tf.data.experimental.TFRecordWriter

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Writes a dataset to a TFRecord file.

tf.data.experimental.TFRecordWriter(
    filename, compression_type=None
)

The elements of the dataset must be scalar strings. To serialize dataset elements as strings, you can use the tf.io.serialize_tensor function.

dataset = tf.data.Dataset.range(3)
dataset = dataset.map(tf.io.serialize_tensor)
writer = tf.data.experimental.TFRecordWriter("/path/to/file.tfrecord")
writer.write(dataset)

To read back the elements, use TFRecordDataset.

dataset = tf.data.TFRecordDataset("/path/to/file.tfrecord")
dataset = dataset.map(lambda x: tf.io.parse_tensor(x, tf.int64))

To shard a dataset across multiple TFRecord files:

dataset = ... # dataset to be written

def reduce_func(key, dataset):
  filename = tf.strings.join([PATH_PREFIX, tf.strings.as_string(key)])
  writer = tf.data.experimental.TFRecordWriter(filename)
  writer.write(dataset.map(lambda _, x: x))
  return tf.data.Dataset.from_tensors(filename)

dataset = dataset.enumerate()
dataset = dataset.apply(tf.data.experimental.group_by_window(
  lambda i, _: i % NUM_SHARDS, reduce_func, tf.int64.max
))

Args:

Methods

write

View source

write(
    dataset
)

Writes a dataset to a TFRecord file.

An operation that writes the content of the specified dataset to the file specified in the constructor.

If the file exists, it will be overwritten.

Args:

Returns:

In graph mode, this returns an operation which when executed performs the write. In eager mode, the write is performed by the method itself and there is no return value.

Raises TypeError: if dataset is not a tf.data.Dataset. TypeError: if the elements produced by the dataset are not scalar strings.