[docs]class Generator():
r"""
The method base class for graph generation. To write a new graph generation method, create a new class
inheriting from this class and implement the functions.
"""
[docs] def train_rand_gen(self, loader, *args, **kwargs):
r"""
Running training for random generation task.
Args:
loader: The data loader for loading training samples.
"""
raise NotImplementedError("The function train_rand_gen is not implemented!")
[docs] def run_rand_gen(self, *args, **kwargs):
r"""
Running graph generation for random generation task.
"""
raise NotImplementedError("The function run_rand_gen is not implemented!")
[docs] def train_prop_opt(self, *args, **kwargs):
r"""
Running training for property optimization task.
"""
raise NotImplementedError("The function train_prop_opt is not implemented!")
[docs] def run_prop_opt(self, *args, **kwargs):
r"""
Running graph generation for property optimization task.
"""
raise NotImplementedError("The function run_prop_opt is not implemented!")
[docs] def train_const_prop_opt(self, loader, *args, **kwargs):
r"""
Running training for constrained optimization task.
Args:
loader: The data loader for loading training samples.
"""
raise NotImplementedError("The function train_const_prop_opt is not implemented!")
[docs] def run_const_prop_opt(self, *args, **kwargs):
r"""
Running molecule optimization for constrained optimization task.
"""
raise NotImplementedError("The function run_const_prop_opt is not implemented!")