Return values and async semantics

[wlruys]

This does not give the expected result.

def run(function: Callable[[], Optional[TaskSpace]]):
    assert callable(function), "The function argument must be callable."

    # Start the Parla runtime.
    with Parla():
        # Create a top-level task to kick off the computation
        @spawn(placement=cpu, vcus=0)
        async def top_level_task():
            # Note that unless function returns a TaskSpace, this will NOT be blocking.
            # If you want to wait on the completion of the tasks launched by function, you must return a TaskSpace that contains their terminal tasks.
            await function()

    # Runtime exists at the end of the context_manager
    # All tasks are guaranteed to be complete at this point

async def value_return():
    import numpy as np

    # Although we typically return values via shared memory
    # Task Futures can be explicitly returned via synchronization

    T = TaskSpace("T")

    for i in range(2):

        @spawn(T[i])
        def t():
            local_array = np.random.rand(3)
            print(f"Task {i} returning: ", local_array, flush=True)
            return local_array

    array1 = await T[0]
    print("Task 0 returned: ", array1, flush=True)
    array2 = await T[1]
    print("Task 1 returned: ", array2, flush=True)
    
    # array3 = await T[2]
    #print("Task 0 returned: ", array1, flush=True)
    #print("Task 1 returned: ", array2, flush=True)
    # print("Task 3 returned: ", array3, flush=True)
    
    return T