def initialize_values(self, x0, step):
step, obj, x, x_old = \
SolverFirstOrder._initialize_values(self, x0, step,
n_empty_vectors=1)
z_list = [np.zeros_like(x) for _ in range(self.prox.n_proxs)]
z_old_list = [np.zeros_like(x) for _ in range(self.prox.n_proxs)]
return x, x_old, z_list, z_old_list, obj, step
def _initialize_values(self, x0, step):
step, obj, x, prev_x, prev_grad_x_ssc, grad_x_ssc = \
SolverFirstOrder._initialize_values(self, x0, step,
n_empty_vectors=3)
grad_x_ssc = self.model_ssc.grad(x, out=grad_x_ssc)
return step, obj, x, prev_x, prev_grad_x_ssc, grad_x_ssc
def _initialize_values(self, x0=None, step=None):
if step is None:
if self.step is None:
if self.linesearch:
# If we use linesearch, then we can choose a large
# initial step
step = 1e9
else:
raise ValueError("No step specified.")
step, obj, x, prev_x, x_new = \
SolverFirstOrder._initialize_values(self, x0, step,
n_empty_vectors=2)
return x, prev_x, x_new, step, obj