tf.TypeSpec

Specifies a TensorFlow value type.

Inherits From: TraceType

A tf.TypeSpec 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.

For example, tf.function'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.

Example:

spec = tf.TensorSpec(shape=[None, None], dtype=tf.int32)
@tf.function(input_signature=[spec])
def double(x):
  return x * 2
double(tf.constant([[1, 2], [3, 4]]))
<tf.Tensor: shape=(2, 2), dtype=int32,
    numpy=array([[2, 4], [6, 8]], dtype=int32)>

Methods

experimental_as_proto

View source

experimental_as_proto() -> struct_pb2.TypeSpecProto

Returns a proto representation of the TypeSpec instance.

Do NOT override for custom non-TF types.

experimental_from_proto

View source

@classmethod
experimental_from_proto(
    proto: struct_pb2.TypeSpecProto
) -> 'TypeSpec'

Returns a TypeSpec instance based on the serialized proto.

Do NOT override for custom non-TF types.

experimental_type_proto

View source

@classmethod
experimental_type_proto() -> Type[struct_pb2.TypeSpecProto]

Returns the type of proto associated with TypeSpec serialization.

Do NOT override for custom non-TF types.

is_compatible_with

View source

is_compatible_with(
    spec_or_value
)

Returns true if spec_or_value is compatible with this TypeSpec.

Prefer using "is_subtype_of" and "most_specific_common_supertype" wherever possible.

is_subtype_of

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is_subtype_of(
    other: tf.types.experimental.TraceType
) -> bool

Returns True if self is a subtype of other.

Implements the tf.types.experimental.func.TraceType interface.

If not overridden by a subclass, the default behavior is to assume the TypeSpec is covariant upon attributes that implement TraceType and invariant upon rest of the attributes as well as the structure and type of the TypeSpec.

most_specific_common_supertype

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most_specific_common_supertype(
    others: Sequence[tf.types.experimental.TraceType]
) -> Optional['TypeSpec']

Returns the most specific supertype TypeSpec of self and others.

Implements the tf.types.experimental.func.TraceType interface.

If not overridden by a subclass, the default behavior is to assume the TypeSpec is covariant upon attributes that implement TraceType and invariant upon rest of the attributes as well as the structure and type of the TypeSpec.

most_specific_compatible_type

View source

most_specific_compatible_type(
    other: 'TypeSpec'
) -> 'TypeSpec'

Returns the most specific TypeSpec compatible with self and other. (deprecated)

Deprecated. Please use most_specific_common_supertype instead. Do not override this function.

__eq__

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__eq__(
    other
) -> bool

Return self==value.

__ne__

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__ne__(
    other
) -> bool

Return self!=value.