code: def setUp(self):
      self.precision_bits = 50
      self.scale = 2**self.precision_bits
  
      self._dim1_scalar = tf.constant([10, 0], dtype=tf.int64)
      self._dim2_scalar = tf.constant([[11, 0]], dtype=tf.int64)
  
      self._A = np.random.rand(5, 3) - 0.5
      self.A = tf_i128.to_i128(
          tf.convert_to_tensor(self._A, dtype=tf.float64), self.scale
      )
  
      self._B = np.random.rand(self._A.shape[0], self._A.shape[1]) - 0.5
      self.B = tf_i128.to_i128(
          tf.convert_to_tensor(self._B, dtype=tf.float64), self.scale
      )
  
      self._C = np.random.rand(self._A.shape[1], 20) - 0.5
      self.C = tf_i128.to_i128(
          tf.convert_to_tensor(self._C, dtype=tf.float64), self.scale
      )
  
      self._D = np.random.randint(low=-100, high=100, size=(3, 10))
      self.D = tf_i128.to_i128(
          tf.convert_to_tensor(self._D, dtype=tf.float64)
      )
  
      self._E = np.random.rand(self._A.shape[1]) - 0.5
      self.E = tf_i128.to_i128(
          tf.convert_to_tensor(self._E, dtype=tf.float64), self.scale
      )
  
      self._F = np.random.rand(1) - 0.5
      self.F = tf_i128.to_i128(
          tf.convert_to_tensor(self._F, dtype=tf.float64), self.scale
      )
  
      self._A_3d = np.random.rand(5, 3, 3) - 0.5
      self.A_3d = tf_i128.to_i128(
          tf.convert_to_tensor(self._A_3d, dtype=tf.float64), self.scale
      )
  
imports: import unittest
  import numpy
  import tensorflow
  from tf_encrypted.operations import tf_i128
label_desc: Use image node_id 1 for calling the I128TestCase obj's underlying member method code with example usage: obj.setUp() without return types