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)
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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Last updated 2021-02-18 UTC.
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