tf.unstack(
value,
num=None,
axis=0,
name='unstack'
)
Defined in tensorflow/python/ops/array_ops.py
.
Unpacks the given dimension of a rank-R
tensor into rank-(R-1)
tensors.
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 rankR > 0
Tensor
to be unstacked.num
: Anint
. The length of the dimensionaxis
. Automatically inferred ifNone
(the default).axis
: Anint
. 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
: Ifnum
is unspecified and cannot be inferred.ValueError
: Ifaxis
is out of the range [-R, R).