code: # Copyright 2019 The TensorFlow Authors. All Rights Reserved.
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #     http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  # ==============================================================================
  """Tests for the `SnapshotDataset` transformation."""
  from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  
  import multiprocessing
  import os
  import shutil
  import time
  
  from absl.testing import parameterized
  import numpy as np
  
  from tensorflow.python.data.experimental.ops import snapshot
  from tensorflow.python.data.kernel_tests import checkpoint_test_base
  from tensorflow.python.data.kernel_tests import test_base
  from tensorflow.python.data.kernel_tests import tf_record_test_base
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.data.ops import readers as core_readers
  from tensorflow.python.framework import combinations
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import gen_array_ops
  from tensorflow.python.ops import string_ops
  from tensorflow.python.platform import test
  
  
  def is_graphdef_file(filename):
    return filename.endswith("-graph.pbtxt")
  
  
  def is_temp_file(filename):
    return "-tmp-" in filename
  
  
  def listdir_and_filter(dirname, filter_fn):
    return [path for path in sorted(os.listdir(dirname)) if filter_fn(path)]
  
  
  class SnapshotTest(tf_record_test_base.TFRecordTestBase,
                     parameterized.TestCase):
  
    def setUp(self):
      super(SnapshotTest, self).setUp()
      tmpdir = self.get_temp_dir()
      tmpdir = os.path.join(tmpdir, "snapshot")
      os.mkdir(tmpdir)
      self._snapshot_dir = tmpdir
  
    def tearDown(self):
      super(SnapshotTest, self).tearDown()
      shutil.rmtree(self._snapshot_dir)
  
    def createTFRecords(self, num_files=10, num_records=100):
      self._num_files = num_files
      self._num_records = num_records
      self._filenames = self._createFiles()
  
    def removeTFRecords(self):
      for filename in self._filenames:
        os.remove(filename)
      self._filenames = []
      self._num_files = None
      self._num_records = None
  
    def assertDatasetProducesSet(self, dataset, expected):
      actual = []
      next_fn = self.getNext(dataset)
      for _ in range(len(expected)):
        elem = self.evaluate(next_fn())
        actual.append(elem)
      self.assertCountEqual(actual, expected)
      with self.assertRaises(errors.OutOfRangeError):
        self.evaluate(next_fn())
  
    def assertSnapshotDirectoryContains(self, directory, num_fingerprints,
                                        num_runs_per_fingerprint,
                                        num_snapshot_shards_per_run):
  
      # Ignore the graphdef pbtxts we write for debugging purposes and temporary
      # files that are an artifact of how TF writes files.
      dirlist = listdir_and_filter(
          directory,
          lambda p: not (is_graphdef_file(p) or is_temp_file(p)))
      self.assertLen(dirlist, num_fingerprints)
  
      for i in range(num_fingerprints):
        fingerprint_dir = os.path.join(directory, dirlist[i])
        fingerprint_dir_list = listdir_and_filter(
            fingerprint_dir, lambda p: not is_temp_file(p))
        self.assertLen(fingerprint_dir_list, num_runs_per_fingerprint + 1)
        self.assertEqual(fingerprint_dir_list[num_runs_per_fingerprint],
                         "snapshot.metadata")
  
        for j in range(num_runs_per_fingerprint):
          run_dir = os.path.join(fingerprint_dir, fingerprint_dir_list[j])
          run_dirlist = sorted(os.listdir(run_dir))
          self.assertLen(run_dirlist, num_snapshot_shards_per_run)
  
          file_counter = 0
          for filename in run_dirlist:
            self.assertEqual(filename, "%08d.shard" % file_counter)
            file_counter += 1
  
    @combinations.generate(test_base.default_test_combinations())
    def testCreateSnapshotDataset(self):
      dataset = dataset_ops.Dataset.from_tensors([1, 2, 3])
      dataset.apply(snapshot.snapshot(self._snapshot_dir))
  
    @combinations.generate(test_base.default_test_combinations())
    def testReadSnapshotDatasetDefault(self):
      self.createTFRecords()
      filenames = self._filenames
      expected = [
          b"Record %d of file %d" % (r, f)  # pylint:disable=g-complex-comprehension
          for f in range(0, 10)
          for r in range(0, 100)
      ]
  
      dataset = core_readers._TFRecordDataset(filenames)
      dataset = dataset.apply(snapshot.snapshot(self._snapshot_dir))
      self.assertDatasetProduces(dataset, expected)
      self.assertSnapshotDirectoryContains(
          self._snapshot_dir,
          num_fingerprints=1,
          num_runs_per_fingerprint=1,
          num_snapshot_shards_per_run=multiprocessing.cpu_count())
  
      self.removeTFRecords()
      dataset2 = core_readers._TFRecordDataset(filenames)
      dataset2 = dataset2.apply(snapshot.snapshot(self._snapshot_dir))
      self.assertDatasetProduces(dataset2, expected)
  
    @combinations.generate(test_base.default_test_combinations())
    def testReadSnapshotDatasetAutoWriteSnappyRead(self):
      self.createTFRecords()
      filenames = self._filenames
      expected = [
          b"Record %d of file %d" % (r, f)  # pylint:disable=g-complex-comprehension
          for f in range(0, 10)
          for r in range(0, 100)
      ]
  
      dataset = core_readers._TFRecordDataset(filenames)
      dataset = dataset.apply(
          snapshot.snapshot(self._snapshot_dir, compression="AUTO"))
      self.assertDatasetProduces(dataset, expected)
  
      self.removeTFRecords()
      dataset2 = core_readers._TFRecordDataset(filenames)
      dataset2 = dataset2.apply(
          snapshot.snapshot(self._snapshot_dir, compression="SNAPPY"))
      self.assertDatasetProduces(dataset2, expected)
  
    @combinations.generate(test_base.default_test_combinations())
    def testReadSnapshotDatasetCustomShardFn(self):
      self.createTFRecords()
      filenames = self._filenames
      expected = [
          b"Record %d of file %d" % (r, f)  # pylint:disable=g-complex-comprehension
          for f in range(0, 10)
          for r in range(0, 100)
      ]
  
      dataset = core_readers._TFRecordDataset(filenames)
      dataset = dataset.apply(
          snapshot.snapshot(self._snapshot_dir, shard_func=lambda _: np.int64(0)))
      self.assertDatasetProduces(dataset, expected)
      self.assertSnapshotDirectoryContains(
          self._snapshot_dir,
          num_fingerprints=1,
          num_runs_per_fingerprint=1,
          num_snapshot_shards_per_run=1)
  
      self.removeTFRecords()
      dataset2 = core_readers._TFRecordDataset(filenames)
      dataset2 = dataset2.apply(
          snapshot.snapshot(self._snapshot_dir, shard_func=lambda _: 0))
      self.assertDatasetProduces(dataset2, expected)
  
