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Represents an iterator of a tf.data.Dataset.
tf.data.Iterator is the primary mechanism for enumerating elements of a tf.data.Dataset. It supports the Python Iterator protocol, which means it can be iterated over using a for-loop:
dataset = tf.data.Dataset.range(2) for element in dataset: print(element) tf.Tensor(0, shape=(), dtype=int64) tf.Tensor(1, shape=(), dtype=int64)
or by fetching individual elements explicitly via get_next():
dataset = tf.data.Dataset.range(2) iterator = iter(dataset) print(iterator.get_next()) tf.Tensor(0, shape=(), dtype=int64) print(iterator.get_next()) tf.Tensor(1, shape=(), dtype=int64)
In addition, non-raising iteration is supported via get_next_as_optional(), which returns the next element (if available) wrapped in a tf.experimental.Optional.
dataset = tf.data.Dataset.from_tensors(42) iterator = iter(dataset) optional = iterator.get_next_as_optional() print(optional.has_value()) tf.Tensor(True, shape=(), dtype=bool) optional = iterator.get_next_as_optional() print(optional.has_value()) tf.Tensor(False, shape=(), dtype=bool)
| Attributes | |
|---|---|
| element_spec | The type specification of an element of this iterator. dataset = tf.data.Dataset.from_tensors(42) iterator = iter(dataset) iterator.element_spec tf.TensorSpec(shape=(), dtype=tf.int32, name=None) For more information, read this guide. | 
get_next@abc.abstractmethod get_next()
Returns the next element.
dataset = tf.data.Dataset.from_tensors(42) iterator = iter(dataset) print(iterator.get_next()) tf.Tensor(42, shape=(), dtype=int32)
| Returns | |
|---|---|
| A (nested) structure of values matching tf.data.Iterator.element_spec. | 
| Raises | |
|---|---|
| tf.errors.OutOfRangeError: If the end of the iterator has been reached. | 
get_next_as_optional@abc.abstractmethod get_next_as_optional()
Returns the next element wrapped in tf.experimental.Optional.
If the iterator has reached the end of the sequence, the returned tf.experimental.Optional will have no value.
dataset = tf.data.Dataset.from_tensors(42) iterator = iter(dataset) optional = iterator.get_next_as_optional() print(optional.has_value()) tf.Tensor(True, shape=(), dtype=bool) print(optional.get_value()) tf.Tensor(42, shape=(), dtype=int32) optional = iterator.get_next_as_optional() print(optional.has_value()) tf.Tensor(False, shape=(), dtype=bool)
| Returns | |
|---|---|
| A tf.experimental.Optionalobject representing the next element. | 
__iter____iter__()
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Code samples licensed under the Apache 2.0 License.
    https://www.tensorflow.org/versions/r2.9/api_docs/python/tf/data/Iterator