def _compute_pmf(gen_graph_distr):
	"""
	Compute the probability mass function (PMF) of graphs. It can be seen as a normalization between 0 and 1, where
	each count is converted into a probability.

	:gen_graph_distr: The distribution of generated graphs. It is a dictionary where, for each entry (key, value), the
		key is a graph (in graph6 format) and the value is the count of this graph. Make sure to generate enough graphs
		to get good results.
	:return: The probability mass function (PMF) of graphs. It is a dictionary where, for each entry (key, value), the
		key is a graph (in graph6 format) and the value is probability to get this graph.
	"""

	# Compute the sum of all counts.
	count_sum = sum(gen_graph_distr.values())

	# Compute the PMF.
	pmf = {graph: (count / count_sum) for graph, count in gen_graph_distr.items()}

	return pmf