code: def test_append_record_multip(self):
      a = tf.random.uniform(
          shape=[100, 100], maxval=10000, dtype=tf.int64
      )
      b = tf.random.uniform(
          shape=[100, 100], maxval=10000, dtype=tf.int64
      )
      c = tf.random.uniform(
          shape=[100, 100], maxval=10000, dtype=tf.int64
      )
      sa = tf.io.serialize_tensor(a)
      sb = tf.io.serialize_tensor(b)
      sc = tf.io.serialize_tensor(c)
      dataset.write_record("./temp_append_multip.TFRecord", sa)
      dataset.write_record("./temp_append_multip.TFRecord", sb)
      dataset.write_record("./temp_append_multip.TFRecord", sc)
  
      temp_dataset = iter(
          tf.data.TFRecordDataset(["./temp_append_multip.TFRecord"])
      )
      rsa = next(temp_dataset)
      ra = tf.io.parse_tensor(rsa, out_type=tf.int64)
      np.testing.assert_array_equal(a, ra)
  
      rsb = next(temp_dataset)
      rb = tf.io.parse_tensor(rsb, out_type=tf.int64)
      np.testing.assert_array_equal(b, rb)
  
      rsc = next(temp_dataset)
      rc = tf.io.parse_tensor(rsc, out_type=tf.int64)
      np.testing.assert_array_equal(c, rc)
      os.remove("./temp_append_multip.TFRecord")
  
file_path: tf-encrypted/tf_encrypted/operations/dataset/write_record_test.py
imports: import os
  import unittest
  import numpy
  import tensorflow
  from tf_encrypted.operations import dataset
label_desc: Use image node_id 3 for calling the TestWriteRecord obj's underlying member method code with example usage: obj.test_append_record_multip() without return types