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.
|