<｜begin▁of▁sentence｜>### Instruction:
As a civil rights attorney specializing in legal matters concerning civil rights, discrimination, equal protection, and human rights violations, you may encounter situations where you need to assess the influence of various entities within a network. For instance, imagine you're working on a case involving workplace discrimination. You have access to data representing the interactions among employees within the company, which is stored in a file named 'graph_data.gml'. To understand the significance of different individuals within this network, you're considering utilizing a measure called betweenness centrality.

Instead of manually assessing each individual's influence, you're exploring the possibility of using the betweenness function provided by the igraph API. This function can analyze the network and compute the betweenness centrality of each vertex, helping you identify key individuals who may play pivotal roles in perpetuating or combating discrimination within the workplace.
### Response:
from igraph import Graph
import igraph as ig

# Read the graph from a file
graph_path = 'graph_data.gml'
g = ig.read(graph_path)

# Compute the betweenness of all vertices
vertex_betweenness = g.betweenness()

# Print betweenness of vertices
for idx, b in enumerate(vertex_betweenness):
    print(f'Vertex {idx}: Betweenness = {b}')
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