tf.FixedLenSequenceFeature
tf.FixedLenSequenceFeature
class tf.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.
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).
Properties
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
Methods
__new__
__new__( _cls, shape, dtype, allow_missing=False, default_value=None )
Create new instance of FixedLenSequenceFeature(shape, dtype, allow_missing, default_value)
© 2017 The TensorFlow Authors. All rights reserved.
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