graph
# If an edge attribute is needed, replace None with the attribute name (e.g., 'weight')
adj_matrix_sparse: csr_matrix = g.get_adjacency_sparse(attribute=None)

# Use the matrix for further computations
print(adj_matrix_sparse)
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