Returns the single element in dataset
as a nested structure of tensors. (deprecated)
tf.contrib.data.get_single_element(
dataset
)
This function enables you to use a tf.data.Dataset
in a stateless
"tensor-in tensor-out" expression, without creating a
tf.compat.v1.data.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:
input_batch = tf.compat.v1.placeholder(tf.string, shape=[BATCH_SIZE])
def preprocessing_fn(input_str):
# ...
return image, label
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.
|