def update_target(self):
copy(np.frombuffer(self.target_vars.vars, ctypes.c_float),
np.frombuffer(self.learning_vars.vars, ctypes.c_float))
# Set shared flags
for i in xrange(len(self.target_update_flags.updated)):
self.target_update_flags.updated[i] = 1
def update_target(self):
if self.alg_type != "AE":
copy(np.frombuffer(self.target_vars.vars, ctypes.c_float),
np.frombuffer(self.learning_vars.vars, ctypes.c_float))
else:
copy(np.frombuffer(self.target_vars_lower.vars, ctypes.c_float),
np.frombuffer(self.learning_vars_lower.vars, ctypes.c_float))
copy(np.frombuffer(self.target_vars_upper.vars, ctypes.c_float),
np.frombuffer(self.learning_vars_upper.vars, ctypes.c_float))
# Set shared flags
for i in range(len(self.target_update_flags.updated)):
self.target_update_flags.updated[i] = 1