tf.data.experimental.Optional

TensorFlow 1 version View source on GitHub

Wraps a value that may/may not be present at runtime.

An 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.experimental.get_next_as_optional returns an Optional that either contains the next value of an iterator if one exists, or a "none" value that indicates the end of the sequence has been reached.

Optional can only be used by values that are convertible to Tensor or CompositeTensor.

value_structure The structure of the components of this optional.

Methods

from_value

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@staticmethod
from_value(
    value
)

Returns an Optional that wraps the given value.

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

Returns
An 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.

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.

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

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

none_from_structure

View source

@staticmethod
none_from_structure(
    value_structure
)

Returns an Optional that has no value.

Args
value_structure A Structure object representing the structure of the components of this optional.

Returns
An Optional that has no value.