class_docstr: A MNISTImageIODataset
class_docstr_tok: ["A","MNISTImageIODataset"]
docstr: Create a MNISTImageDataset.
  
  Args:
      filename: A `tf.string` tensor containing filename.
docstr_tok: ["Create","a","MNISTImageDataset",".","Args",":","filename",":","A","`","tf.string","`","tensor","containing","filename","."]
code: def __init__(self, filename):
      """Create a MNISTImageDataset.
  
      Args:
          filename: A `tf.string` tensor containing filename.
      """
      _, compression = core_ops.io_file_info(filename)
      rows = tf.io.decode_raw(
          core_ops.io_file_read(
              filename, 8, 4, compression=compression
          ),
          tf.int32,
          little_endian=False,
      )
      cols = tf.io.decode_raw(
          core_ops.io_file_read(
              filename, 12, 4, compression=compression
          ),
          tf.int32,
          little_endian=False,
      )
      lens = rows[0] * cols[0]
  
      dataset = tf.data.FixedLengthRecordDataset(
          filename,
          tf.cast(lens, tf.int64),
          header_bytes=16,
          compression_type=compression,
      )
      dataset = dataset.map(lambda e: tf.io.decode_raw(e, tf.uint8))
      dataset = dataset.map(
          lambda e: tf.reshape(e, tf.concat([rows, cols], axis=0))
      )
  
      self._dataset = dataset
      super().__init__(self._dataset._variant_tensor)
  
file_path: io/tensorflow_io/python/ops/mnist_dataset_ops.py
imports: import tensorflow
  from tensorflow_io.python.ops import core_ops
label_desc: Use image node_id 1 to create a new MNISTImageIODataset object from inherited base classes: tf.data with example: obj = MNISTImageIODataset(filename)