|  TensorFlow 1 version |  View source on GitHub | 
Configuration for parsing a variable-length input feature into a Tensor.
tf.io.FixedLenSequenceFeature(
    shape, dtype, allow_missing=False, default_value=None
)
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 Examples 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- SequenceExamplenot for parsing- Examples.
- default_value: Scalar value to be used to pad multiple- Examples to their maximum length. Irrelevant for parsing a single- Exampleor- SequenceExample. Defaults to "" for dtype string and 0 otherwise (optional).
| Attributes | |
|---|---|
| shape | |
| dtype | |
| allow_missing | |
| default_value | |