Missed TensorFlow World? Check out the recap. Learn more

tf.IndexedSlicesSpec

TensorFlow 1 version View source on GitHub

Class IndexedSlicesSpec

Type specification for a tf.IndexedSlices.

Inherits From: TypeSpec

Aliases:

__init__

View source

__init__(
    shape=None,
    dtype=tf.dtypes.float32,
    indices_dtype=tf.dtypes.int64,
    dense_shape_dtype=None,
    indices_shape=None
)

Constructs a type specification for a tf.IndexedSlices.

Args:

  • shape: The dense shape of the IndexedSlices, or None to allow any dense shape.
  • dtype: tf.DType of values in the IndexedSlices.
  • indices_dtype: tf.DType of the indices in the IndexedSlices. One of tf.int32 or tf.int64.
  • dense_shape_dtype: tf.DType of the dense_shape in the IndexedSlices. One of tf.int32, tf.int64, or None (if the IndexedSlices has no dense_shape tensor).
  • indices_shape: The shape of the indices component, which indicates how many slices are in the IndexedSlices.

Properties

value_type

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.