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A transformation that parses Example
protos into a dict
of tensors.
Aliases:
tf.compat.v1.data.experimental.parse_example_dataset
tf.compat.v2.data.experimental.parse_example_dataset
tf.data.experimental.parse_example_dataset(
features,
num_parallel_calls=1
)
Parses a number of serialized Example
protos given in serialized
. We refer
to serialized
as a batch with batch_size
many entries of individual
Example
protos.
This op parses serialized examples into a dictionary mapping keys to Tensor
and SparseTensor
objects. features
is a dict from keys to VarLenFeature
,
SparseFeature
, and FixedLenFeature
objects. Each VarLenFeature
and SparseFeature
is mapped to a SparseTensor
, and each
FixedLenFeature
is mapped to a Tensor
. See tf.io.parse_example
for more
details about feature dictionaries.
Args:
features
: Adict
mapping feature keys toFixedLenFeature
,VarLenFeature
, andSparseFeature
values.num_parallel_calls
: (Optional.) Atf.int32
scalartf.Tensor
, representing the number of parsing processes to call in parallel.
Returns:
A dataset transformation function, which can be passed to
tf.data.Dataset.apply
.
Raises:
ValueError
: if features argument is None.