def __init__(self, filenames):
    'Create a `SequenceFileDataset`.\n\n    `SequenceFileDataset` allows a user to read data from a hadoop sequence\n    file. A sequence file consists of (key value) pairs sequentially. At\n    the moment, `org.apache.hadoop.io.Text` is the only serialization type\n    being supported, and there is no compression support.\n\n    For example:\n\n    ```python\n    dataset = SequenceFileDataset("/foo/bar.seq")\n    iterator = dataset.make_one_shot_iterator()\n    next_element = iterator.get_next()\n    # Prints the (key, value) pairs inside a hadoop sequence file.\n    while True:\n      try:\n        print(sess.run(next_element))\n      except tf.errors.OutOfRangeError:\n        break\n    ```\n\n    Args:\n      filenames: A `tf.string` tensor containing one or more filenames.\n    '
    self._filenames = tf.convert_to_tensor(filenames, dtype=dtypes.string, name='filenames')
    super(SequenceFileDataset, self).__init__()
Create a `SequenceFileDataset`.

`SequenceFileDataset` allows a user to read data from a hadoop sequence
file. A sequence file consists of (key value) pairs sequentially. At
the moment, `org.apache.hadoop.io.Text` is the only serialization type
being supported, and there is no compression support.

For example:

```python
dataset = SequenceFileDataset("/foo/bar.seq")
iterator = dataset.make_one_shot_iterator()
next_element = iterator.get_next()
# Prints the (key, value) pairs inside a hadoop sequence file.
while True:
  try:
    print(sess.run(next_element))
  except tf.errors.OutOfRangeError:
    break
```

Args:
  filenames: A `tf.string` tensor containing one or more filenames.
def __init__(self, filenames):
    'Create a `SequenceFileDataset`.\n\n    `SequenceFileDataset` allows a user to read data from a hadoop sequence\n    file. A sequence file consists of (key value) pairs sequentially. At\n    the moment, `org.apache.hadoop.io.Text` is the only serialization type\n    being supported, and there is no compression support.\n\n    For example:\n\n    ```python\n    dataset = SequenceFileDataset("/foo/bar.seq")\n    iterator = dataset.make_one_shot_iterator()\n    next_element = iterator.get_next()\n    # Prints the (key, value) pairs inside a hadoop sequence file.\n    while True:\n      try:\n        print(sess.run(next_element))\n      except tf.errors.OutOfRangeError:\n        break\n    ```\n\n    Args:\n      filenames: A `tf.string` tensor containing one or more filenames.\n    '
    self._filenames = tf.convert_to_tensor(filenames, dtype=dtypes.string, name='filenames')
    super(SequenceFileDataset, self).__init__()