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 . |
© 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/raw_ops/Unpack