    @combinations.generate(test_base.default_test_combinations())
    def testReadSnapshotDatasetCustomReaderFn(self):
      self.createTFRecords()
      filenames = self._filenames
      expected = [
          b"Record %d of file %d" % (r, f)  # pylint:disable=g-complex-comprehension
          for f in range(0, 10)
          for r in range(0, 100)
      ]
  
      dataset = core_readers._TFRecordDataset(filenames)
      dataset = dataset.apply(
          snapshot.snapshot(
              self._snapshot_dir,
              reader_func=(
                  lambda ds: ds.interleave(  # pylint:disable=g-long-lambda
                      lambda x: x,
                      cycle_length=4,
                      num_parallel_calls=4))))
      self.assertDatasetProduces(dataset, expected)
      self.assertSnapshotDirectoryContains(
          self._snapshot_dir,
          num_fingerprints=1,
          num_runs_per_fingerprint=1,
          num_snapshot_shards_per_run=multiprocessing.cpu_count())
  
      self.removeTFRecords()
      dataset2 = core_readers._TFRecordDataset(filenames)
      dataset2 = dataset2.apply(
          snapshot.snapshot(
              self._snapshot_dir,
              reader_func=(
                  lambda ds: ds.interleave(  # pylint:disable=g-long-lambda
                      lambda x: x,
                      cycle_length=4,
                      num_parallel_calls=4))))
      self.assertDatasetProducesSet(dataset2, expected)
  
    @combinations.generate(test_base.default_test_combinations())
    def testSnapshotDatasetInvalidShardFn(self):
      dataset = dataset_ops.Dataset.range(1000)
      with self.assertRaises(TypeError):
        dataset = dataset.apply(
            snapshot.snapshot(
                self._snapshot_dir, shard_func=lambda _: "invalid_fn"))
        next_fn = self.getNext(dataset)
        self.evaluate(next_fn())
  
    @combinations.generate(test_base.default_test_combinations())
    def testSnapshotDatasetInvalidReaderFn(self):
      dataset = dataset_ops.Dataset.range(1000)
      with self.assertRaises(TypeError):
        dataset = dataset.apply(
            snapshot.snapshot(self._snapshot_dir, reader_func=lambda x: x + 1))
        next_fn = self.getNext(dataset)
        self.evaluate(next_fn())
  
    @combinations.generate(test_base.default_test_combinations())
    def testRoundtripEmptySnapshot(self):
      dataset = dataset_ops.Dataset.range(0)
      dataset = dataset.apply(snapshot.snapshot(self._snapshot_dir))
      self.assertDatasetProduces(dataset, [])
      self.assertSnapshotDirectoryContains(
          self._snapshot_dir,
          num_fingerprints=1,
          num_runs_per_fingerprint=1,
          num_snapshot_shards_per_run=0)
  
      dataset2 = dataset_ops.Dataset.range(0)
      dataset2 = dataset.apply(snapshot.snapshot(self._snapshot_dir))
      self.assertDatasetProduces(dataset2, [])
  
    @combinations.generate(test_base.default_test_combinations())
    def testWriteSnapshotDatasetSimple(self):
      dataset = dataset_ops.Dataset.range(1000)
      dataset = dataset.apply(snapshot.snapshot(self._snapshot_dir))
      self.assertDatasetProduces(dataset, list(range(1000)))
      self.assertSnapshotDirectoryContains(
          self._snapshot_dir,
          num_fingerprints=1,
          num_runs_per_fingerprint=1,
          num_snapshot_shards_per_run=multiprocessing.cpu_count())
  
    @combinations.generate(test_base.default_test_combinations())
    def testWriteSnapshotDatasetMultipleFingerprints(self):
      dataset1 = dataset_ops.Dataset.range(1000)
      dataset1 = dataset1.apply(snapshot.snapshot(self._snapshot_dir))
      self.assertDatasetProduces(dataset1, list(range(1000)))
  
      dataset2 = dataset_ops.Dataset.range(2000)
      dataset2 = dataset2.apply(snapshot.snapshot(self._snapshot_dir))
      self.assertDatasetProduces(dataset2, list(range(2000)))
  
      self.assertSnapshotDirectoryContains(
          self._snapshot_dir,
          num_fingerprints=2,
          num_runs_per_fingerprint=1,
          num_snapshot_shards_per_run=multiprocessing.cpu_count())
  
    @combinations.generate(test_base.default_test_combinations())
    def testWriteSnapshotDatasetSameFingerprintMultipleCompleteRuns(self):
      dataset1 = dataset_ops.Dataset.range(1000)
      dataset1 = dataset1.apply(snapshot.snapshot(self._snapshot_dir))
      self.assertDatasetProduces(dataset1, list(range(1000)))
      dataset2 = dataset_ops.Dataset.range(1000)
      dataset2 = dataset2.apply(snapshot.snapshot(self._snapshot_dir))
      self.assertDatasetProduces(dataset2, list(range(1000)))
  
      self.assertSnapshotDirectoryContains(
          self._snapshot_dir,
          num_fingerprints=1,
          num_runs_per_fingerprint=1,
          num_snapshot_shards_per_run=multiprocessing.cpu_count())
  
    @combinations.generate(test_base.default_test_combinations())
    def testWriteSnapshotDatasetSameFingerprintIncompleteRunRestart(self):
      dataset1 = dataset_ops.Dataset.range(1000)
      dataset1 = dataset1.apply(snapshot.snapshot(self._snapshot_dir))
      next1 = self.getNext(dataset1)
      for i in range(500):
        self.assertEqual(i, self.evaluate(next1()))
  
      dataset2 = dataset_ops.Dataset.range(1000)
      dataset2 = dataset2.apply(snapshot.snapshot(self._snapshot_dir))
      next2 = self.getNext(dataset2)
      for i in range(500):
        self.assertEqual(i, self.evaluate(next2()))
  
      for i in range(500, 1000):
        self.assertEqual(i, self.evaluate(next1()))
        self.assertEqual(i, self.evaluate(next2()))
  
      self.assertSnapshotDirectoryContains(
          self._snapshot_dir,
          num_fingerprints=1,
          num_runs_per_fingerprint=2,
          num_snapshot_shards_per_run=multiprocessing.cpu_count())
  
    @combinations.generate(test_base.default_test_combinations())
    def testWriteSnapshotCustomShardFunction(self):
      dataset = dataset_ops.Dataset.range(1000)
      dataset = dataset.enumerate()
      dataset = dataset.apply(
          snapshot.snapshot(self._snapshot_dir, shard_func=lambda i, _: i % 2))
      dataset = dataset.map(lambda _, elem: elem)
      self.assertDatasetProduces(dataset, list(range(1000)))
      self.assertSnapshotDirectoryContains(
          self._snapshot_dir,
          num_fingerprints=1,
          num_runs_per_fingerprint=1,
          num_snapshot_shards_per_run=2)
  
