tfr.data.build_sequence_example_serving_input_receiver_fn
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Creates a serving_input_receiver_fn for SequenceExample inputs.
tfr.data.build_sequence_example_serving_input_receiver_fn(
input_size,
context_feature_spec,
example_feature_spec,
default_batch_size=None
)
A string placeholder is used for inputs. Note that the context_feature_spec
and example_feature_spec shouldn't contain weights, labels or training
only features in general.
Args |
|---|
input_size
|
(int) The number of frames to keep in a SequenceExample. If
specified, truncation or padding may happen. Otherwise, set it to None to
allow dynamic list size (recommended).
|
context_feature_spec
|
(dict) Map from feature keys to FixedLenFeature or
VarLenFeature values.
|
example_feature_spec
|
(dict) Map from feature keys to FixedLenFeature or
VarLenFeature values.
|
default_batch_size
|
(int) Number of query examples expected per batch. Leave
unset for variable batch size (recommended).
|
Returns |
|---|
A tf.estimator.export.ServingInputReceiver object, which packages the
placeholders and the resulting feature Tensors together.
|
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Last updated 2023-09-29 UTC.
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