tf.data.DatasetSpec

Type specification for tf.data.Dataset.

Inherits From: TypeSpec, TraceType

tf.data.DatasetSpec(
    element_spec, dataset_shape=()
)

See tf.TypeSpec for more information about TensorFlow type specifications.

dataset = tf.data.Dataset.range(3)
tf.data.DatasetSpec.from_value(dataset)
DatasetSpec(TensorSpec(shape=(), dtype=tf.int64, name=None), TensorShape([]))

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.

from_value

View source

@staticmethod
from_value(
    value
)

Creates a DatasetSpec for the given tf.data.Dataset value.

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

View source

is_subtype_of(
    other
)

See base class.

most_specific_common_supertype

View source

most_specific_common_supertype(
    others
)

See base class.

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__

View source

__eq__(
    other
)

Return self==value.

__ne__

View source

__ne__(
    other
) -> bool

Return self!=value.