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tf.stack

Stacks a list of rank-R tensors into one rank-(R+1) tensor.

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/r2.4/api_docs/python/tf/stack