tf.FixedLenSequenceFeature.__new__(_cls, shape, dtype, allow_missing=False) Create new instance of FixedLenSequenceFeature(shape, dtype, allow_missing)

tf.FixedLenSequenceFeature.__getstate__() Exclude the OrderedDict from pickling

tf.FixedLenSequenceFeature.__getnewargs__() Return self as a plain tuple. Used by copy and pickle.

tf.FixedLenSequenceFeature.shape Alias for field number 0

tf.FixedLenSequenceFeature.dtype Alias for field number 1

tf.FixedLenSequenceFeature.allow_missing Alias for field number 2

class tf.FixedLenSequenceFeature Configuration for a dense input feature in a sequence item. 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. dtype: Data type of input. allow_missing: Whether to allow this feature to be missing from a feature list item.

tf.FixedLengthRecordReader.__init__(record_bytes, header_bytes=None, footer_bytes=None, name=None) Create a FixedLengthRecordReader. Args: record_bytes: An int. header_bytes: An optional int. Defaults to 0. footer_bytes: An optional int. Defaults to 0. name: A name for the operation (optional).

tf.FixedLengthRecordReader.supports_serialize Whether the Reader implementation can serialize its state.

tf.FixedLengthRecordReader.serialize_state(name=None) Produce a string tensor that encodes the state of a reader. Not all Readers support being serialized, so this can produce an Unimplemented error. Args: name: A name for the operation (optional). Returns: A string Tensor.