tf.OptionalSpec

TensorFlow 1 version View source on GitHub

Type specification for tf.experimental.Optional.

Inherits From: TypeSpec

tf.OptionalSpec(     element_spec )

For instance, tf.OptionalSpec can be used to define a tf.function that takes tf.experimental.Optional as an input argument:

@tf.function(input_signature=[tf.OptionalSpec(   tf.TensorSpec(shape=(), dtype=tf.int32, name=None))]) def maybe_square(optional):   if optional.has_value():     x = optional.get_value()     return x * x   return -1 optional = tf.experimental.Optional.from_value(5) print(maybe_square(optional)) tf.Tensor(25, shape=(), dtype=int32)

element_spec A nested structure of TypeSpec objects that represents the type specification of the optional element.
value_type The Python type for values that are compatible with this TypeSpec.

In particular, all values that are compatible with this TypeSpec must be an instance of this type.

Methods

from_value

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@staticmethod from_value(     value )

is_compatible_with

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is_compatible_with(     spec_or_value )

Returns true if spec_or_value is compatible with this TypeSpec.

most_specific_compatible_type

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most_specific_compatible_type(     other )

Returns the most specific TypeSpec compatible with self and other.

Args
other A TypeSpec.

Raises
ValueError If there is no TypeSpec that is compatible with both self and other.

__eq__

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__eq__(     other )

Return self==value.

__ne__

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__ne__(     other )

Return self!=value.