code: def forward(
      self, data: torch_geometric.data.Data, *__args, **__kwargs
  ) -> _typing.Sequence[torch.Tensor]:
      x: torch.Tensor = data.x
      edge_index: torch.Tensor = data.edge_index
  
      results: _typing.MutableSequence[torch.Tensor] = [x]
      num_layers = len(self.__convolution_layers)
      for layer in range(num_layers):
          x: torch.Tensor = self.__convolution_layers[layer](
              x, edge_index
          )
          x: torch.Tensor = _utils.activation.activation_func(
              x, self._act
          )
          x: torch.Tensor = self.__batch_normalizations[layer](x)
          results.append(x)
      return results
  
file_path: AutoGL/autogl/module/model/encoders/_pyg/_gin.py
imports: import typing
  import torch.nn.functional
  import torch_geometric
  from torch_geometric.nn.conv import GINConv
  from ..None import base_encoder, encoder_registry
  from ...None import _utils
label_desc: Use image node_id 2 for calling the _GIN obj's underlying member method code with example usage: obj.forward(data) and returns: results