code: def testLoss(self):
      batch_size = 2
      key_depth = 5
      val_depth = 5
      memory_size = 4
      window_size = 3
      x_depth = 5
      memory = transformer_memory.TransformerMemory(
          batch_size, key_depth, val_depth, memory_size
      )
      x = tf.random_uniform(
          [batch_size, window_size, x_depth], minval=0.0
      )
      memory_results, _, _, _ = memory.pre_attention(
          tf.random_uniform(
              [batch_size], minval=0, maxval=1, dtype=tf.int32
          ),
          x,
          None,
          None,
      )
      x = memory.post_attention(memory_results, x)
      with tf.control_dependencies([tf.print("x", x)]):
          is_nan = tf.reduce_any(tf.math.is_nan(x))
      with self.test_session() as session:
          session.run(tf.global_variables_initializer())
          for _ in range(100):
              is_nan_value, _ = session.run([is_nan, x])
      self.assertEqual(is_nan_value, False)
  
file_path: tensor2tensor/tensor2tensor/layers/transformer_memory_test.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  from tensor2tensor.layers import transformer_memory
  import tensorflow.compat.v1
label_desc: Use image node_id 4 for calling the TransformerMemoryTest obj's underlying member method code with example usage: obj.testLoss() without return types