    @combinations.generate(test_base.default_test_combinations())
    def testWriteSnapshotDatasetWithTuples(self):
      dataset1 = dataset_ops.Dataset.range(0, 1000)
      dataset2 = dataset_ops.Dataset.range(1000, 2000)
      dataset3 = dataset_ops.Dataset.range(2000, 3000)
      dataset4 = dataset_ops.Dataset.range(3000, 4000)
  
      dataset = dataset_ops.Dataset.zip((dataset1, dataset2, dataset3, dataset4))
      dataset = dataset.apply(snapshot.snapshot(self._snapshot_dir))
  
      expected = list(
          zip(
              range(0, 1000), range(1000, 2000), range(2000, 3000),
              range(3000, 4000)))
      self.assertDatasetProduces(dataset, expected)
      self.assertSnapshotDirectoryContains(
          self._snapshot_dir,
          num_fingerprints=1,
          num_runs_per_fingerprint=1,
          num_snapshot_shards_per_run=multiprocessing.cpu_count())
  
    @combinations.generate(test_base.default_test_combinations())
    def testWriteSnapshotShuffleSameFingerprint(self):
  
      def make_dataset():
        dataset = dataset_ops.Dataset.range(1000)
        dataset = dataset.shuffle(1000)
        dataset = dataset.apply(snapshot.snapshot(self._snapshot_dir))
        return dataset
  
      dataset1 = make_dataset()
      self.assertDatasetProducesSet(dataset1, list(range(1000)))
      dataset2 = make_dataset()
      self.assertDatasetProducesSet(dataset2, list(range(1000)))
      self.assertSnapshotDirectoryContains(
          self._snapshot_dir,
          num_fingerprints=1,
          num_runs_per_fingerprint=1,
          num_snapshot_shards_per_run=multiprocessing.cpu_count())
  
    @combinations.generate(test_base.default_test_combinations())
    def testReadUsingFlatMap(self):
      dataset = dataset_ops.Dataset.range(1000)
      dataset = dataset.apply(snapshot.snapshot(self._snapshot_dir))
      self.assertDatasetProduces(dataset, list(range(1000)))
      flat_map = dataset_ops.Dataset.from_tensors(dataset).flat_map(lambda x: x)
      self.assertDatasetProduces(flat_map, list(range(1000)))
      self.assertSnapshotDirectoryContains(
          self._snapshot_dir,
          num_fingerprints=1,
          num_runs_per_fingerprint=1,
          num_snapshot_shards_per_run=multiprocessing.cpu_count())
  
    @combinations.generate(test_base.default_test_combinations())
    def testReadOptimizableUsingFlatMap(self):
      dataset = dataset_ops.Dataset.range(1000)
      # Will be optimized into ShuffleAndRepeat.
      dataset = dataset.shuffle(10)
      dataset = dataset.repeat(2)
      dataset = dataset.apply(snapshot.snapshot(self._snapshot_dir))
      self.assertDatasetProducesSet(dataset, 2 * list(range(1000)))
      flat_map = dataset_ops.Dataset.from_tensors(dataset).flat_map(lambda x: x)
      self.assertDatasetProducesSet(flat_map, 2 * list(range(1000)))
      self.assertSnapshotDirectoryContains(
          self._snapshot_dir,
          num_fingerprints=1,
          num_runs_per_fingerprint=1,
          num_snapshot_shards_per_run=multiprocessing.cpu_count())
  
    @combinations.generate(test_base.default_test_combinations())
    def testRepeatAndPrefetch(self):
      """This test reproduces github.com/tensorflow/tensorflow/issues/48903."""
      dataset = dataset_ops.Dataset.from_tensor_slices(np.random.rand(16, 32))
      dataset = dataset.apply(snapshot.snapshot(self._snapshot_dir))
      dataset = dataset.shuffle(buffer_size=16)
      dataset = dataset.batch(16)
      dataset = dataset.repeat()
      dataset = dataset.prefetch(1)
      next_element = self.getNext(dataset)
      for _ in range(30):
        self.evaluate(next_element())
  
  
  class LegacySnapshotTest(tf_record_test_base.TFRecordTestBase,
                           parameterized.TestCase):
  
    def setUp(self):
      super(LegacySnapshotTest, self).setUp()
      self.removeTFRecords()
      tmpdir = self.get_temp_dir()
      tmpdir = os.path.join(tmpdir, "snapshot")
      os.mkdir(tmpdir)
      self.snapshot_dir = tmpdir
  
    def tearDown(self):
      super(LegacySnapshotTest, self).tearDown()
      shutil.rmtree(self.snapshot_dir)
  
    def removeTFRecords(self):
      for filename in self._filenames:
        os.remove(filename)
      self._filenames = []
  
    def setUpTFRecord(self, num_files=10, num_records=10):
      self._num_files = num_files
      self._num_records = num_records
      self._filenames = self._createFiles()
  
    def makeSnapshotDirectory(self):
      return self.snapshot_dir
  
    def assertSnapshotDirectoryContains(self, directory, num_fingerprints,
                                        num_runs_per_fp, num_snapshot_files):
      # Ignore the graphdef pbtxts we write for debugging purposes and temporary
      # files that are an artifact of how TF writes files.
      dirlist = listdir_and_filter(
          directory,
          lambda p: not (is_graphdef_file(p) or is_temp_file(p)))
      self.assertLen(dirlist, num_fingerprints)
  
      for i in range(num_fingerprints):
        fingerprint_dir = os.path.join(directory, dirlist[i])
        fingerprint_dir_list = listdir_and_filter(
            fingerprint_dir, lambda p: not is_temp_file(p))
        self.assertLen(fingerprint_dir_list, num_runs_per_fp + 1)
        self.assertEqual(fingerprint_dir_list[num_runs_per_fp],
                         "snapshot.metadata")
  
        for j in range(num_runs_per_fp):
          run_dir = os.path.join(fingerprint_dir, fingerprint_dir_list[j])
          run_dirlist = sorted(os.listdir(run_dir))
          self.assertLen(run_dirlist, num_snapshot_files)
  
          file_counter = 0
          for filename in run_dirlist:
            self.assertEqual(filename, "%08d.snapshot" % file_counter)
            file_counter += 1
  
    @combinations.generate(test_base.default_test_combinations())
    def testWriteDifferentPipelinesInOneDirectory(self):
      tmpdir = self.snapshot_dir
  
      dataset = dataset_ops.Dataset.range(1000)
      dataset = dataset.apply(snapshot.legacy_snapshot(tmpdir))
      self.assertDatasetProduces(dataset, list(range(1000)))
  
      dataset = dataset_ops.Dataset.range(1001)
      dataset = dataset.apply(snapshot.legacy_snapshot(tmpdir))
      self.assertDatasetProduces(dataset, list(range(1001)))
  
      self.assertSnapshotDirectoryContains(tmpdir, 2, 1, 1)
  
