tf.data.experimental.get_single_element
Returns the single element in dataset as a nested structure of tensors.
tf.data.experimental.get_single_element(
dataset
)
This function enables you to use a tf.data.Dataset in a stateless "tensor-in tensor-out" expression, without creating an iterator. This can be useful when your preprocessing transformations are expressed as a Dataset, and you want to use the transformation at serving time.
For example:
def preprocessing_fn(input_str):
# ...
return image, label
input_batch = ... # input batch of BATCH_SIZE elements
dataset = (tf.data.Dataset.from_tensor_slices(input_batch)
.map(preprocessing_fn, num_parallel_calls=BATCH_SIZE)
.batch(BATCH_SIZE))
image_batch, label_batch = tf.data.experimental.get_single_element(dataset)
| Args | |
|---|---|
dataset |
A tf.data.Dataset object containing a single element. |
| Returns | |
|---|---|
A nested structure of tf.Tensor objects, corresponding to the single element of dataset. |
| Raises | |
|---|---|
TypeError |
if dataset is not a tf.data.Dataset object. InvalidArgumentError (at runtime): if dataset does not contain exactly one element. |
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/data/experimental/get_single_element