tf.unstack

Unpacks the given dimension of a rank-R tensor into rank-(R-1) tensors.

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Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.unstack

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).