TensorFlow 1 version
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View source on GitHub
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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 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 parsingSequenceExamplenot for parsingExamples.default_value: Scalar value to be used to pad multipleExamples to their maximum length. Irrelevant for parsing a singleExampleorSequenceExample. Defaults to "" for dtype string and 0 otherwise (optional).
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shape
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dtype
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allow_missing
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default_value
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TensorFlow 1 version
View source on GitHub