TensorFlow 2 version | View source on GitHub |
Stacks a list of rank-R
tensors into one rank-(R+1)
tensor.
tf.stack(
values, axis=0, name='stack'
)
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]) # [[1, 4], [2, 5], [3, 6]] (Pack along first dim.)
tf.stack([x, y, z], axis=1) # [[1, 2, 3], [4, 5, 6]]
This is the opposite of unstack. The numpy equivalent is
tf.stack([x, y, z]) = np.stack([x, y, z])
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).
|