# Setup the training constant and a test set
from Lcod.simple_problem_generator import SimpleProblemGenerator
from Lcod.simple_problem_generator import create_dictionary
p = 64 # Dimension of the data
D = create_dictionary(K, p, seed=290890)
pb = SimpleProblemGenerator(D, lmbd, rho=rho, batch_size=batch_size,
corr=corr, seed=422742)
sig_test, z0_test, zs_test, _ = pb.get_test(N_test)
sig_val, z0_val, zs_val, _ = pb.get_batch(N_val)
C0 = pb.lasso_cost(zs_test, sig_test)
# Compute optimal values for validation/test sets using ISTA/FISTA
ista = IstaTF(D, gpu_usage=gpu_usage)
ista.optimize(X=sig_val, lmbd=lmbd, Z=zs_val,
max_iter=10000, tol=1e-8 * C0)
c_val = ista.train_cost[-1]
ista.optimize(X=sig_test, lmbd=lmbd, Z=zs_test,
max_iter=10000, tol=1e-8 * C0)
feed_test = {"Z": zs_test, "X": sig_test, "lmbd": lmbd}
feed_val = {"Z": zs_val, "X": sig_val, "lmbd": lmbd,
"c_val": c_val - 1e-10}
# Free the ressources
ista.terminate()
cc = np.array(ista.train_cost)
c_star = cc[-1] - 1e-6
reg_scale = 1e-4
# D = create_dictionary_dl(lmbd,K)
# D = np.identity(3072).astype(np.float32)
D = np.random.random([3072,3072]).astype(np.float32)
pb = FruitProblemGenerator(D,lmbd,batch_size=batch_size,seed=1234)
else:
raise NameError("dataset {} not reconized by the script"
"".format(dataset))
# sig_test, z0_test, zs_test, _ = pb.get_test(N_test)
sig_val, z0_val, zs_val, _ = pb.get_batch(N_val)
# Compute optimal values for validation/test sets using ISTA/FISTA
ista = IstaTF(D, gpu_usage=gpu_usage)
z_curr =ista.optimize(X=sig_val, lmbd=lmbd, Z=zs_val,max_iter=1000)
c_val = 1e-10
# feed_test = {"Z": zs_test, "X": sig_test, "lmbd": lmbd}
feed_val = {"Z": zs_val, "X": sig_val, "lmbd": lmbd, "c_val": c_val-1e-10}
feed_val_lista = {"Z": zs_val, "Zp": z_curr, "X": sig_val, "lmbd": lmbd, "c_val": c_val-1e-10}
#initiate all models
"""
ista = IstaTF(D, gpu_usage=gpu_usage)
fista = FistaTF(D, gpu_usage=gpu_usage)
lfis = LFistaNetwork(D, n_layers=10, shared=True, log_lvl=log_lvl,gpu_usage=gpu_usage,exp_dir=NAME_EXP,Zpflag=True)
lis = LIstaNetwork(D, n_layers=10, shared=True, log_lvl=log_lvl,gpu_usage=gpu_usage, exp_dir=NAME_EXP,Zpflag = True)
"""
D = create_dictionary_haar(p)
pb = ImageProblemGenerator(D,
lmbd,
batch_size=batch_size,
data_dir='data/VOC',
seed=1234)
else:
raise NameError("dataset {} not reconized by the script"
"".format(dataset))
sig_test, z0_test, zs_test, _ = pb.get_test(N_test)
sig_val, z0_val, zs_val, _ = pb.get_batch(N_val)
C0 = pb.lasso_cost(zs_test, sig_test)
# Compute optimal values for validation/test sets using ISTA/FISTA
ista = IstaTF(D, gpu_usage=gpu_usage)
ista.optimize(X=sig_test,
lmbd=lmbd,
Z=zs_test,
max_iter=10000,
tol=1e-8 * C0)
fista = FistaTF(D, gpu_usage=gpu_usage)
fista.optimize(X=sig_val,
lmbd=lmbd,
Z=zs_val,
max_iter=10000,
tol=1e-8 * C0)
c_val = fista.train_cost[-1]
fista.optimize(X=sig_test,
lmbd=lmbd,