tf.raw_ops.Unpack
Unpacks a given dimension of a rank-R tensor into num rank-(R-1) tensors.
tf.raw_ops.Unpack(
value, num, axis=0, name=None
)
Unpacks num tensors from value by chipping it along the axis dimension. 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 pack.
| Args | |
|---|---|
value | A Tensor. 1-D or higher, with axis dimension size equal to num. |
num | An int that is >= 0. |
axis | An optional int. Defaults to 0. Dimension along which to unpack. Negative values wrap around, so the valid range is [-R, R). |
name | A name for the operation (optional). |
| Returns | |
|---|---|
A list of num Tensor objects with the same type as value. |
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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/raw_ops/Unpack