code: def create_mock_states(number_of_nodes, out_channels):
      """
      Creating mock hidden and cell states.
      """
      H = torch.FloatTensor(
          np.random.uniform(-1, 1, (number_of_nodes, in_channels))
      )
      C = torch.FloatTensor(
          np.random.uniform(-1, 1, (number_of_nodes, in_channels))
      )
      return H, C
  
imports: import torch
  import numpy
  import networkx
  from torch_geometric_temporal.nn.recurrent import GConvLSTM, GConvGRU, DCRNN, AGCRN
  from torch_geometric_temporal.nn.recurrent import GCLSTM, LRGCN, DyGrEncoder
  from torch_geometric_temporal.nn.recurrent import EvolveGCNH, EvolveGCNO, TGCN, A3TGCN, A3TGCN2, MPNNLSTM
label_desc: Use image node_id 4 for calling a global function with example usage: create_mock_states(number_of_nodes, out_channels) and returns: H,  C