    @combinations.generate(test_base.default_test_combinations())
    def testWriteSnapshotMultipleSimultaneous(self):
      tmpdir = self.snapshot_dir
  
      dataset1 = dataset_ops.Dataset.range(1000)
      dataset1 = dataset1.apply(snapshot.legacy_snapshot(tmpdir))
      next1 = self.getNext(dataset1)
  
      dataset2 = dataset_ops.Dataset.range(1000)
      dataset2 = dataset2.apply(snapshot.legacy_snapshot(tmpdir))
      next2 = self.getNext(dataset2)
  
      for i in range(0, 1000):
        self.assertEqual(i, self.evaluate(next1()))
        self.assertEqual(i, self.evaluate(next2()))
  
      # we check that only one copy of the metadata has been written, and the
      # one that lost the race would be in passthrough mode.
      self.assertSnapshotDirectoryContains(tmpdir, 1, 1, 1)
  
    @combinations.generate(test_base.default_test_combinations())
    def testGetNextCreatesDir(self):
      tmpdir = self.snapshot_dir
  
      # We create two iterators but call getNext on only one.
      dataset1 = dataset_ops.Dataset.range(1000)
      dataset1 = dataset1.apply(snapshot.legacy_snapshot(tmpdir))
      next1 = self.getNext(dataset1)
  
      dataset2 = dataset_ops.Dataset.range(1001)
      dataset2 = dataset2.apply(snapshot.legacy_snapshot(tmpdir))
      _ = self.getNext(dataset2)
  
      for _ in range(1000):
        self.evaluate(next1())
  
      # We check that only one directory is created.
      self.assertSnapshotDirectoryContains(tmpdir, 1, 1, 1)
  
    @combinations.generate(
        combinations.times(
            test_base.default_test_combinations(),
            combinations.combine(compression=[
                snapshot.COMPRESSION_NONE, snapshot.COMPRESSION_GZIP,
                snapshot.COMPRESSION_SNAPPY
            ])))
    def testWriteSnapshotSimpleSuccessful(self, compression):
      tmpdir = self.snapshot_dir
  
      dataset = dataset_ops.Dataset.range(1000)
      dataset = dataset.apply(
          snapshot.legacy_snapshot(tmpdir, compression=compression))
      self.assertDatasetProduces(dataset, list(range(1000)))
  
      self.assertSnapshotDirectoryContains(tmpdir, 1, 1, 1)
  
    @combinations.generate(
        combinations.times(
            test_base.default_test_combinations(),
            combinations.combine(compression=[
                snapshot.COMPRESSION_NONE, snapshot.COMPRESSION_GZIP,
                snapshot.COMPRESSION_SNAPPY
            ])))
    def testWriteSnapshotRepeatAfterwards(self, compression):
      tmpdir = self.snapshot_dir
  
      dataset = dataset_ops.Dataset.range(10)
      dataset = dataset.apply(
          snapshot.legacy_snapshot(tmpdir, compression=compression))
      dataset = dataset.repeat(10)
      self.assertDatasetProduces(dataset, list(range(10)) * 10)
  
      self.assertSnapshotDirectoryContains(tmpdir, 1, 1, 1)
  
    @combinations.generate(
        combinations.times(
            test_base.default_test_combinations(),
            combinations.combine(compression=[
                snapshot.COMPRESSION_NONE, snapshot.COMPRESSION_GZIP,
                snapshot.COMPRESSION_SNAPPY
            ])))
    def testWriteSnapshotMixTypes(self, compression):
      tmpdir = self.snapshot_dir
  
      dataset = dataset_ops.Dataset.range(10)
  
      def map_fn(x):
        return (x, string_ops.as_string(x), string_ops.as_string(2 * x), 2 * x)
  
      dataset = dataset.map(map_fn)
      dataset = dataset.apply(
          snapshot.legacy_snapshot(tmpdir, compression=compression))
      dataset = dataset.repeat(10)
  
      expected = []
      for i in range(10):
        expected.append((i, str(i), str(2 * i), 2 * i))
      self.assertDatasetProduces(dataset, expected * 10)
  
      self.assertSnapshotDirectoryContains(tmpdir, 1, 1, 1)
  
    @combinations.generate(test_base.default_test_combinations())
    def testSpecifySnapshotNameWriteAndRead(self):
      tmpdir = self.snapshot_dir
  
      dataset = dataset_ops.Dataset.range(10)
      dataset = dataset.apply(
          snapshot.legacy_snapshot(tmpdir, snapshot_name="my_custom_snapshot"))
      dataset = dataset.repeat(10)
      self.assertDatasetProduces(dataset, list(range(10)) * 10)
  
      self.assertSnapshotDirectoryContains(tmpdir, 1, 1, 1)
      self.assertTrue(
          os.path.exists(os.path.join(tmpdir, "custom-my_custom_snapshot")))
      self.assertTrue(
          os.path.exists(
              os.path.join(tmpdir, "custom-my_custom_snapshot", "custom")))
  
    @combinations.generate(test_base.default_test_combinations())
    def testForcePassthroughMode(self):
      tmpdir = self.snapshot_dir
  
      dataset = dataset_ops.Dataset.range(10)
      dataset = dataset.apply(
          snapshot.legacy_snapshot(tmpdir, mode="passthrough"))
      dataset = dataset.repeat(10)
      self.assertDatasetProduces(dataset, list(range(10)) * 10)
  
      self.assertSnapshotDirectoryContains(tmpdir, 0, 0, 0)
  
    @combinations.generate(test_base.default_test_combinations())
    def testForceWriteMode(self):
      tmpdir = self.snapshot_dir
  
      dataset = dataset_ops.Dataset.range(10)
      dataset = dataset.apply(snapshot.legacy_snapshot(tmpdir, mode="write"))
      dataset = dataset.repeat(10)
      self.assertDatasetProduces(dataset, list(range(10)) * 10)
  
      # We will end up writing 10 different runs.
      self.assertSnapshotDirectoryContains(tmpdir, 1, 10, 1)
  
    @combinations.generate(test_base.default_test_combinations())
    def testForceReadMode(self):
      tmpdir = self.snapshot_dir
  
      # We write a copy of the snapshot first.
      dataset = dataset_ops.Dataset.range(10)
      dataset = dataset.apply(
          snapshot.legacy_snapshot(
              tmpdir, mode="write", snapshot_name="my_custom_snapshot"))
      self.assertDatasetProduces(dataset, list(range(10)))
  
      # We move the run to a new name.
      shutil.move(
          os.path.join(tmpdir, "custom-my_custom_snapshot"),
          os.path.join(tmpdir, "custom-my_custom_snapshot_2"))
  
