Stacks a list of rank-R tensors into one rank-(R+1) RaggedTensor.
tf.ragged.stack(
values, axis=0, name=None
)
Given a list of tensors or ragged tensors with the same rank R
(R >= axis), returns a rank-R+1 RaggedTensor result such that
result[i0...iaxis] is [value[i0...iaxis] for value in values].
Example:
>>> t1 = tf.ragged.constant([[1, 2], [3, 4, 5]])
>>> t2 = tf.ragged.constant([[6], [7, 8, 9]])
>>> tf.ragged.stack([t1, t2], axis=0)
[[[1, 2], [3, 4, 5]], [[6], [7, 9, 0]]]
>>> tf.ragged.stack([t1, t2], axis=1)
[[[1, 2], [6]], [[3, 4, 5], [7, 8, 9]]]
Args |
|---|
values
|
A list of tf.Tensor or tf.RaggedTensor. May not be empty. All
values must have the same rank and the same dtype; but unlike
tf.stack, they can have arbitrary dimension sizes.
|
axis
|
A python integer, indicating the dimension along which to stack.
(Note: Unlike tf.stack, the axis parameter must be statically known.)
Negative values are supported only if the rank of at least one
values value is statically known.
|
name
|
A name prefix for the returned tensor (optional).
|
Returns |
|---|
A RaggedTensor with rank R+1.
result.ragged_rank=1+max(axis, max(rt.ragged_rank for rt in values])).
|
Raises |
|---|
ValueError
|
If values is empty, if axis is out of bounds or if
the input tensors have different ranks.
|
TensorFlow 1 version
View source on GitHub