tf.data.experimental.parse_example_dataset
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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.deterministic dataset option (True by default) is used
to decide whether to produce elements deterministically.
|
Raises |
|---|
ValueError
|
if features argument is None.
|
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Last updated 2023-03-17 UTC.
[null,null,["Last updated 2023-03-17 UTC."],[],[],null,["# tf.data.experimental.parse_example_dataset\n\n\u003cbr /\u003e\n\n|------------------------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.9.3/tensorflow/python/data/experimental/ops/parsing_ops.py#L106-L160) |\n\nA transformation that parses `Example` protos into a `dict` of tensors.\n\n#### View aliases\n\n\n**Compat aliases for migration**\n\nSee\n[Migration guide](https://www.tensorflow.org/guide/migrate) for\nmore details.\n\n[`tf.compat.v1.data.experimental.parse_example_dataset`](https://www.tensorflow.org/api_docs/python/tf/data/experimental/parse_example_dataset)\n\n\u003cbr /\u003e\n\n tf.data.experimental.parse_example_dataset(\n features, num_parallel_calls=1, deterministic=None\n )\n\nParses a number of serialized `Example` protos given in `serialized`. We refer\nto `serialized` as a batch with `batch_size` many entries of individual\n`Example` protos.\n\nThis op parses serialized examples into a dictionary mapping keys to `Tensor`,\n`SparseTensor`, and `RaggedTensor` objects. `features` is a dict from keys to\n`VarLenFeature`, `RaggedFeature`, `SparseFeature`, and `FixedLenFeature`\nobjects. Each `VarLenFeature` and `SparseFeature` is mapped to a\n`SparseTensor`; each `RaggedFeature` is mapped to a `RaggedTensor`; and each\n`FixedLenFeature` is mapped to a `Tensor`. See [`tf.io.parse_example`](../../../tf/io/parse_example) for more\ndetails about feature dictionaries.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|----------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `features` | A `dict` mapping feature keys to `FixedLenFeature`, `VarLenFeature`, `RaggedFeature`, and `SparseFeature` values. |\n| `num_parallel_calls` | (Optional.) A [`tf.int32`](../../../tf#int32) scalar [`tf.Tensor`](../../../tf/Tensor), representing the number of parsing processes to call in parallel. |\n| `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.deterministic`](../../../tf/data/Options#deterministic) dataset option (`True` by default) is used to decide whether to produce elements deterministically. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A dataset transformation function, which can be passed to [`tf.data.Dataset.apply`](../../../tf/data/Dataset#apply). ||\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Raises ------ ||\n|--------------|-------------------------------|\n| `ValueError` | if features argument is None. |\n\n\u003cbr /\u003e"]]
View source on GitHub