What is the Mutual Information for one instance?

I'm computing mutual information for several features where one of my datasets has one instance. One instance is because of a specific filtering criterion I used. I'm using sklearn.feature_selection.mutual_info_classif¶ to calculate MI. I am getting an ValueError due to this one instance. Anyway, I wanted to quantify this case MI. Therefore I was looking for the definition of MI and searching for ways to quantify this specific case. Is it 0 ? - meaning just one feature value and label, no information content? How do we quantify this specific situation? Any suggestions are appreciated. Example: X = array([[7., 7., 0., 0., 1., 0., 2., 1., 0.]]) #set of feature values Y = array([2.]) #label mi_scores = mutual_info_classif(X, Y,random_state=0) Something like the above. Then I'm getting ValueError: Found array with 0 sample(s) (shape=(0, 1)) while a minimum of 1 is required.