code: def test_base_esn():
      units = 3
      expected_output = np.array(
          [[2.77, 2.77, 2.77], [4.77, 4.77, 4.77], [6.77, 6.77, 6.77]],
          dtype=np.float32,
      )
  
      const_initializer = tf.constant_initializer(0.5)
      cell = ESNCell(
          units=units,
          connectivity=1,
          leaky=1,
          spectral_radius=0.9,
          use_norm2=True,
          use_bias=True,
          activation=None,
          kernel_initializer=const_initializer,
          recurrent_initializer=const_initializer,
          bias_initializer=const_initializer,
      )
  
      inputs = tf.constant(
          np.array(
              [
                  [1.0, 1.0, 1.0, 1.0],
                  [2.0, 2.0, 2.0, 2.0],
                  [3.0, 3.0, 3.0, 3.0],
              ],
              dtype=np.float32,
          ),
          dtype=tf.float32,
      )
      state_value = tf.constant(
          0.3 * np.ones((units, units), dtype=np.float32),
          dtype=tf.float32,
      )
      init_state = [state_value, state_value]
      output, state = cell(inputs, init_state)
  
      np.testing.assert_allclose(output, expected_output, 1e-5)
      np.testing.assert_allclose(state, expected_output, 1e-5)
  
file_path: addons/tensorflow_addons/rnn/tests/esn_cell_test.py
imports: import numpy
  import tensorflow
  import tensorflow.keras
  from tensorflow_addons.rnn import ESNCell
label_desc: Use image node_id 1 for calling a global function with example usage: test_base_esn() without return types