def olympic_100m_men(optimize=True, plot=True):
try:import pods<EOL>except ImportError:<EOL><INDENT>print('<STR_LIT>')<EOL>return<EOL><DEDENT>data = pods.datasets.olympic_100m_men()<EOL>m = GPy.models.GPRegression(data['<STR_LIT:X>'], data['<STR_LIT:Y>'])<EOL>m.rbf.lengthscale = <NUM_LIT:10><EOL>if optimize:<EOL><INDENT>m.optimize('<STR_LIT>', max_iters=<NUM_LIT:200>)<EOL><DEDENT>if plot:<EOL><INDENT>m.plot(plot_limits=(<NUM_LIT>, <NUM_LIT>))<EOL><DEDENT>return m<EOL>
Run a standard Gaussian process regression on the Rogers and Girolami olympics data.