      # Even though the snapshot.metadata is pointing to the old run that no
      # longer exists after we moved, we force it to read from the run we specify.
      dataset = dataset_ops.Dataset.range(10)
      dataset = dataset.apply(
          snapshot.legacy_snapshot(
              tmpdir, mode="read", snapshot_name="my_custom_snapshot_2"))
      self.assertDatasetProduces(dataset, list(range(10)))
  
      # We should still have one snapshot and one run.
      self.assertSnapshotDirectoryContains(tmpdir, 1, 1, 1)
  
    @combinations.generate(test_base.default_test_combinations())
    def testForceReadNonexistentSnapshot(self):
      tmpdir = self.snapshot_dir
      dataset = dataset_ops.Dataset.range(10)
      with self.assertRaises(errors.NotFoundError):
        dataset = dataset.apply(snapshot.legacy_snapshot(tmpdir, mode="read"))
        get_next = self.getNext(dataset)
        self.evaluate(get_next())
  
    @combinations.generate(test_base.default_test_combinations())
    def testForceReadNonexistentNamedSnapshot(self):
      tmpdir = self.snapshot_dir
      dataset = dataset_ops.Dataset.range(10)
      with self.assertRaises(errors.NotFoundError):
        dataset = dataset.apply(
            snapshot.legacy_snapshot(
                tmpdir, mode="read", snapshot_name="my_nonexistent_snapshot"))
        get_next = self.getNext(dataset)
        self.evaluate(get_next())
  
    @combinations.generate(
        combinations.times(
            test_base.default_test_combinations(),
            combinations.combine(compression=[
                snapshot.COMPRESSION_NONE, snapshot.COMPRESSION_GZIP,
                snapshot.COMPRESSION_SNAPPY
            ])))
    def testReadSnapshotBackAfterWrite(self, compression):
      self.setUpTFRecord()
      filenames = self._filenames
  
      expected = [
          b"Record %d of file %d" % (r, f)  # pylint:disable=g-complex-comprehension
          for f in range(0, 10)
          for r in range(0, 10)
      ]
  
      tmpdir = self.snapshot_dir
      dataset = core_readers._TFRecordDataset(filenames)
      dataset = dataset.apply(
          snapshot.legacy_snapshot(tmpdir, compression=compression))
      self.assertDatasetProduces(dataset, expected)
  
      # remove the original files and try to read the data back only from snapshot
      self.removeTFRecords()
  
      dataset2 = core_readers._TFRecordDataset(filenames)
      dataset2 = dataset2.apply(
          snapshot.legacy_snapshot(tmpdir, compression=compression))
      self.assertDatasetProduces(dataset2, expected)
  
    @combinations.generate(test_base.default_test_combinations())
    def testReadShuffledSnapshotAfterWrite(self):
      self.setUpTFRecord(num_files=10, num_records=50)
      filenames = self._filenames
  
      expected = [
          b"Record %d of file %d" % (r, f)  # pylint:disable=g-complex-comprehension
          for f in range(0, 10)
          for r in range(0, 50)
      ]
  
      tmpdir = self.snapshot_dir
      dataset = core_readers._TFRecordDataset(filenames)
      dataset = dataset.apply(
          snapshot.legacy_snapshot(tmpdir, shard_size_bytes=100))
      self.assertDatasetProduces(dataset, expected)
  
      # remove the original files and try to read the data back only from snapshot
      self.removeTFRecords()
  
      dataset2 = core_readers._TFRecordDataset(filenames)
      dataset2 = dataset2.apply(
          snapshot.legacy_snapshot(
              tmpdir, shard_size_bytes=100, shuffle_on_read=True))
      next2 = self.getNext(dataset2)
  
      res1 = self.evaluate(next2())
      res2 = self.evaluate(next2())
      res3 = self.evaluate(next2())
      res4 = self.evaluate(next2())
      res5 = self.evaluate(next2())
  
      # make sure that we don't read the file back in the same order.
      self.assertNotEqual([res1, res2, res3, res4, res5], expected[0:5])
  
      # make sure all the elements are still there
      dataset3 = core_readers._TFRecordDataset(filenames)
      dataset3 = dataset3.apply(
          snapshot.legacy_snapshot(
              tmpdir, shard_size_bytes=100, shuffle_on_read=True))
      self.assertDatasetProduces(dataset3, expected, assert_items_equal=True)
  
    @combinations.generate(test_base.default_test_combinations())
    def testReadShuffledSnapshotWithSeedAfterWrite(self):
      self.setUpTFRecord(num_files=10, num_records=50)
      filenames = self._filenames
  
      expected = [
          b"Record %d of file %d" % (r, f)  # pylint:disable=g-complex-comprehension
          for f in range(0, 10)
          for r in range(0, 50)
      ]
  
      tmpdir = self.snapshot_dir
      dataset = core_readers._TFRecordDataset(filenames)
      dataset = dataset.apply(
          snapshot.legacy_snapshot(tmpdir, shard_size_bytes=10))
      self.assertDatasetProduces(dataset, expected)
  
      # remove the original files and try to read the data back only from snapshot
      self.removeTFRecords()
  
      dataset2 = core_readers._TFRecordDataset(filenames)
      dataset2 = dataset2.apply(
          snapshot.legacy_snapshot(
              tmpdir,
              shard_size_bytes=10,
              shuffle_on_read=True,
              shuffle_seed=123456))
      next2 = self.getNext(dataset2)
  
      dataset3 = core_readers._TFRecordDataset(filenames)
      dataset3 = dataset3.apply(
          snapshot.legacy_snapshot(
              tmpdir,
              shard_size_bytes=10,
              shuffle_on_read=True,
              shuffle_seed=123456))
      next3 = self.getNext(dataset3)
  
      # make sure that the items are read back in the same order for both datasets
      for _ in range(500):
        res2 = self.evaluate(next2())
        res3 = self.evaluate(next3())
        self.assertEqual(res2, res3)
  
    @combinations.generate(
        combinations.times(
            test_base.default_test_combinations(),
            combinations.combine(compression=[
                snapshot.COMPRESSION_NONE, snapshot.COMPRESSION_GZIP,
                snapshot.COMPRESSION_SNAPPY
            ])))
    def testReadSnapshotParallelAfterWrite(self, compression):
      self.setUpTFRecord(5, 500)
      filenames = self._filenames
  
      expected = [
          b"Record %d of file %d" % (r, f)  # pylint:disable=g-complex-comprehension
          for f in range(0, 5)
          for r in range(0, 500)
      ]
  
      tmpdir = self.snapshot_dir
      dataset = core_readers._TFRecordDataset(filenames)
      dataset = dataset.apply(
          snapshot.legacy_snapshot(
              tmpdir,
              shard_size_bytes=1024 * 1024,
              num_reader_threads=2,
              reader_buffer_size=10,
              compression=compression))
      self.assertDatasetProduces(dataset, expected, assert_items_equal=True)
  
