def pconfig(config, rbm):
'''
Config a problem and optimizer.
'''
# hamiltonian
hconfig = config['hamiltonian']
hamiltonian = load_hamiltonian(**hconfig)
# cgen
cgenconfig = config['cgen']
cgen=SpinConfigGenerator(initial_config=random_config(num_spin=hamiltonian.nsite, mag=cgenconfig['mag']), \
nflip=cgenconfig['num_flip'], inverse_rate=cgenconfig['inverse_rate'])
# vmc
vmcconfig = config['vmc']
vmc=VMC(cgen, nbath=vmcconfig['num_bath_sweep']*hamiltonian.nsite, \
measure_step=vmcconfig['num_sweep_per_sample']*hamiltonian.nsite,\
sampling_method=vmcconfig['accept_method'], iprint=vmcconfig['iprint'])
# sr
srconfig = config['sr']
reg_method = srconfig['reg_method']
lambda0 = srconfig['lambda']
if reg_method == 'delta':
reg_params = ('delta', {'lambda0': lambda0})
elif reg_method == 'trunc':
reg_params = ('trunc', {
'lambda0': lambda0,
'eps_trunc': srconfig['eps_trunc']
})
elif reg_method == 'carleo':
raise NotImplementedError()
reg_params = ('carleo', {'lambda0': lambda0, 'b': 0.9})
elif reg_method == 'sd':
reg_params = ('sd', {})
elif reg_method == 'pinv':
reg_params = ('pinv', {})
else:
raise ValueError('Can not load predefined regulation method %s' %
reg_method)
sr=SR(hamiltonian, reg_params=reg_params, state=rbm, \
rtheta_training_ratio=srconfig['rtheta_training_ratio'],\
layer_wise=srconfig['sr_layerwise'])
# optimize
optimizeconfig = config['optimize']
prob = ProbDef(hamiltonian, rbm, vmc, sr, \
num_vmc_run=vmcconfig['num_vmc_run'], num_vmc_sample=vmcconfig['num_sample'],
redistribute_samples=vmcconfig['redistribute_samples'])
optimizer = get_optimizer(rbm.get_variables(), prob.compute_gradient,
**optimizeconfig)
return optimizer, prob
def __init__(self,
hamiltonian,
rbm,
reg_method,
num_vmc_run=1,
num_vmc_sample=1000,
sr_layerwise=True):
self.reg_method = reg_method
#Create a VMC sampling engine.
cgen=SpinConfigGenerator(initial_config=[-1,1]*(hamiltonian.nsite//2)+\
[1]*(hamiltonian.nsite%2),nflip=2 if hamiltonian.mag is not None else 1, inverse_rate=0.05)
vmc = VMC(cgen,
nbath=200 * hamiltonian.nsite,
measure_step=hamiltonian.nsite,
sampling_method='metropolis',
iprint=0)
##################### choose an regulation method ##############################
if reg_method == 'delta':
reg_params = ('delta', {'lambda0': 1e-4})
elif reg_method == 'trunc':
reg_params = ('trunc', {'lambda0': 0.2, 'eps_trunc': 1e-3})
elif reg_method == 'carleo':
reg_params = ('carleo', {'lambda0': 100, 'b': 0.9})
elif reg_method == 'sd':
reg_params = ('sd', {})
elif reg_method == 'pinv':
reg_params = ('pinv', {})
else:
raise ValueError('Can not load predefined regulation method %s' %
reg_method)
sr = SR(hamiltonian,
reg_params=reg_params,
state=rbm,
rtheta_training_ratio=[1., 30.],
layer_wise=sr_layerwise)
super(ModelProbDef, self).__init__(hamiltonian,
rbm,
vmc,
sr,
num_vmc_run=num_vmc_run,
num_vmc_sample=num_vmc_sample)