code: def __init__(
      self,
      input_dimension: int,
      dimensions: _typing.Sequence[int],
      _act: _typing.Optional[str],
      _dropout: _typing.Optional[float],
      aggr: _typing.Optional[str],
  ):
      super(_SAGE, self).__init__()
      self._act: _typing.Optional[str] = _act
      self._dropout: _typing.Optional[float] = _dropout
      self.__convolution_layers: torch.nn.ModuleList = (
          torch.nn.ModuleList()
      )
      for layer, output_dimension in enumerate(dimensions):
          self.__convolution_layers.append(
              SAGEConv(
                  input_dimension
                  if layer == 0
                  else dimensions[layer - 1],
                  output_dimension,
                  aggr=aggr,
              )
          )
  
file_path: AutoGL/autogl/module/model/encoders/_pyg/_sage.py
imports: import torch.nn.functional
  import typing
  import torch_geometric
  from torch_geometric.nn.conv import SAGEConv
  from ..None import base_encoder, encoder_registry
  from ...None import _utils
label_desc: Use image node_id 1 to create a new _SAGE object from inherited base classes: torch.nn with example: obj = _SAGE(input_dimension, dimensions, _act, _dropout, aggr)