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 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 lengthNone
.dtype
: Data type of input.allow_missing
: Whether to allow this feature to be missing from a feature list item. Is available only for parsingSequenceExample
not for parsingExamples
.default_value
: Scalar value to be used to pad multipleExample
s to their maximum length. Irrelevant for parsing a singleExample
orSequenceExample
. Defaults to "" for dtype string and 0 otherwise (optional).
Attributes | |
---|---|
shape
|
|
dtype
|
|
allow_missing
|
|
default_value
|