tf.unstack
Unpacks the given dimension of a rank-R tensor into rank-(R-1) tensors.
tf.unstack(
value, num=None, axis=0, name='unstack'
)
Unpacks num tensors from value by chipping it along the axis dimension. If num is not specified (the default), it is inferred from value's shape. If value.shape[axis] is not known, ValueError is raised.
For example, given a tensor of shape (A, B, C, D);
If axis == 0 then the i'th tensor in output is the slice value[i, :, :, :] and each tensor in output will have shape (B, C, D). (Note that the dimension unpacked along is gone, unlike split).
If axis == 1 then the i'th tensor in output is the slice value[:, i, :, :] and each tensor in output will have shape (A, C, D). Etc.
This is the opposite of stack.
| Args | |
|---|---|
value |
A rank R > 0 Tensor to be unstacked. |
num |
An int. The length of the dimension axis. Automatically inferred if None (the default). |
axis |
An int. The axis to unstack along. Defaults to the first dimension. Negative values wrap around, so the valid range is [-R, R). |
name |
A name for the operation (optional). |
| Returns | |
|---|---|
The list of Tensor objects unstacked from value. |
| Raises | |
|---|---|
ValueError |
If num is unspecified and cannot be inferred. |
ValueError |
If axis is out of the range [-R, R). |
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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/unstack