tf.TensorArraySpec

Type specification for a tf.TensorArray.

Inherits From: TypeSpec, TraceType

tf.TensorArraySpec(
    element_shape=None,
    dtype=tf.dtypes.float32,
    dynamic_size=False,
    infer_shape=True
)

element_shape The shape of each element in the TensorArray.
dtype Data type of the TensorArray.
dynamic_size Whether the TensorArray can grow past its initial size.
infer_shape Whether shape inference is enabled.

value_type

Methods

from_value

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@staticmethod
from_value(
    value
)

is_compatible_with

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is_compatible_with(
    other
)

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

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is_subtype_of(
    other
)

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.

Args
other A TraceType object.

most_specific_common_supertype

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most_specific_common_supertype(
    others
)

Returns the most specific supertype of self and others.

Args
others A Sequence of TypeSpec.

Returns None if a supertype does not exist.

most_specific_compatible_type

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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
) -> bool

Return self==value.

__ne__

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__ne__(
    other
) -> bool

Return self!=value.