TensorFlow

API

 tf.data / experimental / experimental.StatsOptions


Writes a dataset to a TFRecord file.

Used in the notebooks

Used in the tutorials

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
))

filename a string path indicating where to write the TFRecord data.
compression_type (Optional.) a string indicating what type of compression to use when writing the file. See tf.io.TFRecordCompressionType for what types of compression are available. Defaults to None.

Methods

write

View source

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
dataset a tf.data.Dataset whose elements are to be written to a file

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.


此页内容是否对您有帮助