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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def olympic_marathon_men(optimize=True, plot=True):
 """Run a standard Gaussian process regression on the Olympic marathon data."""

    try:import pods
    except ImportError:
        print('pods unavailable, see https://github.com/sods/ods for example datasets')
        return
    data = pods.datasets.olympic_marathon_men()

    # create simple GP Model
    m = GPy.models.GPRegression(data['X'], data['Y'])

    # set the lengthscale to be something sensible (defaults to 1)
    m.kern.lengthscale = 10.

    if optimize:
        m.optimize('bfgs', max_iters=200)
    if plot:
        m.plot(plot_limits=(1850, 2050))

    return m