x0 = 0.01*ones(m)
##########################################
# Stores the intermediate values for later plotting
phf_cb = convergence.PlottingCallback("Conf. Hessian free", ndata)
x, optinfo = phessianfree.optimize(f, x0, ndata, maxiter=20, callback=phf_cb, props={})
##########################################
# Stores the intermediate values for later plotting
hf_cb = convergence.PlottingCallback("Hessian free", ndata)
x, optinfo = phessianfree.optimize(f, x0, ndata, maxiter=14, callback=hf_cb, props={
'subsetVariant': 'cg',
'subsetObjective': False,
})
##########################################
lbfgs_wrapper = convergence.PlottingWrapper(f, "lbfgs", ndata)
logger.info("Running scipy's lbfgs implementation")
scipy.optimize.fmin_l_bfgs_b(lbfgs_wrapper, x0, m=10, maxfun=30, disp=5)
##########################################
phf_sgd = convergence.PlottingCallback("SGD", ndata)
x = phessianfree.sgd(f, x0, ndata, maxiter=30, callback=phf_sgd,
props={'SGDInitialStep': 4.0, 'SGDStepScale': 0.1})
#########################################
convergence.plot([lbfgs_wrapper, hf_cb, phf_cb, phf_sgd], [0.235, 0.3])
'subsetVariant': 'lbfgs',
'parts': 100,
'innerSolveAverage': False, # Should be used when parts is large
'solveFraction': 0.2,
'gradRelErrorBound': 0.1
}
logger.info("Running phessianfree with inner lbfgs linear solver")
x, optinfo = phessianfree.optimize(f, x0, ndata, maxiter=20, callback=phf_cb, props=props)
##############################
# Run with inner cg method as well
props = {
'subsetVariant': 'cg',
'parts': 100,
'solveFraction': 0.2,
'subsetObjective': False
}
phf_cb_cg = convergence.PlottingCallback("phessianfree cg", ndata)
logger.info("Running phessianfree with conjugate gradient linear solver")
#x, optinfo = phessianfree.optimize(f, x0, ndata, maxiter=iters, callback=phf_cb_cg, props=props)
phf_sgd = convergence.PlottingCallback("SGD", ndata)
x = phessianfree.sgd(f, x0, ndata, maxiter=30, callback=phf_sgd,
props={'SGDInitialStep': 30.0, 'SGDStepScale': 0.1})
convergence.plot([lbfgs_wrapper, phf_cb, phf_sgd], [119, 160])
