tf.data.experimental.parse_example_dataset | TensorFlow v2.16.1 (original) (raw)
A transformation that parses Example protos into a dict of tensors. (deprecated)
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tf.compat.v1.data.experimental.parse_example_dataset
tf.data.experimental.parse_example_dataset(
features, num_parallel_calls=1, deterministic=None
)
Parses a number of serialized Example protos given in serialized. We refer to serialized as a batch with batch_size many entries of individualExample protos.
This op parses serialized examples into a dictionary mapping keys to Tensor,SparseTensor, and RaggedTensor objects. features is a dict from keys toVarLenFeature, RaggedFeature, SparseFeature, and FixedLenFeatureobjects. Each VarLenFeature and SparseFeature is mapped to aSparseTensor; each RaggedFeature is mapped to a RaggedTensor; and eachFixedLenFeature is mapped to a Tensor. See tf.io.parse_example for more details about feature dictionaries.
| Args | |
|---|---|
| features | A dict mapping feature keys to FixedLenFeature,VarLenFeature, RaggedFeature, and SparseFeature values. |
| num_parallel_calls | (Optional.) A tf.int32 scalar tf.Tensor, representing the number of parsing processes to call in parallel. |
| deterministic | (Optional.) A boolean controlling whether determinism should be traded for performance by allowing elements to be produced out of order if some parsing calls complete faster than others. Ifdeterministic is None, thetf.data.Options.deterministic dataset option (True by default) is used to decide whether to produce elements deterministically. |
| Returns |
|---|
| A dataset transformation function, which can be passed totf.data.Dataset.apply. |
| Raises | |
|---|---|
| ValueError | if features argument is None. |