      # remove the original files and try to read the data back only from
      # snapshot.
      self.removeTFRecords()
  
      dataset2 = core_readers._TFRecordDataset(filenames)
      dataset2 = dataset2.apply(
          snapshot.legacy_snapshot(
              tmpdir,
              shard_size_bytes=1024 * 1024,
              num_reader_threads=2,
              reader_buffer_size=10,
              compression=compression))
      self.assertDatasetProduces(dataset2, expected, assert_items_equal=True)
  
    # Not testing Snappy here because Snappy reads currently require a lot of
    # memory.
    @combinations.generate(
        combinations.times(
            test_base.default_test_combinations(),
            combinations.times(
                combinations.combine(compression=[
                    snapshot.COMPRESSION_NONE, snapshot.COMPRESSION_GZIP
                ]),
                combinations.combine(threads=2, size=[1, 2]) +
                combinations.combine(threads=8, size=[1, 4, 8]))))
    def testReadSnapshotBackAfterMultiThreadedWrite(self, compression, threads,
                                                    size):
      self.setUpTFRecord()
      filenames = self._filenames
  
      expected = [
          b"Record %d of file %d" % (r, f)  # pylint:disable=g-complex-comprehension
          for f in range(0, 10)
          for r in range(0, 10)
      ]
  
      tmpdir = self.snapshot_dir
      dataset = core_readers._TFRecordDataset(filenames)
      dataset = dataset.apply(
          snapshot.legacy_snapshot(
              tmpdir,
              compression=compression,
              num_writer_threads=threads,
              writer_buffer_size=size))
      self.assertDatasetProduces(dataset, expected)
  
      # remove the original files and try to read the data back only from
      # snapshot
      self.removeTFRecords()
  
      dataset2 = core_readers._TFRecordDataset(filenames)
      dataset2 = dataset2.apply(
          snapshot.legacy_snapshot(tmpdir, compression=compression))
      self.assertDatasetProduces(dataset2, expected, assert_items_equal=True)
  
    @combinations.generate(test_base.default_test_combinations())
    def testSameFingerprintWithDifferentInitializationOrder(self):
      tmpdir = self.snapshot_dir
  
      dataset1 = dataset_ops.Dataset.range(0, 100)
      dataset2 = dataset_ops.Dataset.range(100, 200)
      dataset3 = dataset_ops.Dataset.range(200, 300)
  
      dataset = dataset1.concatenate(dataset2).concatenate(dataset3)
      dataset = dataset.apply(snapshot.legacy_snapshot(tmpdir))
      self.assertDatasetProduces(dataset, list(range(300)))
  
      dataset4 = dataset_ops.Dataset.range(200, 300)
      dataset5 = dataset_ops.Dataset.range(100, 200)
      dataset6 = dataset_ops.Dataset.range(0, 100)
  
      dataset = dataset6.concatenate(dataset5).concatenate(dataset4)
      dataset = dataset.apply(snapshot.legacy_snapshot(tmpdir))
      self.assertDatasetProduces(dataset, list(range(300)))
  
      self.assertSnapshotDirectoryContains(tmpdir, 1, 1, 1)
  
    @combinations.generate(test_base.default_test_combinations())
    def testExpiredSnapshotRewrite(self):
      tmpdir = self.snapshot_dir
  
      dataset1 = dataset_ops.Dataset.range(1000)
      dataset1 = dataset1.apply(
          snapshot.legacy_snapshot(tmpdir, pending_snapshot_expiry_seconds=1))
      next1 = self.getNext(dataset1)
  
      # Don't finish reading dataset1, so it is never finalized
      for _ in range(500):
        self.evaluate(next1())
      self.assertSnapshotDirectoryContains(tmpdir, 1, 1, 1)
  
      time.sleep(2)
  
      # Creating dataset2 after we run through dataset1 due to eager mode, where
      # the snapshot state is determined immediately upon dataset creation. We
      # only want to determine the snapshot state for dataset2 after the first
      # snapshot has expired.
      dataset2 = dataset_ops.Dataset.range(1000)
      dataset2 = dataset2.apply(
          snapshot.legacy_snapshot(tmpdir, pending_snapshot_expiry_seconds=1))
      next2 = self.getNext(dataset2)
  
      for _ in range(500):
        self.evaluate(next2())
      self.assertSnapshotDirectoryContains(tmpdir, 1, 2, 1)
  
    @combinations.generate(test_base.default_test_combinations())
    def testSnapshotArgsCreateNewSnapshot(self):
      tmpdir = self.snapshot_dir
  
      dataset1 = dataset_ops.Dataset.range(1000)
      dataset1 = dataset1.apply(
          snapshot.legacy_snapshot(tmpdir, shard_size_bytes=10000))
      next1 = self.getNext(dataset1)
  
      for _ in range(1000):
        self.evaluate(next1())
      self.assertSnapshotDirectoryContains(tmpdir, 1, 1, 1)
  
      # Create second snapshot with a different shard_size_bytes
      dataset2 = dataset_ops.Dataset.range(1000)
      dataset2 = dataset1.apply(
          snapshot.legacy_snapshot(tmpdir, shard_size_bytes=20000))
      next2 = self.getNext(dataset2)
  
      for _ in range(1000):
        self.evaluate(next2())
      self.assertSnapshotDirectoryContains(tmpdir, 2, 1, 1)
  
    @combinations.generate(
        combinations.times(
            test_base.default_test_combinations(),
            combinations.combine(compression=[
                snapshot.COMPRESSION_NONE, snapshot.COMPRESSION_GZIP,
                snapshot.COMPRESSION_SNAPPY
            ])))
    def testSpecifyShardSize(self, compression):
      tmpdir = self.snapshot_dir
  
      dataset = dataset_ops.Dataset.from_tensor_slices([1.0])
      dataset = dataset.map(lambda x: gen_array_ops.broadcast_to(x, [1024, 1024]))
      dataset = dataset.repeat(10)
      dataset = dataset.apply(
          snapshot.legacy_snapshot(
              tmpdir, shard_size_bytes=10 * 1024 * 1024, compression=compression))
      next_fn = self.getNext(dataset)
  
      for _ in range(10):
        self.evaluate(next_fn())
  
      num_files = 1
      if compression == snapshot.COMPRESSION_NONE:
        num_files = 3
      self.assertSnapshotDirectoryContains(tmpdir, 1, 1, num_files)
  
    @combinations.generate(test_base.default_test_combinations())
    def testAdditionalOperationsAfterReadBack(self):
      self.setUpTFRecord()
      filenames = self._filenames
  
      expected = [
          b"Record %d of file %d" % (r, f)  # pylint:disable=g-complex-comprehension
          for f in range(0, 10)
          for r in range(0, 10)
      ]
  
      tmpdir = self.snapshot_dir
      dataset = core_readers._TFRecordDataset(filenames)
      dataset = dataset.apply(snapshot.legacy_snapshot(tmpdir))
      self.assertDatasetProduces(dataset, expected)
  
