Python `yield from`, or return a generator?

The difference is that your first mymap is just a usual function,
in this case a factory which returns a generator. Everything
inside the body gets executed as soon as you call the function.

def gen_factory(func, seq):
    """Generator factory returning a generator."""
    # do stuff ... immediately when factory gets called
    print("build generator & return")
    return (func(*args) for args in seq)

The second mymap is also a factory, but it’s also a generator
itself, yielding from a self-built sub-generator inside.
Because it is a generator itself, execution of the body does
not start until the first invokation of next(generator).

def gen_generator(func, seq):
    """Generator yielding from sub-generator inside."""
    # do stuff ... first time when 'next' gets called
    print("build generator & yield")
    yield from (func(*args) for args in seq)

I think the following example will make it clearer.
We define data packages which shall be processed with functions,
bundled up in jobs we pass to the generators.

def add(a, b):
    return a + b

def sqrt(a):
    return a ** 0.5

data1 = [*zip(range(1, 5))]  # [(1,), (2,), (3,), (4,)]
data2 = [(2, 1), (3, 1), (4, 1), (5, 1)]

job1 = (sqrt, data1)
job2 = (add, data2)

Now we run the following code inside an interactive shell like IPython to
see the different behavior. gen_factory immediately prints
out, while gen_generator only does so after next() being called.

gen_fac = gen_factory(*job1)
# build generator & return <-- printed immediately
next(gen_fac)  # start
# Out: 1.0
[*gen_fac]  # deplete rest of generator
# Out: [1.4142135623730951, 1.7320508075688772, 2.0]

gen_gen = gen_generator(*job1)
next(gen_gen)  # start
# build generator & yield <-- printed with first next()
# Out: 1.0
[*gen_gen]  # deplete rest of generator
# Out: [1.4142135623730951, 1.7320508075688772, 2.0]

To give you a more reasonable use case example for a construct
like gen_generator we’ll extend it a little and make a coroutine
out of it by assigning yield to variables, so we can inject jobs
into the running generator with send().

Additionally we create a helper function which will run all tasks
inside a job and ask as for a new one upon completion.

def gen_coroutine():
    """Generator coroutine yielding from sub-generator inside."""
    # do stuff... first time when 'next' gets called
    print("receive job, build generator & yield, loop")
    while True:
        try:
            func, seq = yield "send me work ... or I quit with next next()"
        except TypeError:
            return "no job left"
        else:
            yield from (func(*args) for args in seq)


def do_job(gen, job):
    """Run all tasks in job."""
    print(gen.send(job))
    while True:
        result = next(gen)
        print(result)
        if result == "send me work ... or I quit with next next()":
            break

Now we run gen_coroutinewith our helper function do_joband two jobs.

gen_co = gen_coroutine()
next(gen_co)  # start
# receive job, build generator & yield, loop  <-- printed with first next()
# Out:'send me work ... or I quit with next next()'
do_job(gen_co, job1)  # prints out all results from job
# 1
# 1.4142135623730951
# 1.7320508075688772
# 2.0
# send me work... or I quit with next next()
do_job(gen_co, job2)  # send another job into generator
# 3
# 4
# 5
# 6
# send me work... or I quit with next next()
next(gen_co)
# Traceback ...
# StopIteration: no job left

To come back to your question which version is the better approach in general.
IMO something like gen_factory makes only sense if you need the same thing done for multiple generators you are going to create, or in cases your construction process for generators is complicated enough to justify use of a factory instead of building individual generators in place with a generator comprehension.

Note:

The description above for the gen_generator function (second mymap) states
“it is a generator itself”. That is a bit vague and technically not
really correct, but facilitates reasoning about the differences of the functions
in this tricky setup where gen_factory also returns a generator, namely that
one built by the generator comprehension inside.

In fact any function (not only those from this question with generator comprehensions inside!) with a yield inside, upon invocation, just
returns a generator object which gets constructed out of the function body.

type(gen_coroutine) # function
gen_co = gen_coroutine(); type(gen_co) # generator

So the whole action we observed above for gen_generator and gen_coroutine
takes place within these generator objects, functions with yield inside have spit out before.