Function ping

dwave/cloud/cli.py:501–556

Ping a solver by submitting a single-qubit problem. If solver is not specified, a QPU solver is selected by default.

(*, config_file, profile, endpoint, region, client_type, solver_def,
         sampling_params, request_timeout, polling_timeout, label, json_output,
         output)

@json_output
@standardized_output
def ping(*, config_file, profile, endpoint, region, client_type, solver_def,
         sampling_params, request_timeout, polling_timeout, label, json_output,
         output):
    """Ping a solver by submitting a single-qubit problem.

    If solver is not specified, a QPU solver is selected by default.
    """

    # parse params (TODO: move to click validator)
    params = {}
    if sampling_params is not None:
        try:
            params = orjson.loads(sampling_params)
            assert isinstance(params, dict)
        except:
            raise CLIError("sampling parameters required as JSON-encoded "
                           "map of param names to values", code=99)

    if label:
        params.update(label=label)

    # gently prefer the least busy QPU
    def order_by(solver):
        category = solver.properties.get('category')
        avg_load = solver.properties.get('avg_load')
        return (0 if category == 'qpu' else 1, avg_load)

    config = dict(
        config_file=config_file, profile=profile,
        endpoint=endpoint, region=region,
        client=client_type, solver=solver_def,
        request_timeout=request_timeout, polling_timeout=polling_timeout,
        defaults=dict(solver=dict(order_by=order_by)))

    t0 = timer()
    client, solver = _get_client_solver(config, output)

    # generate problem
    problem, min_params = solver.minimal_problem
    params = min_params | params

    t1 = timer()
    sample = partial(solver.sample_problem, problem=problem, **params)
    response = _sample(sample, output)

    t2 = timer()
    output("\nWall clock time:")
    output(" * Solver definition fetch: {wallclock_solver_definition:.3f} ms", wallclock_solver_definition=(t1-t0)*1000.0)
    output(" * Problem submit and results fetch: {wallclock_sampling:.3f} ms", wallclock_sampling=(t2-t1)*1000.0)
    output(" * Total: {wallclock_total:.3f} ms", wallclock_total=(t2-t0)*1000.0)
    if response.timing:
        output("\nQPU timing:")
        for component, duration in sorted(response.timing.items()):
            output(" * %(name)s = {%(name)s} us" % {"name": component}, **{component: duration})
    else:
        output("\nQPU timing data not available.")