code: def test_correctness(self):
      x = (
          np.arange(450).reshape((2, 3, 5, 5, 3)).astype("float32")
          / 100
      )
      s1 = np.arange(200).reshape((2, 5, 5, 4)).astype("float32") / 100
      s2 = np.arange(200).reshape((2, 5, 5, 4)).astype("float32") / 100
  
      if backend.config.image_data_format() == "channels_first":
          x = x.transpose((0, 1, 4, 2, 3))
          s1 = s1.transpose((0, 3, 1, 2))
          s2 = s2.transpose((0, 3, 1, 2))
      layer = ConvLSTM(
          rank=2,
          filters=4,
          kernel_size=3,
          padding="same",
          kernel_initializer=initializers.Constant(0.01),
          recurrent_initializer=initializers.Constant(0.02),
      )
      output = layer(x, initial_state=[s1, s2])
      output = backend.convert_to_numpy(output)
      self.assertAllClose(np.sum(output), 119.812454)
  
file_path: keras/keras/layers/rnn/conv_lstm_test.py
imports: import numpy
  from keras import backend
  from keras import initializers
  from keras import testing
  from keras.layers.rnn.conv_lstm import ConvLSTM
  from keras.layers.rnn.conv_lstm import ConvLSTMCell
label_desc: Use image node_id 1 for calling the ConvLSTMTest obj's underlying member method code with example usage: obj.test_correctness() without return types