Allow the use of `lightning.pytorch.core.LightningModule` (instead of `torch.nn.Module`) as a base for `to_hetero()` and `to_hetero_with_bases()` to convert homogenous GNNs into heterogenous ones when using PyTorch Lightning.
### 🚀 The feature, motivation and pitch I'm using PyG with PyTorch Lightning. In PyTorch Lightning the inheritance base is `lightning.pytorch.core.LightningModule` instead of the plain `torch.nn.Module` (`LightningModule` is derived from `Module` through). As a consequence, I stumbled upon the problem, that I can't use ` to_hetero()` (also `to_hetero_with_bases()`) to convert my homogenous GNN into a heterogenous one. The reason is that those methods assume a `Module` as base: https://github.com/pyg-team/pytorch_geometric/blob/a89e0222f43cda6282774fa8e01fb3951357a40e/torch_geometric/nn/to_hetero_transformer.py#L137 ``` model = GNNGraphConv( # own GNN based on LightningModule # in_channels=graph.num_node_features, in_channels=-1, # lazy init for heterogenous graphs # (channels inferred on first forward pass) hidden_channels=trial_params.model_parameters.hidden_channels, dropout_rate=trial_params.mo