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([]))

element_spec The inner element spec.
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

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.

Args
spec_or_value A TypeSpec or TypeSpec associated value to compare against.

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.

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
) -> bool

Return self!=value.