def x_proj(params):
params[0].data[0] = 1e-5
def grad_proj(params):
params[0].grad.data[0] = 0
## one can also simply set since nfix is globally accessible
# def x_proj(*args,**kw):
# nfix.data[0] = 1e-5
# def grad_proj(*args,**kw):
# nfix.grad.data[0] = 0
# nfi.set_oprions(0,x_proj=x_proj,grad_proj=grad_proj)
paramidx = 0
nfi.set_options(paramidx, x_proj=x_proj, grad_proj=grad_proj)
"""
Now we can solve this constraint optimization problem in a unconstraint manner
"""
print("\n\n\n\n ***************** constraint powell_bs ***************** ")
x, f, d = lbfgsb(nfi.f, x0, nfi.fprime, m=100, factr=1, pgtol=1e-14, iprint=10)
out, fx, its, imode, smode = slsqp(nfi.f,
x0,
fprime=nfi.fprime,
acc=1e-16,
iter=15000,
iprint=1,
full_output=True)
"""
The original output ('x' or 'out') of the optimizer may not satisfy the constraint.
Recall that the nfi.flat_param will automatically do the projection in reader and setter,
f = nfi.f(a)
g = nfi.fprime(a)
print(g)
print(a - nfi.flat_param)
print(nfi.f(a) - f)
print(np.linalg.norm(nfi.fprime(a) - g))
nfi.fprime(a + 1)
print(nfi.f(a) - f)
print(nfi.flat_param - a)
nfi.flat_param = a
print(nfi.fprime(a) - g)
print('no frozen, no x_proj, no grad_proj, 2 param_groups')
test()
nfi.set_options(1, x_proj=x_proj, grad_proj=grad_proj)
print('set x_proj and grad_proj in param_group[1], 2 param_groups')
test()
nfi.add_param_group(param_group2)
print('add param_group')
test()
nfi.flat_param = random.randn(nfi.numel())
nfi.set_options(1, isfrozen=True)
print('set frozen in param_group[1], 3 param_groups')
test()
nfi.set_options(1, x_proj=None, grad_proj=None)
print('delete x_proj,grad_proj in param_group[1], 3 param_groups')
test()
nfi.set_options(0, x_proj=x_proj, grad_proj=grad_proj)
print('add x_proj and grad_proj in param_group[0], 3 param_groups')
test()
x, f, d = lbfgsb(nfi.f, x0, nfi.fprime, m=100, factr=1, pgtol=1e-14, iprint=10)
out, fx, its, imode, smode = slsqp(nfi.f,
x0,
fprime=nfi.fprime,
acc=1e-16,
iter=15000,
iprint=1,
full_output=True)
def x_proj(params):
params[0].data[0] = 1e-5
def grad_proj(params):
params[0].grad.data[0] = 0
nfi.set_options(0, x_proj=x_proj, grad_proj=grad_proj)
x, f, d = lbfgsb(nfi.f, x0, nfi.fprime, m=100, factr=1, pgtol=1e-14, iprint=10)
x = nfi.flat_param
out, fx, its, imode, smode = slsqp(nfi.f,
x0,
fprime=nfi.fprime,
acc=1e-16,
iter=15000,
iprint=1,
full_output=True)
out = nfi.flat_param
#%%
