code: def setUpClass(cls):
      cls.batch_size = 16
  
      cls.vocab_size = 200
      cls.embedding_size = 32
      cls.dec_seq_length = 5
      cls.pure_time = np.linspace(-1, 1, 21)
      cls.pure_signal = 100 * np.sin(cls.pure_time)
      cls.dataset = np.zeros((100, 21))
      for i in range(100):
          noise = 100 + 1 * np.random.normal(
              0, 1, cls.pure_signal.shape
          )
          cls.dataset[i] = cls.pure_signal + noise
      cls.dataset = cls.dataset.astype(int)
      np.random.shuffle(cls.dataset)
      cls.trainX = cls.dataset[:80, :15]
      cls.trainY = cls.dataset[:80, 15:]
      cls.testX = cls.dataset[80:, :15]
      cls.testY = cls.dataset[80:, 15:]
  
      cls.trainY[:, 0] = 0  # start_token == 0
      cls.testY[:, 0] = 0  # start_token == 0
  
      # Parameters
      cls.src_len = len(cls.trainX)
      cls.tgt_len = len(cls.trainY)
  
      assert cls.src_len == cls.tgt_len
  
      cls.num_epochs = 500
      cls.n_step = cls.src_len // cls.batch_size
  
file_path: TensorLayer/tests/models/test_seq2seq_with_attention.py
imports: import os
  import unittest
  import numpy
  import tensorflow
  from sklearn.utils import shuffle
  from tqdm import tqdm
  import tensorlayer
  from tensorlayer.cost import cross_entropy_seq
  from tensorlayer.models.seq2seq_with_attention import Seq2seqLuongAttention
  from tests.utils import CustomTestCase
label_desc: Use image node_id 1 for calling the Model_SEQ2SEQ_WITH_ATTENTION_Test obj's underlying member method code with example usage: obj.setUpClass(cls) without return types