Class FixedLenSequenceFeature

tensorflow/python/ops/parsing_ops.py:157–187

Configuration for parsing a variable-length input feature into a `Tensor`. The resulting `Tensor` of parsing a single `SequenceExample` or `Example` has a static `shape` of `[None] + shape` and the specified `dtype`. The resulting `Tensor` of parsing a `batch_size` many `Example`s has a sta

@tf_export("io.FixedLenSequenceFeature",
           v1=["io.FixedLenSequenceFeature", "FixedLenSequenceFeature"])
class FixedLenSequenceFeature(collections.namedtuple(
    "FixedLenSequenceFeature",
    ["shape", "dtype", "allow_missing", "default_value"])):
  """Configuration for parsing a variable-length input feature into a `Tensor`.

  The resulting `Tensor` of parsing a single `SequenceExample` or `Example` has
  a static `shape` of `[None] + shape` and the specified `dtype`.
  The resulting `Tensor` of parsing a `batch_size` many `Example`s has
  a static `shape` of `[batch_size, None] + shape` and the specified `dtype`.
  The entries in the `batch` from different `Examples` will be padded with
  `default_value` to the maximum length present in the `batch`.

  To treat a sparse input as dense, provide `allow_missing=True`; otherwise,
  the parse functions will fail on any examples missing this feature.

  Fields:
    shape: Shape of input data for dimension 2 and higher. First dimension is
      of variable length `None`.
    dtype: Data type of input.
    allow_missing: Whether to allow this feature to be missing from a feature
      list item. Is available only for parsing `SequenceExample` not for
      parsing `Examples`.
    default_value: Scalar value to be used to pad multiple `Example`s to their
      maximum length. Irrelevant for parsing a single `Example` or
      `SequenceExample`. Defaults to "" for dtype string and 0 otherwise
      (optional).
  """

  def __new__(cls, shape, dtype, allow_missing=False, default_value=None):
    return super(FixedLenSequenceFeature, cls).__new__(
        cls, shape, dtype, allow_missing, default_value)


def _features_to_raw_params(features, types):