code: def test_gcn_lstm_model_prediction():
      fx, fy, a = get_timeseries_graph_data()
  
      gcn_lstm_model = GCN_LSTM(
          seq_len=fx.shape[-1],
          adj=a,
          gc_layer_sizes=[8, 8, 16],
          gc_activations=["relu", "relu", "relu"],
          lstm_layer_sizes=[8, 16, 32],
          lstm_activations=["tanh"],
      )
  
      x_input, x_output = gcn_lstm_model.in_out_tensors()
      model = Model(inputs=x_input, outputs=x_output)
  
      test_sample = np.random.rand(1, 5, 4)
      pred = model.predict(test_sample)
  
      # check 1 prediction for each node
      assert pred.shape == (1, 5)
  
imports: import numpy
  import pandas
  import pytest
  from tensorflow.keras import Model
  from stellargraph import StellarGraph, IndexedArray
  from stellargraph.layer import GCN_LSTM
  from stellargraph.layer import FixedAdjacencyGraphConvolution
  from stellargraph.mapper import SlidingFeaturesNodeGenerator
  from ..None import test_utils
label_desc: Use image node_id 9 for calling a global function with example usage: test_gcn_lstm_model_prediction() without return types