Missed TensorFlow Dev Summit? Check out the video playlist. Watch recordings

tf.IndexedSlicesSpec

TensorFlow 1 version View source on GitHub

Type specification for a tf.IndexedSlices.

Inherits From: TypeSpec

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

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.

Attributes:

  • 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.