# Class TypeSpec

Specifies a TensorFlow value type.

# Aliases:

• Class tf.compat.v1.TypeSpec
• Class tf.compat.v1.data.experimental.Structure
• Class tf.compat.v2.TypeSpec tf.TypeSpecA provides metadata describing an object accepted or returned by TensorFlow APIs. Concrete subclasses, such as tf.TensorSpec and tf.RaggedTensorSpec, are used to describe different value types.

tf.functionFor example, 's input_signature argument accepts a list (or nested structure) of TypeSpecs.

Creating new subclasses of TypeSpec (outside of TensorFlow core) is not currently supported. In particular, we may make breaking changes to the private methods and properties defined by this base class.

# Properties

# value_type

The Python type for values that are compatible with this TypeSpec.

# Methods

# eq

View source

 __eq__(other)

Return self==value.

# ne

View source

 __ne__(other)

Return self!=value.

# is_compatible_with

View source

 is_compatible_with(spec_or_value)

Returns true if spec_or_value is compatible with this TypeSpec.

# most_specific_compatible_type

View source

 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.