tf.stack
Stacks a list of rank-R tensors into one rank-(R+1) tensor.
tf.stack(
values, axis=0, name='stack'
)
See also tf.concat, tf.tile, tf.repeat.
Packs the list of tensors in values into a tensor with rank one higher than each tensor in values, by packing them along the axis dimension. Given a list of length N of tensors of shape (A, B, C);
if axis == 0 then the output tensor will have the shape (N, A, B, C). if axis == 1 then the output tensor will have the shape (A, N, B, C). Etc.
For example:
x = tf.constant([1, 4])
y = tf.constant([2, 5])
z = tf.constant([3, 6])
tf.stack([x, y, z])
<tf.Tensor: shape=(3, 2), dtype=int32, numpy=
array([[1, 4],
[2, 5],
[3, 6]], dtype=int32)>
tf.stack([x, y, z], axis=1)
<tf.Tensor: shape=(2, 3), dtype=int32, numpy=
array([[1, 2, 3],
[4, 5, 6]], dtype=int32)>
This is the opposite of unstack. The numpy equivalent is np.stack
np.array_equal(np.stack([x, y, z]), tf.stack([x, y, z]))
True
| Args | |
|---|---|
values |
A list of Tensor objects with the same shape and type. |
axis |
An int. The axis to stack along. Defaults to the first dimension. Negative values wrap around, so the valid range is [-(R+1), R+1). |
name |
A name for this operation (optional). |
| Returns | |
|---|---|
output |
A stacked Tensor with the same type as values. |
| Raises | |
|---|---|
ValueError |
If axis is out of the range [-(R+1), R+1). |
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/stack