Given a compiled set of $n$ tasks,

represented by an array, task, and a

neural network system with $m$ nodes,

each processes tasks efficiently. For

optimal performance, tasks must be

distributed evenly across these nodes,

i$.$e$.,$ all nodes should serve the same

number of tasks. Each task assigned to a

single node must be different.

Maximize the number of tasks

completed by allocating tasks effectively

within the neural network and return

the maximum number of tasks

completed using the distributed neural

network system.

Note: All nodes must be assigned an

equal number of tasks.

Example

$n=7$