tf.experimental.Optional

Represents a value that may or may not be present.

View aliases

Main aliases

tf.data.experimental.Optional

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.data.experimental.Optional, tf.compat.v1.experimental.Optional

A tf.experimental.Optional can represent the result of an operation that may fail as a value, rather than raising an exception and halting execution. For example, tf.data.Iterator.get_next_as_optional() returns a tf.experimental.Optional that either contains the next element of an iterator if one exists, or an "empty" value that indicates the end of the sequence has been reached.

tf.experimental.Optional can only be used with values that are convertible to tf.Tensor or tf.CompositeTensor.

One can create a tf.experimental.Optional from a value using the from_value() method:

optional = tf.experimental.Optional.from_value(42)
print(optional.has_value())
tf.Tensor(True, shape=(), dtype=bool)
print(optional.get_value())
tf.Tensor(42, shape=(), dtype=int32)

or without a value using the empty() method:

optional = tf.experimental.Optional.empty(
  tf.TensorSpec(shape=(), dtype=tf.int32, name=None))
print(optional.has_value())
tf.Tensor(False, shape=(), dtype=bool)

Attributes
element_spec	The type specification of an element of this optional. optional = tf.experimental.Optional.from_value(42) print(optional.element_spec) tf.TensorSpec(shape=(), dtype=tf.int32, name=None)

Methods

empty

View source

@staticmethod
empty(
    element_spec
)

Returns an Optional that has no value.

Note: This method takes an argument that defines the structure of the value that would be contained in the returned Optional if it had a value.

optional = tf.experimental.Optional.empty(
  tf.TensorSpec(shape=(), dtype=tf.int32, name=None))
print(optional.has_value())
tf.Tensor(False, shape=(), dtype=bool)

Args
element_spec	A (nested) structure of tf.TypeSpec objects matching the structure of an element of this optional.

Returns
A tf.experimental.Optional with no value.

from_value

View source

@staticmethod
from_value(
    value
)

Returns a tf.experimental.Optional that wraps the given value.

optional = tf.experimental.Optional.from_value(42)
print(optional.has_value())
tf.Tensor(True, shape=(), dtype=bool)
print(optional.get_value())
tf.Tensor(42, shape=(), dtype=int32)

Args
value	A value to wrap. The value must be convertible to tf.Tensor or tf.CompositeTensor.

Returns
A tf.experimental.Optional that wraps value.

get_value

View source

@abc.abstractmethod
get_value(
    name=None
)

Returns the value wrapped by this optional.

If this optional does not have a value (i.e. self.has_value() evaluates to False), this operation will raise tf.errors.InvalidArgumentError at runtime.

optional = tf.experimental.Optional.from_value(42)
print(optional.get_value())
tf.Tensor(42, shape=(), dtype=int32)

Args
name	(Optional.) A name for the created operation.

Returns
The wrapped value.

has_value

View source

@abc.abstractmethod
has_value(
    name=None
)

Returns a tensor that evaluates to True if this optional has a value.

optional = tf.experimental.Optional.from_value(42)
print(optional.has_value())
tf.Tensor(True, shape=(), dtype=bool)

Args
name	(Optional.) A name for the created operation.

Returns
A scalar tf.Tensor of type tf.bool.