ML Community Day is November 9! Join us for updates from TensorFlow, JAX, and more Learn more

tf.RaggedTensorSpec

Type specification for a tf.RaggedTensor.

Inherits From: TypeSpec

Used in the notebooks

Used in the guide

shape The shape of the RaggedTensor, or None to allow any shape. If a shape is specified, then all ragged dimensions must have size None.
dtype tf.DType of values in the RaggedTensor.
ragged_rank Python integer, the number of times the RaggedTensor's flat_values is partitioned. Defaults to shape.ndims - 1.
row_splits_dtype dtype for the RaggedTensor's row_splits tensor. One of tf.int32 or tf.int64.
flat_values_spec TypeSpec for flat_value of the RaggedTensor. It shall be provided when the flat_values is a CompositeTensor rather then Tensor. If both dtype and flat_values_spec and are provided, dtype must be the same as flat_values_spec.dtype. (experimental)

dtype The tf.dtypes.DType specified by this type for the RaggedTensor.

rt = tf.ragged.constant([["a"], ["b", "c"]], dtype=tf.string)
tf.type_spec_from_value(rt).dtype
tf.string

flat_values_spec The TypeSpec of the flat_values of RaggedTensor.
ragged_rank The number of times the RaggedTensor's flat_values is partitioned.

Defaults to shape.ndims - 1.

values = tf.ragged.constant([[1, 2, 3], [4], [5, 6], [7, 8, 9, 10]])
tf.type_spec_from_value(values).ragged_rank
1
rt1 = tf.RaggedTensor.from_uniform_row_length(values, 2)
tf.type_spec_from_value(rt1).ragged_rank
2

row_splits_dtype The tf.dtypes.DType of the RaggedTensor's row_splits.

rt = tf.ragged.constant([[1, 2, 3], [4]], row_splits_dtype=tf.int64)
tf.type_spec_from_value(rt).row_splits_dtype
tf.int64

shape The statically known shape of the RaggedTensor.

rt = tf.ragged.constant([[0], [1, 2]])