code: def create_data(self):
      def gen_train_sample(data, past_seq_len, future_seq_len):
          data = pd.DataFrame(data)
          x, y = self.ft._roll_train(
              data,
              past_seq_len=past_seq_len,
              future_seq_len=future_seq_len,
          )
          return x, y
  
      def gen_test_sample(data, past_seq_len):
          test_data = pd.DataFrame(data)
          x = self.ft._roll_test(test_data, past_seq_len=past_seq_len)
          return x
  
      self.long_num = 6
      self.time_step = 2
      look_back = (self.long_num + 1) * self.time_step
      look_forward = 1
      self.x_train, self.y_train = gen_train_sample(
          data=np.random.randn(64, 4),
          past_seq_len=look_back,
          future_seq_len=look_forward,
      )
      self.x_val, self.y_val = gen_train_sample(
          data=np.random.randn(16, 4),
          past_seq_len=look_back,
          future_seq_len=look_forward,
      )
      self.x_test = gen_test_sample(
          data=np.random.randn(16, 4), past_seq_len=look_back
      )
  
file_path: analytics-zoo/pyzoo/test/zoo/chronos/model/test_mtnet.py
imports: import shutil
  import pytest
  from test.zoo.pipeline.utils.test_utils import ZooTestCase
  from zoo.chronos.model.MTNet_keras import MTNetKeras
  from zoo.chronos.autots.deprecated.feature.time_sequence import TimeSequenceFeatureTransformer
  import pandas
  import numpy
  import tensorflow
  from numpy.testing import assert_array_almost_equal
label_desc: Use image node_id 3 for calling the TestMTNetKeras obj's underlying member method code with example usage: obj.create_data() and returns: x,  y, x