In the JuMP code below, I want to count the number of occurrences of each possible integer in the variable matrix M. s is defined to be a Kx1 variable vector equal to M[:]. Is there any difference in efficiency between

@constraint(model, [i=1:v-1], [n[i]; s] in MOI.CountBelongs(1+K, Set([i])))

versus

@constraint(model, [i=1:v-1], [n[i]; M[:]] in MOI.CountBelongs(1+K, Set([i])))

using JuMP

a = 4

b = 3

K = a*b

v = 16

model = Model()

@variable(model, 1 <= M[1:a,1:b] <= v-1, Int)

@variable(model, 1 <= s[1:K] <= v-1, Int)

@constraint(model, s .== M[:])

@variable(model, 0 <= n[1:v-1] <= K, Int)

#
n[i] is the count of how many `i`

are in s for 1 <= i <= v-1.

@constraint(model, [i=1:v-1], [n[i]; s] in MOI.CountBelongs(1+K, Set([i])))

vs

@constraint(model, [i=1:v-1], [n[i]; M[:]] in MOI.CountBelongs(1+K, Set([i])))