FixedLenSequenceFeature
Defined in tensorflow/python/ops/parsing_ops.py
.
See the guide: Inputs and Readers > Converting
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.
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).allow_missing
Alias for field number 2
default_value
Alias for field number 3
dtype
Alias for field number 1
shape
Alias for field number 0
__new__
@staticmethod __new__( cls, shape, dtype, allow_missing=False, default_value=None )
Create new instance of FixedLenSequenceFeature(shape, dtype, allow_missing, default_value)
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/FixedLenSequenceFeature