tf.data.experimental.get_structure

Returns the type signature for elements of the input dataset / iterator.

View aliases

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.data.experimental.get_structure

tf.data.experimental.get_structure(
    dataset_or_iterator
)

For example, to get the structure of a tf.data.Dataset:

dataset = tf.data.Dataset.from_tensor_slices([1, 2, 3])
tf.data.experimental.get_structure(dataset)
TensorSpec(shape=(), dtype=tf.int32, name=None)

dataset = tf.data.experimental.from_list([(1, 'a'), (2, 'b'), (3, 'c')])
tf.data.experimental.get_structure(dataset)
(TensorSpec(shape=(), dtype=tf.int32, name=None),
 TensorSpec(shape=(), dtype=tf.string, name=None))

To get the structure of an tf.data.Iterator:

dataset = tf.data.Dataset.from_tensor_slices([1, 2, 3])
tf.data.experimental.get_structure(iter(dataset))
TensorSpec(shape=(), dtype=tf.int32, name=None)

Args
dataset_or_iterator	A tf.data.Dataset or an tf.data.Iterator.

Returns
A (nested) structure of tf.TypeSpec objects matching the structure of an element of dataset_or_iterator and specifying the type of individual components.

Raises
TypeError	If input is not a tf.data.Dataset or an tf.data.Iterator object.