PythonToCppWorkaround.py

class M(nn.Module):
	# Only empty lists/dicts and TorchScript classes need types
	__annotations__ = {
		my_list: List[int],
	}

	def __init__(self, some_values):
		super(M, self).__init__()
		for key in some_values:
			setattr(self, key, some_values[key])

	def forward(self):
		pass

my_values_to_save = {
	'a': 20,
	'b': [1, 2, 3],
	'c': torch.randn(2, 2)
}

torch.jit.script(M(my_values_to_save)).save('out.pt')

# In C++, load `out.pt` as a script::Module and use `get_attribute` to extract
# values by name