class_docstr: AutoAttend Search Space , please refer to http://proceedings.mlr.press/v139/guan21a.html for details.
  The current implementation is nc (no context weight sharing), 
  we will in future add other types of partial weight sharing proposed in the paper.
  
  Parameters
  ----------
  ops_type : int 
      0 or 1 , choosing from two sets of ops with index ops_type
  gnn_ops : list of str
      op names for searching, which descripts the compostion of operation pool
  act_op : str
      determine used activation function 
  agg_ops : list of str
      agg op names for searching. Only ['add','attn'] are options, as mentioned in the paper.
code: def __init__(
      self,
      hidden_dim: _typ.Optional[int] = 64,
      layer_number: _typ.Optional[int] = 2,
      dropout: _typ.Optional[float] = 0.9,
      input_dim: _typ.Optional[int] = None,
      output_dim: _typ.Optional[int] = None,
      ops_type=0,
      gnn_ops: _typ.Sequence[_typ.Union[str, _typ.Any]] = None,
      act_op="tanh",
      head=8,
      agg_ops=["add", "attn"],
      # agg_ops=['attn'],
  ):
      super().__init__()
  
      from autogl.backend import DependentBackend
  
      assert (
          not DependentBackend.is_dgl()
      ), "Now AutoAttend only support pyg"
  
      self.layer_number = layer_number
      self.hidden_dim = hidden_dim
      self.input_dim = input_dim
      self.output_dim = output_dim
      self.gnn_ops = gnn_ops
      self.dropout = dropout
      self.act_op = act_op
      self.ops_type = ops_type
      self.head = head
      self.agg_ops = agg_ops
  
imports: from nni.nas.pytorch.mutables import Mutable
  import typing
  import torch
  import torch.nn.functional
  from nni.nas.pytorch import mutables
  from .None import register_nas_space
  from .base import BaseSpace
  from ..utils import count_parameters, measure_latency
  from torch import nn
  from .operation import act_map, gnn_map
  from ..backend import *
  from .autoattend_space.ops1 import OPS
  from .autoattend_space.ops2 import OPS
  from .autoattend_space.operations import agg_map
label_desc: Use image node_id 1 to create a new AutoAttendNodeClassificationSpace object from inherited base classes: BaseSpace with example: obj = AutoAttendNodeClassificationSpace(hidden_dim, layer_number, dropout, input_dim, output_dim, ops_type, gnn_ops, act_op, head, agg_ops)