tf.unstack

TensorFlow 2 version View source on GitHub

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

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.

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).

The list of Tensor objects unstacked from value.

ValueError If num is unspecified and cannot be inferred.
ValueError If axis is out of the range [-R, R).