      # remove the original files and try to read the data back only from snapshot
      self.removeTFRecords()
  
      dataset2 = core_readers._TFRecordDataset(filenames)
      dataset2 = dataset2.apply(snapshot.legacy_snapshot(tmpdir))
      self.assertDatasetProduces(dataset2, expected)
  
      expected_after = [
          b"cord %d of file %d" % (r, f)  # pylint:disable=g-complex-comprehension
          for f in range(0, 10)
          for r in range(0, 10)
      ]
  
      dataset3 = core_readers._TFRecordDataset(filenames)
      dataset3 = dataset3.apply(snapshot.legacy_snapshot(tmpdir))
      dataset3 = dataset3.map(lambda x: string_ops.substr_v2(x, 2, 1000))
      self.assertDatasetProduces(dataset3, expected_after)
  
  
  class SnapshotCheckpointTest(checkpoint_test_base.CheckpointTestBase,
                               parameterized.TestCase):
  
    def _build_snapshot_dataset(self, repeat=False):
  
      def ds_fn():
        self._snapshot_dir = os.path.join(self.get_temp_dir(), "snapshot")
        if not os.path.exists(self._snapshot_dir):
          os.mkdir(self._snapshot_dir)
  
        dataset = dataset_ops.Dataset.range(100)
        dataset = dataset.apply(snapshot.snapshot(self._snapshot_dir))
        if repeat:
          dataset = dataset.repeat(2)
        return dataset
  
      return ds_fn
  
    @combinations.generate(test_base.default_test_combinations())
    def testCheckpointBeforeEpochEndNoRepeat(self):
      ds_fn = self._build_snapshot_dataset(repeat=False)
      outputs = self.gen_outputs(ds_fn, [], 50, verify_exhausted=False)
      self.assertSequenceEqual(outputs, range(50))
      outputs.extend(
          self.gen_outputs(ds_fn, [], 50, ckpt_saved=True, verify_exhausted=True))
      self.assertSequenceEqual(outputs, range(100))
  
    @combinations.generate(test_base.default_test_combinations())
    def testCheckpointBeforeOneEpochWithReading(self):
      ds_fn = self._build_snapshot_dataset(repeat=True)
  
      # Generate 50 entries from iterator and save checkpoint.
      outputs = self.gen_outputs(ds_fn, [], 50, verify_exhausted=False)
      self.assertSequenceEqual(outputs, list(range(50)))
  
      # Restore from checkpoint and produce the rest of the elements from the
      # iterator.
      t = self.gen_outputs(ds_fn, [], 150, ckpt_saved=True, verify_exhausted=True)
      outputs.extend(t)
      self.assertSequenceEqual(
          outputs,
          list(range(50)) + list(range(50, 100)) + list(range(100)))
  
    @combinations.generate(test_base.default_test_combinations())
    def testCheckpointBeforeOneEpochThenRunAFewSteps(self):
      ds_fn = self._build_snapshot_dataset(repeat=False)
      outputs = self.gen_outputs(
          ds_fn, [10], 20, verify_exhausted=False, save_checkpoint_at_end=False)
      self.assertSequenceEqual(outputs, range(20))
  
      outputs = outputs[:10]
      outputs.extend(
          self.gen_outputs(ds_fn, [], 90, ckpt_saved=True, verify_exhausted=True))
      self.assertSequenceEqual(outputs, range(100))
  
    @combinations.generate(test_base.default_test_combinations())
    def testCheckpointAfterOneEpoch(self):
      ds_fn = self._build_snapshot_dataset(repeat=True)
  
      # Generate 110 entries from iterator and save checkpoint.
      outputs = self.gen_outputs(ds_fn, [], 110, verify_exhausted=False)
      self.assertSequenceEqual(outputs, list(range(100)) + list(range(10)))
  
      # Restore from checkpoint and produce the rest of the elements from the
      # iterator.
      t = self.gen_outputs(ds_fn, [], 90, ckpt_saved=True, verify_exhausted=True)
      outputs.extend(t)
      self.assertSequenceEqual(
          outputs,
          list(range(100)) + list(range(10)) + list(range(10, 100)))
  
    @combinations.generate(test_base.default_test_combinations())
    def testCheckpointAfterOneEpochRunFewSteps(self):
      ds_fn = self._build_snapshot_dataset(repeat=True)
  
      # Generate 120 entries from iterator and save checkpoint at 110.
      outputs = self.gen_outputs(
          ds_fn, [110], 120, verify_exhausted=False, save_checkpoint_at_end=False)
      self.assertSequenceEqual(outputs, list(range(100)) + list(range(20)))
  
      # Restore from checkpoint and produce the rest of the elements from the
      # iterator.
      outputs = outputs[:110]
      t = self.gen_outputs(ds_fn, [], 90, ckpt_saved=True, verify_exhausted=True)
      outputs.extend(t)
      self.assertSequenceEqual(
          outputs,
          list(range(100)) + list(range(10)) + list(range(10, 100)))
  
  
  class LegacySnapshotCheckpointTest(
      checkpoint_test_base.CheckpointTestBase, parameterized.TestCase):
  
    def _build_snapshot_dataset(self,
                                num_threads=1,
                                repeat=False,
                                pending_snapshot_expiry_seconds=-1,
                                shard_size_bytes=None):
  
      def ds_fn():
        self.snapshot_dir = os.path.join(self.get_temp_dir(), "snapshot")
        if not os.path.exists(self.snapshot_dir):
          os.mkdir(self.snapshot_dir)
        dataset = dataset_ops.Dataset.range(1000)
        dataset = dataset.apply(
            snapshot.legacy_snapshot(
                self.snapshot_dir,
                num_writer_threads=num_threads,
                writer_buffer_size=2 * num_threads,
                num_reader_threads=num_threads,
                reader_buffer_size=2 * num_threads,
                pending_snapshot_expiry_seconds=pending_snapshot_expiry_seconds,
                shard_size_bytes=shard_size_bytes))
        if repeat:
          dataset = dataset.repeat(2)
        return dataset
  
      return ds_fn
  
    @combinations.generate(
        combinations.times(
            test_base.default_test_combinations(),
            combinations.combine(pending_snapshot_expiry_seconds=[None, 1])))
    def testSnapshotBeforeEpochEnd(self, pending_snapshot_expiry_seconds):
      ds_fn = self._build_snapshot_dataset(
          pending_snapshot_expiry_seconds=pending_snapshot_expiry_seconds)
      outputs = self.gen_outputs(ds_fn, [], 100, verify_exhausted=False)
      self.assertSequenceEqual(outputs, range(100))
      outputs.extend(
          self.gen_outputs(
              ds_fn, [], 900, ckpt_saved=True, verify_exhausted=False))
      self.assertSequenceEqual(outputs, range(1000))
  
