A transformation that parses Example
protos into a dict
of tensors.
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 individual
Example
protos.
This op parses serialized examples into a dictionary mapping keys to Tensor
,
SparseTensor
, and RaggedTensor
objects. features
is a dict from keys to
VarLenFeature
, RaggedFeature
, SparseFeature
, and FixedLenFeature
objects. Each VarLenFeature
and SparseFeature
is mapped to a
SparseTensor
; each RaggedFeature
is mapped to a RaggedTensor
; and each
FixedLenFeature
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. If
deterministic is None , the
tf.data.Options.experimental_deterministic dataset option (True by
default) is used to decide whether to produce elements
deterministically.
|
Raises |
ValueError
|
if features argument is None.
|