    @combinations.generate(
        combinations.times(
            test_base.default_test_combinations(),
            combinations.combine(pending_snapshot_expiry_seconds=[None, 1])))
    def testCheckpointBeforeOneEpochThenRunFewStepsSmallShardMultiThread(
        self, pending_snapshot_expiry_seconds):
      ds_fn = self._build_snapshot_dataset(
          pending_snapshot_expiry_seconds=pending_snapshot_expiry_seconds,
          shard_size_bytes=100)
  
      outputs = []
      with ops.Graph().as_default() as g:
        init_op, get_next_op, saver = self._build_graph(ds_fn)
        with self.session(graph=g) as sess:
          self._initialize(init_op, sess)
          start = 0
          end = 100
          num_iters = end - start
          for _ in range(num_iters):
            outputs.append(sess.run(get_next_op))
          self._save(sess, saver)
          start = 100
          end = 400
          num_iters = end - start
          for _ in range(num_iters):
            outputs.append(sess.run(get_next_op))
      self.assertSequenceEqual(outputs, range(400))
  
      outputs = outputs[:100]
      outputs.extend(
          self.gen_outputs(
              ds_fn, [], 900, ckpt_saved=True, verify_exhausted=False))
      self.assertSequenceEqual(outputs, range(1000))
      fp_dir_list = os.listdir(self.snapshot_dir)
      self.assertLen(list(fp_dir_list), 2)
      for d in fp_dir_list:
        if not d.endswith("-graph.pbtxt"):
          fp_dir = os.path.join(self.snapshot_dir, d)
          run_dir_list = os.listdir(fp_dir)
          self.assertLen(list(run_dir_list), 2)
          for e in run_dir_list:
            if e != "snapshot.metadata":
              run_dir = os.path.join(fp_dir, e)
              self.assertLen(list(os.listdir(run_dir)), 258)
  
    @combinations.generate(
        combinations.times(
            test_base.default_test_combinations(),
            combinations.combine(pending_snapshot_expiry_seconds=[None, 1])))
    def testCheckpointBeforeOneEpochThenRunFewSteps(
        self, pending_snapshot_expiry_seconds):
      ds_fn = self._build_snapshot_dataset(
          pending_snapshot_expiry_seconds=pending_snapshot_expiry_seconds)
  
      # Generate 200 entries from iterator but save checkpoint after producing
      # 100.
      outputs = self.gen_outputs(
          ds_fn, [100], 200, verify_exhausted=False, save_checkpoint_at_end=False)
      self.assertSequenceEqual(outputs, range(200))
  
      outputs = outputs[:100]
      outputs.extend(
          self.gen_outputs(
              ds_fn, [], 900, ckpt_saved=True, verify_exhausted=False))
      self.assertSequenceEqual(outputs, range(1000))
  
    @combinations.generate(
        combinations.times(
            test_base.default_test_combinations(),
            combinations.combine(pending_snapshot_expiry_seconds=[None, 1])))
    def testCheckpointBeforeOneEpochThenRunFewStepsMultipleThreads(
        self, pending_snapshot_expiry_seconds):
      ds_fn = self._build_snapshot_dataset(
          num_threads=2,
          pending_snapshot_expiry_seconds=pending_snapshot_expiry_seconds)
  
      # Generate 200 entries from iterator but save checkpoint after producing
      # 100.
      outputs = self.gen_outputs(
          ds_fn, [100], 200, verify_exhausted=False, save_checkpoint_at_end=False)
      self.assertSequenceEqual(outputs, range(200))
  
      outputs = outputs[:100]
      outputs.extend(
          self.gen_outputs(
              ds_fn, [], 900, ckpt_saved=True, verify_exhausted=False))
      self.assertSequenceEqual(outputs, range(1000))
  
    @combinations.generate(
        combinations.times(
            test_base.default_test_combinations(),
            combinations.combine(pending_snapshot_expiry_seconds=[None, 1])))
    def testCheckpointAfterOneEpoch(self, pending_snapshot_expiry_seconds):
      ds_fn = self._build_snapshot_dataset(
          repeat=True,
          pending_snapshot_expiry_seconds=pending_snapshot_expiry_seconds)
  
      # Generate 1100 entries from iterator and save checkpoint.
      outputs = self.gen_outputs(ds_fn, [], 1100, verify_exhausted=False)
      self.assertSequenceEqual(outputs, list(range(1000)) + list(range(100)))
  
      # Restore from checkpoint and produce the rest of the elements from the
      # iterator.
      t = self.gen_outputs(
          ds_fn, [], 900, ckpt_saved=True, verify_exhausted=False)
      outputs.extend(t)
      self.assertSequenceEqual(
          outputs,
          list(range(1000)) + list(range(100)) + list(range(900)))
  
    @combinations.generate(
        combinations.times(
            test_base.default_test_combinations(),
            combinations.combine(pending_snapshot_expiry_seconds=[None, 1])))
    def testCheckpointAfterOneEpochThenRunFewSteps(
        self, pending_snapshot_expiry_seconds):
      ds_fn = self._build_snapshot_dataset(
          repeat=True,
          pending_snapshot_expiry_seconds=pending_snapshot_expiry_seconds)
  
      # Generate 200 entries from iterator but save checkpoint after producing
      # 100.
      outputs = self.gen_outputs(
          ds_fn, [1100],
          1200,
          verify_exhausted=False,
          save_checkpoint_at_end=False)
      self.assertSequenceEqual(
          outputs,
          list(range(1000)) + list(range(100)) + list(range(100)))
  
      outputs = outputs[:1100]
      t = self.gen_outputs(
          ds_fn, [], 900, ckpt_saved=True, verify_exhausted=False)
      outputs.extend(t)
      self.assertSequenceEqual(
          outputs, (list(range(1000)) + list(range(100)) + list(range(900))))
  
  
  if __name__ == "__main__":
    test.main()
  
apis: tensorflow.python.data.kernel_tests.test_base.default_test_combinations tensorflow.python.framework.ops.Graph tensorflow.python.data.ops.dataset_ops.Dataset.from_tensor_slices tensorflow.python.data.ops.dataset_ops.Dataset.range tensorflow.python.data.ops.dataset_ops.Dataset.zip tensorflow.python.framework.combinations.combine tensorflow.python.data.experimental.ops.snapshot.legacy_snapshot tensorflow.python.ops.string_ops.as_string tensorflow.python.ops.gen_array_ops.broadcast_to numpy.int64 tensorflow.python.data.experimental.ops.snapshot.snapshot tensorflow.python.platform.test.main numpy.random.rand tensorflow.python.ops.string_ops.substr_v2 tensorflow.python.data.ops.dataset_ops.Dataset.from_tensors tensorflow.python.data.ops.readers._TFRecordDataset